As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Source code for google.cloud.retail_v2alpha.services.generative_question_service.client

# -*- coding: utf-8 -*-
# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from collections import OrderedDict
import os
import re
from typing import (
    Callable,
    Dict,
    Mapping,
    MutableMapping,
    MutableSequence,
    Optional,
    Sequence,
    Tuple,
    Type,
    Union,
    cast,
)
import warnings

from google.api_core import client_options as client_options_lib
from google.api_core import exceptions as core_exceptions
from google.api_core import gapic_v1
from google.api_core import retry as retries
from google.auth import credentials as ga_credentials  # type: ignore
from google.auth.exceptions import MutualTLSChannelError  # type: ignore
from google.auth.transport import mtls  # type: ignore
from google.auth.transport.grpc import SslCredentials  # type: ignore
from google.oauth2 import service_account  # type: ignore

from google.cloud.retail_v2alpha import gapic_version as package_version

try:
    OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault, None]
except AttributeError:  # pragma: NO COVER
    OptionalRetry = Union[retries.Retry, object, None]  # type: ignore

from google.cloud.location import locations_pb2  # type: ignore
from google.longrunning import operations_pb2  # type: ignore
from google.protobuf import field_mask_pb2  # type: ignore

from google.cloud.retail_v2alpha.types import (
    generative_question,
    generative_question_service,
)

from .transports.base import DEFAULT_CLIENT_INFO, GenerativeQuestionServiceTransport
from .transports.grpc import GenerativeQuestionServiceGrpcTransport
from .transports.grpc_asyncio import GenerativeQuestionServiceGrpcAsyncIOTransport
from .transports.rest import GenerativeQuestionServiceRestTransport


class GenerativeQuestionServiceClientMeta(type):
    """Metaclass for the GenerativeQuestionService client.

    This provides class-level methods for building and retrieving
    support objects (e.g. transport) without polluting the client instance
    objects.
    """

    _transport_registry = (
        OrderedDict()
    )  # type: Dict[str, Type[GenerativeQuestionServiceTransport]]
    _transport_registry["grpc"] = GenerativeQuestionServiceGrpcTransport
    _transport_registry["grpc_asyncio"] = GenerativeQuestionServiceGrpcAsyncIOTransport
    _transport_registry["rest"] = GenerativeQuestionServiceRestTransport

    def get_transport_class(
        cls,
        label: Optional[str] = None,
    ) -> Type[GenerativeQuestionServiceTransport]:
        """Returns an appropriate transport class.

        Args:
            label: The name of the desired transport. If none is
                provided, then the first transport in the registry is used.

        Returns:
            The transport class to use.
        """
        # If a specific transport is requested, return that one.
        if label:
            return cls._transport_registry[label]

        # No transport is requested; return the default (that is, the first one
        # in the dictionary).
        return next(iter(cls._transport_registry.values()))


