# -*- 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 logging as std_logging import re from typing import ( Callable, Dict, Mapping, MutableMapping, MutableSequence, Optional, Sequence, Tuple, Type, Union, ) from google.api_core import exceptions as core_exceptions from google.api_core import gapic_v1 from google.api_core import retry_async as retries from google.api_core.client_options import ClientOptions from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore from google.ai.generativelanguage_v1beta import gapic_version as package_version try: OptionalRetry = Union[retries.AsyncRetry, gapic_v1.method._MethodDefault, None] except AttributeError: # pragma: NO COVER OptionalRetry = Union[retries.AsyncRetry, object, None] # type: ignore from google.longrunning import operations_pb2 # type: ignore from google.protobuf import field_mask_pb2 # type: ignore from google.protobuf import timestamp_pb2 # type: ignore from google.ai.generativelanguage_v1beta.services.retriever_service import pagers from google.ai.generativelanguage_v1beta.types import retriever, retriever_service from .client import RetrieverServiceClient from .transports.base import DEFAULT_CLIENT_INFO, RetrieverServiceTransport from .transports.grpc_asyncio import RetrieverServiceGrpcAsyncIOTransport try: from google.api_core import client_logging # type: ignore CLIENT_LOGGING_SUPPORTED = True # pragma: NO COVER except ImportError: # pragma: NO COVER CLIENT_LOGGING_SUPPORTED = False _LOGGER = std_logging.getLogger(__name__) class RetrieverServiceAsyncClient: """An API for semantic search over a corpus of user uploaded content. """ _client: RetrieverServiceClient # Copy defaults from the synchronous client for use here. # Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead. DEFAULT_ENDPOINT = RetrieverServiceClient.DEFAULT_ENDPOINT DEFAULT_MTLS_ENDPOINT = RetrieverServiceClient.DEFAULT_MTLS_ENDPOINT _DEFAULT_ENDPOINT_TEMPLATE = RetrieverServiceClient._DEFAULT_ENDPOINT_TEMPLATE _DEFAULT_UNIVERSE = RetrieverServiceClient._DEFAULT_UNIVERSE chunk_path = staticmethod(RetrieverServiceClient.chunk_path) parse_chunk_path = staticmethod(RetrieverServiceClient.parse_chunk_path) corpus_path = staticmethod(RetrieverServiceClient.corpus_path) parse_corpus_path = staticmethod(RetrieverServiceClient.parse_corpus_path) document_path = staticmethod(RetrieverServiceClient.document_path) parse_document_path = staticmethod(RetrieverServiceClient.parse_document_path) common_billing_account_path = staticmethod( RetrieverServiceClient.common_billing_account_path ) parse_common_billing_account_path = staticmethod( RetrieverServiceClient.parse_common_billing_account_path ) common_folder_path = staticmethod(RetrieverServiceClient.common_folder_path) parse_common_folder_path = staticmethod( RetrieverServiceClient.parse_common_folder_path ) common_organization_path = staticmethod( RetrieverServiceClient.common_organization_path ) parse_common_organization_path = staticmethod( RetrieverServiceClient.parse_common_organization_path ) common_project_path = staticmethod(RetrieverServiceClient.common_project_path) parse_common_project_path = staticmethod( RetrieverServiceClient.parse_common_project_path ) common_location_path = staticmethod(RetrieverServiceClient.common_location_path) parse_common_location_path = staticmethod( RetrieverServiceClient.parse_common_location_path ) @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: RetrieverServiceAsyncClient: The constructed client. """ return RetrieverServiceClient.from_service_account_info.__func__(RetrieverServiceAsyncClient, info, *args, **kwargs) # type: ignore @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: RetrieverServiceAsyncClient: The constructed client. """ return RetrieverServiceClient.from_service_account_file.__func__(RetrieverServiceAsyncClient, filename, *args, **kwargs) # type: ignore from_service_account_json = from_service_account_file @classmethod def get_mtls_endpoint_and_cert_source( cls, client_options: Optional[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. 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. """ return RetrieverServiceClient.get_mtls_endpoint_and_cert_source(client_options) # type: ignore @property def transport(self) -> RetrieverServiceTransport: """Returns the transport used by the client instance. Returns: RetrieverServiceTransport: The transport used by the client instance. """ return self._client.transport @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._client._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._client._universe_domain get_transport_class = RetrieverServiceClient.get_transport_class def __init__( self, *, credentials: Optional[ga_credentials.Credentials] = None, transport: Optional[ Union[ str, RetrieverServiceTransport, Callable[..., RetrieverServiceTransport] ] ] = "grpc_asyncio", client_options: Optional[ClientOptions] = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, ) -> None: """Instantiates the retriever service async 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,RetrieverServiceTransport,Callable[..., RetrieverServiceTransport]]]): 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 RetrieverServiceTransport 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 ``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 = RetrieverServiceClient( credentials=credentials, transport=transport, client_options=client_options, client_info=client_info, ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( std_logging.DEBUG ): # pragma: NO COVER _LOGGER.debug( "Created client `google.ai.generativelanguage_v1beta.RetrieverServiceAsyncClient`.", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "universeDomain": getattr( self._client._transport._credentials, "universe_domain", "" ), "credentialsType": f"{type(self._client._transport._credentials).__module__}.{type(self._client._transport._credentials).