[docs]class GenerativeQuestionServiceClient(metaclass=GenerativeQuestionServiceClientMeta): """Service for managing LLM generated questions in search serving. """ @staticmethod def _get_default_mtls_endpoint(api_endpoint): """Converts api endpoint to mTLS endpoint. Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to "*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively. Args: api_endpoint (Optional[str]): the api endpoint to convert. Returns: str: converted mTLS api endpoint. """ if not api_endpoint: return api_endpoint mtls_endpoint_re = re.compile( r"(?P<name>[^.]+)(?P<mtls>\.mtls)?(?P<sandbox>\.sandbox)?(?P<googledomain>\.googleapis\.com)?" ) m = mtls_endpoint_re.match(api_endpoint) name, mtls, sandbox, googledomain = m.groups() if mtls or not googledomain: return api_endpoint if sandbox: return api_endpoint.replace( "sandbox.googleapis.com", "mtls.sandbox.googleapis.com" ) return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com") # Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead. DEFAULT_ENDPOINT = "retail.googleapis.com" DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore DEFAULT_ENDPOINT ) _DEFAULT_ENDPOINT_TEMPLATE = "retail.{UNIVERSE_DOMAIN}" _DEFAULT_UNIVERSE = "googleapis.com"
[docs] @classmethod def from_service_account_info(cls, info: dict, *args, **kwargs): """Creates an instance of this client using the provided credentials info. Args: info (dict): The service account private key info. args: Additional arguments to pass to the constructor. kwargs: Additional arguments to pass to the constructor. Returns: GenerativeQuestionServiceClient: The constructed client. """ credentials = service_account.Credentials.from_service_account_info(info) kwargs["credentials"] = credentials return cls(*args, **kwargs)
[docs] @classmethod def from_service_account_file(cls, filename: str, *args, **kwargs): """Creates an instance of this client using the provided credentials file. Args: filename (str): The path to the service account private key json file. args: Additional arguments to pass to the constructor. kwargs: Additional arguments to pass to the constructor. Returns: GenerativeQuestionServiceClient: The constructed client. """ credentials = service_account.Credentials.from_service_account_file(filename) kwargs["credentials"] = credentials return cls(*args, **kwargs)
from_service_account_json = from_service_account_file @property def transport(self) -> GenerativeQuestionServiceTransport: """Returns the transport used by the client instance. Returns: GenerativeQuestionServiceTransport: The transport used by the client instance. """ return self._transport
[docs] @staticmethod def catalog_path( project: str, location: str, catalog: str, ) -> str: """Returns a fully-qualified catalog string.""" return "projects/{project}/locations/{location}/catalogs/{catalog}".format( project=project, location=location, catalog=catalog, )
[docs] @staticmethod def parse_catalog_path(path: str) -> Dict[str, str]: """Parses a catalog path into its component segments.""" m = re.match( r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/catalogs/(?P<catalog>.+?)$", path, ) return m.groupdict() if m else {}
[docs] @staticmethod def common_billing_account_path( billing_account: str, ) -> str: """Returns a fully-qualified billing_account string.""" return "billingAccounts/{billing_account}".format( billing_account=billing_account, )
[docs] @staticmethod def parse_common_billing_account_path(path: str) -> Dict[str, str]: """Parse a billing_account path into its component segments.""" m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path) return m.groupdict() if m else {}
[docs] @staticmethod def common_folder_path( folder: str, ) -> str: """Returns a fully-qualified folder string.""" return "folders/{folder}".format( folder=folder, )
[docs] @staticmethod def parse_common_folder_path(path: str) -> Dict[str, str]: """Parse a folder path into its component segments.""" m = re.match(r"^folders/(?P<folder>.+?)$", path) return m.groupdict() if m else {}
[docs] @staticmethod def common_organization_path( organization: str, ) -> str: """Returns a fully-qualified organization string.""" return "organizations/{organization}".format( organization=organization, )
[docs] @staticmethod def parse_common_organization_path(path: str) -> Dict[str, str]: """Parse a organization path into its component segments.""" m = re.match(r"^organizations/(?P<organization>.+?)$", path) return m.groupdict() if m else {}
[docs] @staticmethod def common_project_path( project: str, ) -> str: """Returns a fully-qualified project string.""" return "projects/{project}".format( project=project, )
[docs] @staticmethod def parse_common_project_path(path: str) -> Dict[str, str]: """Parse a project path into its component segments.""" m = re.match(r"^projects/(?P<project>.+?)$", path) return m.groupdict() if m else {}
[docs] @staticmethod def common_location_path( project: str, location: str, ) -> str: """Returns a fully-qualified location string.""" return "projects/{project}/locations/{location}".format( project=project, location=location, )