__qualname__}", "credentialsInfo": getattr( self.transport._credentials, "get_cred_info", lambda: None )(), } if hasattr(self._client._transport, "_credentials") else { "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "credentialsType": None, }, ) async def create_corpus( self, request: Optional[Union[retriever_service.CreateCorpusRequest, dict]] = None, *, corpus: Optional[retriever.Corpus] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Corpus: r"""Creates an empty ``Corpus``. .. 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.ai import generativelanguage_v1beta async def sample_create_corpus(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.CreateCorpusRequest( ) # Make the request response = await client.create_corpus(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.CreateCorpusRequest, dict]]): The request object. Request to create a ``Corpus``. corpus (:class:`google.ai.generativelanguage_v1beta.types.Corpus`): Required. The ``Corpus`` to create. This corresponds to the ``corpus`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Corpus: A Corpus is a collection of Documents. A project can create up to 5 corpora. """ # 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([corpus]) 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, retriever_service.CreateCorpusRequest): request = retriever_service.CreateCorpusRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if corpus is not None: request.corpus = corpus # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.create_corpus ] # Validate the universe domain. self._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def get_corpus( self, request: Optional[Union[retriever_service.GetCorpusRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Corpus: r"""Gets information about a specific ``Corpus``. .. 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.ai import generativelanguage_v1beta async def sample_get_corpus(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.GetCorpusRequest( name="name_value", ) # Make the request response = await client.get_corpus(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.GetCorpusRequest, dict]]): The request object. Request for getting information about a specific ``Corpus``. name (:class:`str`): Required. The name of the ``Corpus``. Example: ``corpora/my-corpus-123`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Corpus: A Corpus is a collection of Documents. A project can create up to 5 corpora. """ # 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([name]) 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, retriever_service.GetCorpusRequest): request = retriever_service.GetCorpusRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.get_corpus ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def update_corpus( self, request: Optional[Union[retriever_service.UpdateCorpusRequest, dict]] = None, *, corpus: Optional[retriever.Corpus] = 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, Union[str, bytes]]] = (), ) -> retriever.Corpus: r"""Updates a ``Corpus``. .. 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.ai import generativelanguage_v1beta async def sample_update_corpus(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.UpdateCorpusRequest( ) # Make the request response = await client.update_corpus(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.UpdateCorpusRequest, dict]]): The request object. Request to update a ``Corpus``. corpus (:class:`google.ai.generativelanguage_v1beta.types.Corpus`): Required. The ``Corpus`` to update. This corresponds to the ``corpus`` field on the ``request`` instance; if ``request`` is provided, this should not be set. update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`): Required. The list of fields to update. Currently, this only supports updating ``display_name``. 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_async.AsyncRetry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Corpus: A Corpus is a collection of Documents. A project can create up to 5 corpora. """ # 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([corpus, 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, retriever_service.UpdateCorpusRequest): request = retriever_service.UpdateCorpusRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if corpus is not None: request.corpus = corpus 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._client._transport._wrapped_methods[ self._client._transport.update_corpus ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata( (("corpus.name", request.corpus.name),) ), ) # Validate the universe domain. self._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def delete_corpus( self, request: Optional[Union[retriever_service.DeleteCorpusRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> None: r"""Deletes a ``Corpus``. .. 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.ai import generativelanguage_v1beta async def sample_delete_corpus(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.DeleteCorpusRequest( name="name_value", ) # Make the request await client.delete_corpus(request=request) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.DeleteCorpusRequest, dict]]): The request object. Request to delete a ``Corpus``. name (:class:`str`): Required. The resource name of the ``Corpus``. Example: ``corpora/my-corpus-123`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. """ # 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([name]) 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, retriever_service.DeleteCorpusRequest): request = retriever_service.DeleteCorpusRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.delete_corpus ] # 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._client._validate_universe_domain() # Send the request. await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) async def list_corpora( self, request: Optional[Union[retriever_service.ListCorporaRequest, dict]] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> pagers.ListCorporaAsyncPager: r"""Lists all ``Corpora`` owned by the user. .. 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.ai import generativelanguage_v1beta async def sample_list_corpora(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.ListCorporaRequest( ) # Make the request page_result = client.list_corpora(request=request) # Handle the response async for response in page_result: print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.ListCorporaRequest, dict]]): The request object. Request for listing ``Corpora``. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.services.retriever_service.pagers.ListCorporaAsyncPager: Response from ListCorpora containing a paginated list of Corpora. The results are sorted by ascending corpus.create_time. Iterating over this object will yield results and resolve additional pages automatically. """ # Create or coerce a protobuf request object. # - 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, retriever_service.ListCorporaRequest): request = retriever_service.ListCorporaRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.list_corpora ] # Validate the universe domain. self._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # This method is paged; wrap the response in a pager, which provides # an `__aiter__` convenience method. response = pagers.ListCorporaAsyncPager( method=rpc, request=request, response=response, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def query_corpus( self, request: Optional[Union[retriever_service.QueryCorpusRequest, dict]] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.QueryCorpusResponse: r"""Performs semantic search over a ``Corpus``. .. 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.ai import generativelanguage_v1beta async def sample_query_corpus(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.QueryCorpusRequest( name="name_value", query="query_value", ) # Make the request response = await client.query_corpus(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.QueryCorpusRequest, dict]]): The request object. Request for querying a ``Corpus``. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.QueryCorpusResponse: Response from QueryCorpus containing a list of relevant chunks. """ # Create or coerce a protobuf request object. # - 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, retriever_service.QueryCorpusRequest): request = retriever_service.QueryCorpusRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.query_corpus ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def create_document( self, request: Optional[Union[retriever_service.CreateDocumentRequest, dict]] = None, *, parent: Optional[str] = None, document: Optional[retriever.Document] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Document: r"""Creates an empty ``Document``. .. 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.ai import generativelanguage_v1beta async def sample_create_document(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.CreateDocumentRequest( parent="parent_value", ) # Make the request response = await client.create_document(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.CreateDocumentRequest, dict]]): The request object. Request to create a ``Document``. parent (:class:`str`): Required. The name of the ``Corpus`` where this ``Document`` will be created. Example: ``corpora/my-corpus-123`` This corresponds to the ``parent`` field on the ``request`` instance; if ``request`` is provided, this should not be set. document (:class:`google.ai.generativelanguage_v1beta.types.Document`): Required. The ``Document`` to create. This corresponds to the ``document`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Document: A Document is a collection of Chunks. A Corpus can have a maximum of 10,000 Documents. """ # 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, document]) 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, retriever_service.CreateDocumentRequest): request = retriever_service.CreateDocumentRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if parent is not None: request.parent = parent if document is not None: request.document = document # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.create_document ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def get_document( self, request: Optional[Union[retriever_service.GetDocumentRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Document: r"""Gets information about a specific ``Document``. .. 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.ai import generativelanguage_v1beta async def sample_get_document(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.GetDocumentRequest( name="name_value", ) # Make the request response = await client.get_document(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.GetDocumentRequest, dict]]): The request object. Request for getting information about a specific ``Document``. name (:class:`str`): Required. The name of the ``Document`` to retrieve. Example: ``corpora/my-corpus-123/documents/the-doc-abc`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Document: A Document is a collection of Chunks. A Corpus can have a maximum of 10,000 Documents. """ # 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([name]) 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, retriever_service.GetDocumentRequest): request = retriever_service.GetDocumentRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.get_document ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def update_document( self, request: Optional[Union[retriever_service.UpdateDocumentRequest, dict]] = None, *, document: Optional[retriever.Document] = 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, Union[str, bytes]]] = (), ) -> retriever.Document: r"""Updates a ``Document``. .. 