[docs] @staticmethod def parse_common_location_path(path: str) -> Dict[str, str]: """Parse a location path into its component segments.""" m = re.match(r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path) return m.groupdict() if m else {}
[docs] @classmethod def get_mtls_endpoint_and_cert_source( cls, client_options: Optional[client_options_lib.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. Args: 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. Returns: Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the client cert source to use. Raises: google.auth.exceptions.MutualTLSChannelError: If any errors happen. """ warnings.warn( "get_mtls_endpoint_and_cert_source is deprecated. Use the api_endpoint property instead.", DeprecationWarning, ) if client_options is None: client_options = client_options_lib.ClientOptions() use_client_cert = os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto") if use_client_cert not in ("true", "false"): raise ValueError( "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`" ) if use_mtls_endpoint not in ("auto", "never", "always"): raise MutualTLSChannelError( "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`" ) # Figure out the client cert source to use. client_cert_source = None if use_client_cert == "true": if client_options.client_cert_source: client_cert_source = client_options.client_cert_source elif mtls.has_default_client_cert_source(): client_cert_source = mtls.default_client_cert_source() # Figure out which api endpoint to use. if client_options.api_endpoint is not None: api_endpoint = client_options.api_endpoint elif use_mtls_endpoint == "always" or ( use_mtls_endpoint == "auto" and client_cert_source ): api_endpoint = cls.DEFAULT_MTLS_ENDPOINT else: api_endpoint = cls.DEFAULT_ENDPOINT return api_endpoint, client_cert_source
@staticmethod def _read_environment_variables(): """Returns the environment variables used by the client. Returns: Tuple[bool, str, str]: returns the GOOGLE_API_USE_CLIENT_CERTIFICATE, GOOGLE_API_USE_MTLS_ENDPOINT, and GOOGLE_CLOUD_UNIVERSE_DOMAIN environment variables. Raises: ValueError: If GOOGLE_API_USE_CLIENT_CERTIFICATE is not any of ["true", "false"]. google.auth.exceptions.MutualTLSChannelError: If GOOGLE_API_USE_MTLS_ENDPOINT is not any of ["auto", "never", "always"]. """ use_client_cert = os.getenv( "GOOGLE_API_USE_CLIENT_CERTIFICATE", "false" ).lower() use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto").lower() universe_domain_env = os.getenv("GOOGLE_CLOUD_UNIVERSE_DOMAIN") if use_client_cert not in ("true", "false"): raise ValueError( "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`" ) if use_mtls_endpoint not in ("auto", "never", "always"): raise MutualTLSChannelError( "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`" ) return use_client_cert == "true", use_mtls_endpoint, universe_domain_env @staticmethod def _get_client_cert_source(provided_cert_source, use_cert_flag): """Return the client cert source to be used by the client. Args: provided_cert_source (bytes): The client certificate source provided. use_cert_flag (bool): A flag indicating whether to use the client certificate. Returns: bytes or None: The client cert source to be used by the client. """ client_cert_source = None if use_cert_flag: if provided_cert_source: client_cert_source = provided_cert_source elif mtls.has_default_client_cert_source(): client_cert_source = mtls.default_client_cert_source() return client_cert_source @staticmethod def _get_api_endpoint( api_override, client_cert_source, universe_domain, use_mtls_endpoint ): """Return the API endpoint used by the client. Args: api_override (str): The API endpoint override. If specified, this is always the return value of this function and the other arguments are not used. client_cert_source (bytes): The client certificate source used by the client. universe_domain (str): The universe domain used by the client. use_mtls_endpoint (str): How to use the mTLS endpoint, which depends also on the other parameters. Possible values are "always", "auto", or "never". Returns: str: The API endpoint to be used by the client. """ if api_override is not None: api_endpoint = api_override elif use_mtls_endpoint == "always" or ( use_mtls_endpoint == "auto" and client_cert_source ): _default_universe = GenerativeQuestionServiceClient._DEFAULT_UNIVERSE if universe_domain != _default_universe: raise MutualTLSChannelError( f"mTLS is not supported in any universe other than {_default_universe}." ) api_endpoint = GenerativeQuestionServiceClient.DEFAULT_MTLS_ENDPOINT else: api_endpoint = ( GenerativeQuestionServiceClient._DEFAULT_ENDPOINT_TEMPLATE.format( UNIVERSE_DOMAIN=universe_domain ) ) return api_endpoint @staticmethod def _get_universe_domain( client_universe_domain: Optional[str], universe_domain_env: Optional[str] ) -> str: """Return the universe domain used by the client. Args: client_universe_domain (Optional[str]): The universe domain configured via the client options. universe_domain_env (Optional[str]): The universe domain configured via the "GOOGLE_CLOUD_UNIVERSE_DOMAIN" environment variable. Returns: str: The universe domain to be used by the client. Raises: ValueError: If the universe domain is an empty string. """ universe_domain = GenerativeQuestionServiceClient._DEFAULT_UNIVERSE if client_universe_domain is not None: universe_domain = client_universe_domain elif universe_domain_env is not None: universe_domain = universe_domain_env if len(universe_domain.strip()) == 0: raise ValueError("Universe Domain cannot be an empty string.") return universe_domain def _validate_universe_domain(self): """Validates client's and credentials' universe domains are consistent. Returns: bool: True iff the configured universe domain is valid. Raises: ValueError: If the configured universe domain is not valid. """ # NOTE (b/349488459): universe validation is disabled until further notice. return True @property def api_endpoint(self): """Return the API endpoint used by the client instance. Returns: str: The API endpoint used by the client instance. """ return self._api_endpoint @property def universe_domain(self) -> str: """Return the universe domain used by the client instance. Returns: str: The universe domain used by the client instance. """ return self._universe_domain def __init__( self, *, credentials: Optional[ga_credentials.Credentials] = None, transport: Optional[ Union[ str, GenerativeQuestionServiceTransport, Callable[..., GenerativeQuestionServiceTransport], ] ] = None, client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, ) -> None: """Instantiates the generative question service client. Args: 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,GenerativeQuestionServiceTransport,Callable[..., GenerativeQuestionServiceTransport]]]): 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 GenerativeQuestionServiceTransport constructor. If set to None, a transport is chosen automatically. 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. Raises: google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport creation failed for any reason. """ self._client_options = client_options if isinstance(self._client_options, dict): self._client_options = client_options_lib.from_dict(self._client_options) if self._client_options is None: self._client_options = client_options_lib.ClientOptions() self._client_options = cast( client_options_lib.ClientOptions, self._client_options ) universe_domain_opt = getattr(self._client_options, "universe_domain", None) ( self._use_client_cert, self._use_mtls_endpoint, self._universe_domain_env, ) = GenerativeQuestionServiceClient._read_environment_variables() self._client_cert_source = ( GenerativeQuestionServiceClient._get_client_cert_source( self._client_options.client_cert_source, self._use_client_cert ) ) self._universe_domain = GenerativeQuestionServiceClient._get_universe_domain( universe_domain_opt, self._universe_domain_env ) self._api_endpoint = None # updated below, depending on `transport` # Initialize the universe domain validation. self._is_universe_domain_valid = False api_key_value = getattr(self._client_options, "api_key", None) if api_key_value and credentials: raise ValueError( "client_options.api_key and credentials are mutually exclusive" ) # Save or instantiate the transport. # Ordinarily, we provide the transport, but allowing a custom transport # instance provides an extensibility point for unusual situations. transport_provided = isinstance(transport, GenerativeQuestionServiceTransport) if transport_provided: # transport is a GenerativeQuestionServiceTransport instance. if credentials or self._client_options.credentials_file or api_key_value: raise ValueError( "When providing a transport instance, " "provide its credentials directly." ) if self._client_options.scopes: raise ValueError( "When providing a transport instance, provide its scopes " "directly." ) self._transport = cast(GenerativeQuestionServiceTransport, transport) self._api_endpoint = self._transport.host self._api_endpoint = ( self._api_endpoint or GenerativeQuestionServiceClient._get_api_endpoint( self._client_options.api_endpoint, self._client_cert_source, self._universe_domain, self._use_mtls_endpoint, ) ) if not transport_provided: import google.auth._default # type: ignore if api_key_value and hasattr( google.auth._default, "get_api_key_credentials" ): credentials = google.auth._default.get_api_key_credentials( api_key_value ) transport_init: Union[ Type[GenerativeQuestionServiceTransport], Callable[..., GenerativeQuestionServiceTransport], ] = ( GenerativeQuestionServiceClient.get_transport_class(transport) if isinstance(transport, str) or transport is None else cast(Callable[..., GenerativeQuestionServiceTransport], transport) ) # initialize with the provided callable or the passed in class self._transport = transport_init( credentials=credentials, credentials_file=self._client_options.credentials_file, host=self._api_endpoint, scopes=self._client_options.scopes, client_cert_source_for_mtls=self._client_cert_source, quota_project_id=self._client_options.quota_project_id, client_info=client_info, always_use_jwt_access=True, api_audience=self._client_options.api_audience, )