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.ai import generativelanguage_v1beta async def sample_update_document(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.UpdateDocumentRequest( ) # Make the request response = await client.update_document(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.UpdateDocumentRequest, dict]]): The request object. Request to update a ``Document``. document (:class:`google.ai.generativelanguage_v1beta.types.Document`): Required. The ``Document`` to update. This corresponds to the ``document`` field on the ``request`` instance; if ``request`` is provided, this should not be set. update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`): Required. The list of fields to update. Currently, this only supports updating ``display_name`` and ``custom_metadata``. 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_async.AsyncRetry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Document: A Document is a collection of Chunks. A Corpus can have a maximum of 10,000 Documents. """ # 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([document, 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, retriever_service.UpdateDocumentRequest): request = retriever_service.UpdateDocumentRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if document is not None: request.document = document 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._client._transport._wrapped_methods[ self._client._transport.update_document ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata( (("document.name", request.document.name),) ), ) # Validate the universe domain. self._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def delete_document( self, request: Optional[Union[retriever_service.DeleteDocumentRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> None: r"""Deletes a ``Document``. .. 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.ai import generativelanguage_v1beta async def sample_delete_document(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.DeleteDocumentRequest( name="name_value", ) # Make the request await client.delete_document(request=request) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.DeleteDocumentRequest, dict]]): The request object. Request to delete a ``Document``. name (:class:`str`): Required. The resource name of the ``Document`` to delete. Example: ``corpora/my-corpus-123/documents/the-doc-abc`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. """ # 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([name]) 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, retriever_service.DeleteDocumentRequest): request = retriever_service.DeleteDocumentRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.delete_document ] # 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._client._validate_universe_domain() # Send the request. await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) async def list_documents( self, request: Optional[Union[retriever_service.ListDocumentsRequest, dict]] = None, *, parent: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> pagers.ListDocumentsAsyncPager: r"""Lists all ``Document``\ s in a ``Corpus``. .. 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.ai import generativelanguage_v1beta async def sample_list_documents(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.ListDocumentsRequest( parent="parent_value", ) # Make the request page_result = client.list_documents(request=request) # Handle the response async for response in page_result: print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.ListDocumentsRequest, dict]]): The request object. Request for listing ``Document``\ s. parent (:class:`str`): Required. The name of the ``Corpus`` containing ``Document``\ s. Example: ``corpora/my-corpus-123`` This corresponds to the ``parent`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.services.retriever_service.pagers.ListDocumentsAsyncPager: Response from ListDocuments containing a paginated list of Documents. The Documents are sorted by ascending document.create_time. Iterating over this object will yield results and resolve additional pages automatically. """ # 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, retriever_service.ListDocumentsRequest): request = retriever_service.ListDocumentsRequest(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._client._transport._wrapped_methods[ self._client._transport.list_documents ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # This method is paged; wrap the response in a pager, which provides # an `__aiter__` convenience method. response = pagers.ListDocumentsAsyncPager( method=rpc, request=request, response=response, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def query_document( self, request: Optional[Union[retriever_service.QueryDocumentRequest, dict]] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.QueryDocumentResponse: r"""Performs semantic search over a ``Document``. .. 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.ai import generativelanguage_v1beta async def sample_query_document(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.QueryDocumentRequest( name="name_value", query="query_value", ) # Make the request response = await client.query_document(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.QueryDocumentRequest, dict]]): The request object. Request for querying a ``Document``. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.QueryDocumentResponse: Response from QueryDocument containing a list of relevant chunks. """ # Create or coerce a protobuf request object. # - 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, retriever_service.QueryDocumentRequest): request = retriever_service.QueryDocumentRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.query_document ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def create_chunk( self, request: Optional[Union[retriever_service.CreateChunkRequest, dict]] = None, *, parent: Optional[str] = None, chunk: Optional[retriever.Chunk] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Chunk: r"""Creates a ``Chunk``. .. 