[docs] def update_generative_questions_feature_config( self, request: Optional[ Union[ generative_question_service.UpdateGenerativeQuestionsFeatureConfigRequest, dict, ] ] = None, *, generative_questions_feature_config: Optional[ generative_question.GenerativeQuestionsFeatureConfig ] = None, update_mask: Optional[field_mask_pb2.FieldMask] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> generative_question.GenerativeQuestionsFeatureConfig: r"""Manages overal generative question feature state -- enables toggling feature on and off. .. code-block:: python # 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 retail_v2alpha def sample_update_generative_questions_feature_config(): # Create a client client = retail_v2alpha.GenerativeQuestionServiceClient() # Initialize request argument(s) generative_questions_feature_config = retail_v2alpha.GenerativeQuestionsFeatureConfig() generative_questions_feature_config.catalog = "catalog_value" request = retail_v2alpha.UpdateGenerativeQuestionsFeatureConfigRequest( generative_questions_feature_config=generative_questions_feature_config, ) # Make the request response = client.update_generative_questions_feature_config(request=request) # Handle the response print(response) Args: request (Union[google.cloud.retail_v2alpha.types.UpdateGenerativeQuestionsFeatureConfigRequest, dict]): The request object. Request for UpdateGenerativeQuestionsFeatureConfig method. generative_questions_feature_config (google.cloud.retail_v2alpha.types.GenerativeQuestionsFeatureConfig): Required. The configuration managing the feature state. This corresponds to the ``generative_questions_feature_config`` field on the ``request`` instance; if ``request`` is provided, this should not be set. update_mask (google.protobuf.field_mask_pb2.FieldMask): Optional. Indicates which fields in the provided [GenerativeQuestionsFeatureConfig][google.cloud.retail.v2alpha.GenerativeQuestionsFeatureConfig] to update. If not set or empty, all supported fields are updated. This corresponds to the ``update_mask`` 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: google.cloud.retail_v2alpha.types.GenerativeQuestionsFeatureConfig: Configuration for overall generative question feature state. """ # Create or coerce a protobuf request object. # - Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([generative_questions_feature_config, update_mask]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) # - Use the request object if provided (there's no risk of modifying the input as # there are no flattened fields), or create one. if not isinstance( request, generative_question_service.UpdateGenerativeQuestionsFeatureConfigRequest, ): request = generative_question_service.UpdateGenerativeQuestionsFeatureConfigRequest( request ) # If we have keyword arguments corresponding to fields on the # request, apply these. if generative_questions_feature_config is not None: request.generative_questions_feature_config = ( generative_questions_feature_config ) if update_mask is not None: request.update_mask = update_mask # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.update_generative_questions_feature_config ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata( ( ( "generative_questions_feature_config.catalog", request.generative_questions_feature_config.catalog, ), ) ), ) # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
[docs] def get_generative_questions_feature_config( self, request: Optional[ Union[ generative_question_service.GetGenerativeQuestionsFeatureConfigRequest, dict, ] ] = None, *, catalog: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> generative_question.GenerativeQuestionsFeatureConfig: r"""Manages overal generative question feature state -- enables toggling feature on and off. .. code-block:: python # 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 retail_v2alpha def sample_get_generative_questions_feature_config(): # Create a client client = retail_v2alpha.GenerativeQuestionServiceClient() # Initialize request argument(s) request = retail_v2alpha.GetGenerativeQuestionsFeatureConfigRequest( catalog="catalog_value", ) # Make the request response = client.get_generative_questions_feature_config(request=request) # Handle the response print(response) Args: request (Union[google.cloud.retail_v2alpha.types.GetGenerativeQuestionsFeatureConfigRequest, dict]): The request object. Request for GetGenerativeQuestionsFeatureConfig method. catalog (str): Required. Resource name of the parent catalog. Format: projects/{project}/locations/{location}/catalogs/{catalog} This corresponds to the ``catalog`` 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: google.cloud.retail_v2alpha.types.GenerativeQuestionsFeatureConfig: Configuration for overall generative question feature state. """ # Create or coerce a protobuf request object. # - Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([catalog]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) # - Use the request object if provided (there's no risk of modifying the input as # there are no flattened fields), or create one. if not isinstance( request, generative_question_service.GetGenerativeQuestionsFeatureConfigRequest, ): request = ( generative_question_service.GetGenerativeQuestionsFeatureConfigRequest( request ) ) # If we have keyword arguments corresponding to fields on the # request, apply these. if catalog is not None: request.catalog = catalog # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.get_generative_questions_feature_config ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("catalog", request.catalog),)), ) # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
[docs] def list_generative_question_configs( self, request: Optional[ Union[ generative_question_service.ListGenerativeQuestionConfigsRequest, dict ] ] = None, *, parent: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> generative_question_service.ListGenerativeQuestionConfigsResponse: r"""Returns all questions for a given catalog. .. code-block:: python # 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 retail_v2alpha def sample_list_generative_question_configs(): # Create a client client = retail_v2alpha.GenerativeQuestionServiceClient() # Initialize request argument(s) request = retail_v2alpha.ListGenerativeQuestionConfigsRequest( parent="parent_value", ) # Make the request response = client.list_generative_question_configs(request=request) # Handle the response print(response) Args: request (Union[google.cloud.retail_v2alpha.types.ListGenerativeQuestionConfigsRequest, dict]): The request object. Request for ListQuestions method. parent (str): Required. Resource name of the parent catalog. Format: projects/{project}/locations/{location}/catalogs/{catalog} This corresponds to the ``parent`` 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: google.cloud.retail_v2alpha.types.ListGenerativeQuestionConfigsResponse: Response for ListQuestions method. """ # Create or coerce a protobuf request object. # - Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([parent]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) # - Use the request object if provided (there's no risk of modifying the input as # there are no flattened fields), or create one. if not isinstance( request, generative_question_service.ListGenerativeQuestionConfigsRequest ): request = generative_question_service.ListGenerativeQuestionConfigsRequest( request ) # If we have keyword arguments corresponding to fields on the # request, apply these. if parent is not None: request.parent = parent # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.list_generative_question_configs ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)), ) # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
[docs] def update_generative_question_config( self, request: Optional[ Union[ generative_question_service.UpdateGenerativeQuestionConfigRequest, dict ] ] = None, *, generative_question_config: Optional[ generative_question.GenerativeQuestionConfig ] = None, update_mask: Optional[field_mask_pb2.FieldMask] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> generative_question.GenerativeQuestionConfig: r"""Allows management of individual questions. .. code-block:: python # 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 retail_v2alpha def sample_update_generative_question_config(): # Create a client client = retail_v2alpha.GenerativeQuestionServiceClient() # Initialize request argument(s) generative_question_config = retail_v2alpha.GenerativeQuestionConfig() generative_question_config.catalog = "catalog_value" generative_question_config.facet = "facet_value" request = retail_v2alpha.UpdateGenerativeQuestionConfigRequest( generative_question_config=generative_question_config, ) # Make the request response = client.update_generative_question_config(request=request) # Handle the response print(response) Args: request (Union[google.cloud.retail_v2alpha.types.UpdateGenerativeQuestionConfigRequest, dict]): The request object. Request for UpdateGenerativeQuestionConfig method. generative_question_config (google.cloud.retail_v2alpha.types.GenerativeQuestionConfig): Required. The question to update. This corresponds to the ``generative_question_config`` field on the ``request`` instance; if ``request`` is provided, this should not be set. update_mask (google.protobuf.field_mask_pb2.FieldMask): Optional. Indicates which fields in the provided [GenerativeQuestionConfig][google.cloud.retail.v2alpha.GenerativeQuestionConfig] to update. The following are NOT supported: - [GenerativeQuestionConfig.frequency][google.cloud.retail.v2alpha.GenerativeQuestionConfig.frequency] If not set or empty, all supported fields are updated. This corresponds to the ``update_mask`` 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: google.cloud.retail_v2alpha.types.GenerativeQuestionConfig: Configuration for a single generated question. """ # Create or coerce a protobuf request object. # - Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([generative_question_config, update_mask]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) # - Use the request object if provided (there's no risk of modifying the input as # there are no flattened fields), or create one. if not isinstance( request, generative_question_service.UpdateGenerativeQuestionConfigRequest ): request = generative_question_service.UpdateGenerativeQuestionConfigRequest( request ) # If we have keyword arguments corresponding to fields on the # request, apply these. if generative_question_config is not None: request.generative_question_config = generative_question_config if update_mask is not None: request.update_mask = update_mask # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.update_generative_question_config ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata( ( ( "generative_question_config.catalog", request.generative_question_config.catalog, ), ) ), ) # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