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.ai import generativelanguage_v1beta async def sample_create_chunk(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) chunk = generativelanguage_v1beta.Chunk() chunk.data.string_value = "string_value_value" request = generativelanguage_v1beta.CreateChunkRequest( parent="parent_value", chunk=chunk, ) # Make the request response = await client.create_chunk(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.CreateChunkRequest, dict]]): The request object. Request to create a ``Chunk``. parent (:class:`str`): Required. The name of the ``Document`` where this ``Chunk`` will be created. Example: ``corpora/my-corpus-123/documents/the-doc-abc`` This corresponds to the ``parent`` field on the ``request`` instance; if ``request`` is provided, this should not be set. chunk (:class:`google.ai.generativelanguage_v1beta.types.Chunk`): Required. The ``Chunk`` to create. This corresponds to the ``chunk`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Chunk: A Chunk is a subpart of a Document that is treated as an independent unit for the purposes of vector representation and storage. A Corpus can have a maximum of 1 million Chunks. """ # 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, chunk]) 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, retriever_service.CreateChunkRequest): request = retriever_service.CreateChunkRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if parent is not None: request.parent = parent if chunk is not None: request.chunk = chunk # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.create_chunk ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def batch_create_chunks( self, request: Optional[ Union[retriever_service.BatchCreateChunksRequest, dict] ] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.BatchCreateChunksResponse: r"""Batch create ``Chunk``\ s. .. 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.ai import generativelanguage_v1beta async def sample_batch_create_chunks(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) requests = generativelanguage_v1beta.CreateChunkRequest() requests.parent = "parent_value" requests.chunk.data.string_value = "string_value_value" request = generativelanguage_v1beta.BatchCreateChunksRequest( requests=requests, ) # Make the request response = await client.batch_create_chunks(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.BatchCreateChunksRequest, dict]]): The request object. Request to batch create ``Chunk``\ s. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.BatchCreateChunksResponse: Response from BatchCreateChunks containing a list of created Chunks. """ # Create or coerce a protobuf request object. # - 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, retriever_service.BatchCreateChunksRequest): request = retriever_service.BatchCreateChunksRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.batch_create_chunks ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def get_chunk( self, request: Optional[Union[retriever_service.GetChunkRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Chunk: r"""Gets information about a specific ``Chunk``. .. 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.ai import generativelanguage_v1beta async def sample_get_chunk(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.GetChunkRequest( name="name_value", ) # Make the request response = await client.get_chunk(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.GetChunkRequest, dict]]): The request object. Request for getting information about a specific ``Chunk``. name (:class:`str`): Required. The name of the ``Chunk`` to retrieve. Example: ``corpora/my-corpus-123/documents/the-doc-abc/chunks/some-chunk`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Chunk: A Chunk is a subpart of a Document that is treated as an independent unit for the purposes of vector representation and storage. A Corpus can have a maximum of 1 million Chunks. """ # 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([name]) 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, retriever_service.GetChunkRequest): request = retriever_service.GetChunkRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.get_chunk ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def update_chunk( self, request: Optional[Union[retriever_service.UpdateChunkRequest, dict]] = None, *, chunk: Optional[retriever.Chunk] = 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, Union[str, bytes]]] = (), ) -> retriever.Chunk: r"""Updates a ``Chunk``. .. 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.ai import generativelanguage_v1beta async def sample_update_chunk(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) chunk = generativelanguage_v1beta.Chunk() chunk.data.string_value = "string_value_value" request = generativelanguage_v1beta.UpdateChunkRequest( chunk=chunk, ) # Make the request response = await client.update_chunk(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.UpdateChunkRequest, dict]]): The request object. Request to update a ``Chunk``. chunk (:class:`google.ai.generativelanguage_v1beta.types.Chunk`): Required. The ``Chunk`` to update. This corresponds to the ``chunk`` field on the ``request`` instance; if ``request`` is provided, this should not be set. update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`): Required. The list of fields to update. Currently, this only supports updating ``custom_metadata`` and ``data``. 