[docs] def batch_update_generative_question_configs( self, request: Optional[ Union[ generative_question_service.BatchUpdateGenerativeQuestionConfigsRequest, dict, ] ] = None, *, parent: Optional[str] = None, requests: Optional[ MutableSequence[ generative_question_service.UpdateGenerativeQuestionConfigRequest ] ] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> generative_question_service.BatchUpdateGenerativeQuestionConfigsResponse: r"""Allows management of multiple questions. .. code-block:: python # 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 retail_v2alpha def sample_batch_update_generative_question_configs(): # Create a client client = retail_v2alpha.GenerativeQuestionServiceClient() # Initialize request argument(s) requests = retail_v2alpha.UpdateGenerativeQuestionConfigRequest() requests.generative_question_config.catalog = "catalog_value" requests.generative_question_config.facet = "facet_value" request = retail_v2alpha.BatchUpdateGenerativeQuestionConfigsRequest( requests=requests, ) # Make the request response = client.batch_update_generative_question_configs(request=request) # Handle the response print(response) Args: request (Union[google.cloud.retail_v2alpha.types.BatchUpdateGenerativeQuestionConfigsRequest, dict]): The request object. Request for BatchUpdateGenerativeQuestionConfig method. parent (str): Optional. Resource name of the parent catalog. Format: projects/{project}/locations/{location}/catalogs/{catalog} This corresponds to the ``parent`` field on the ``request`` instance; if ``request`` is provided, this should not be set. requests (MutableSequence[google.cloud.retail_v2alpha.types.UpdateGenerativeQuestionConfigRequest]): Required. The updates question configs. This corresponds to the ``requests`` 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: google.cloud.retail_v2alpha.types.BatchUpdateGenerativeQuestionConfigsResponse: Aggregated response for UpdateGenerativeQuestionConfig method. """ # Create or coerce a protobuf request object. # - Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([parent, requests]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) # - Use the request object if provided (there's no risk of modifying the input as # there are no flattened fields), or create one. if not isinstance( request, generative_question_service.BatchUpdateGenerativeQuestionConfigsRequest, ): request = ( generative_question_service.BatchUpdateGenerativeQuestionConfigsRequest( request ) ) # If we have keyword arguments corresponding to fields on the # request, apply these. if parent is not None: request.parent = parent if requests is not None: request.requests = requests # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.batch_update_generative_question_configs ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)), ) # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
def __enter__(self) -> "GenerativeQuestionServiceClient": return self
[docs] def __exit__(self, type, value, traceback): """Releases underlying transport's resources. .. warning:: ONLY use as a context manager if the transport is NOT shared with other clients! Exiting the with block will CLOSE the transport and may cause errors in other clients! """ self.transport.close()
[docs] def list_operations( self, request: Optional[operations_pb2.ListOperationsRequest] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> operations_pb2.ListOperationsResponse: r"""Lists operations that match the specified filter in the request. Args: request (:class:`~.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: ~.operations_pb2.ListOperationsResponse: Response message for ``ListOperations`` method. """ # Create or coerce a protobuf request object. # The request isn't a proto-plus wrapped type, # so it must be constructed via keyword expansion. if isinstance(request, dict): request = operations_pb2.ListOperationsRequest(**request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.list_operations] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)), ) # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
[docs] def get_operation( self, request: Optional[operations_pb2.GetOperationRequest] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> operations_pb2.Operation: r"""Gets the latest state of a long-running operation. Args: request (:class:`~.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: ~.operations_pb2.Operation: An ``Operation`` object. """ # Create or coerce a protobuf request object. # The request isn't a proto-plus wrapped type, # so it must be constructed via keyword expansion. if isinstance(request, dict): request = operations_pb2.GetOperationRequest(**request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.get_operation] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)), ) # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response
DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( gapic_version=package_version.__version__ ) __all__ = ("GenerativeQuestionServiceClient",)