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_async.AsyncRetry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.Chunk: A Chunk is a subpart of a Document that is treated as an independent unit for the purposes of vector representation and storage. A Corpus can have a maximum of 1 million Chunks. """ # 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([chunk, 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, retriever_service.UpdateChunkRequest): request = retriever_service.UpdateChunkRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if chunk is not None: request.chunk = chunk 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._client._transport._wrapped_methods[ self._client._transport.update_chunk ] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata( (("chunk.name", request.chunk.name),) ), ) # Validate the universe domain. self._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def batch_update_chunks( self, request: Optional[ Union[retriever_service.BatchUpdateChunksRequest, dict] ] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.BatchUpdateChunksResponse: r"""Batch update ``Chunk``\ s. .. 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.ai import generativelanguage_v1beta async def sample_batch_update_chunks(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) requests = generativelanguage_v1beta.UpdateChunkRequest() requests.chunk.data.string_value = "string_value_value" request = generativelanguage_v1beta.BatchUpdateChunksRequest( requests=requests, ) # Make the request response = await client.batch_update_chunks(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.BatchUpdateChunksRequest, dict]]): The request object. Request to batch update ``Chunk``\ s. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.types.BatchUpdateChunksResponse: Response from BatchUpdateChunks containing a list of updated Chunks. """ # Create or coerce a protobuf request object. # - 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, retriever_service.BatchUpdateChunksRequest): request = retriever_service.BatchUpdateChunksRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.batch_update_chunks ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def delete_chunk( self, request: Optional[Union[retriever_service.DeleteChunkRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> None: r"""Deletes a ``Chunk``. .. 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.ai import generativelanguage_v1beta async def sample_delete_chunk(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.DeleteChunkRequest( name="name_value", ) # Make the request await client.delete_chunk(request=request) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.DeleteChunkRequest, dict]]): The request object. Request to delete a ``Chunk``. name (:class:`str`): Required. The resource name of the ``Chunk`` to delete. Example: ``corpora/my-corpus-123/documents/the-doc-abc/chunks/some-chunk`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. """ # 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([name]) 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, retriever_service.DeleteChunkRequest): request = retriever_service.DeleteChunkRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.delete_chunk ] # 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._client._validate_universe_domain() # Send the request. await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) async def batch_delete_chunks( self, request: Optional[ Union[retriever_service.BatchDeleteChunksRequest, dict] ] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> None: r"""Batch delete ``Chunk``\ s. .. 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.ai import generativelanguage_v1beta async def sample_batch_delete_chunks(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) requests = generativelanguage_v1beta.DeleteChunkRequest() requests.name = "name_value" request = generativelanguage_v1beta.BatchDeleteChunksRequest( requests=requests, ) # Make the request await client.batch_delete_chunks(request=request) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.BatchDeleteChunksRequest, dict]]): The request object. Request to batch delete ``Chunk``\ s. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. """ # Create or coerce a protobuf request object. # - 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, retriever_service.BatchDeleteChunksRequest): request = retriever_service.BatchDeleteChunksRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._client._transport._wrapped_methods[ self._client._transport.batch_delete_chunks ] # 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._client._validate_universe_domain() # Send the request. await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) async def list_chunks( self, request: Optional[Union[retriever_service.ListChunksRequest, dict]] = None, *, parent: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> pagers.ListChunksAsyncPager: r"""Lists all ``Chunk``\ s in a ``Document``. .. 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.ai import generativelanguage_v1beta async def sample_list_chunks(): # Create a client client = generativelanguage_v1beta.RetrieverServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta.ListChunksRequest( parent="parent_value", ) # Make the request page_result = client.list_chunks(request=request) # Handle the response async for response in page_result: print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta.types.ListChunksRequest, dict]]): The request object. Request for listing ``Chunk``\ s. parent (:class:`str`): Required. The name of the ``Document`` containing ``Chunk``\ s. Example: ``corpora/my-corpus-123/documents/the-doc-abc`` This corresponds to the ``parent`` field on the ``request`` instance; if ``request`` is provided, this should not be set. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.ai.generativelanguage_v1beta.services.retriever_service.pagers.ListChunksAsyncPager: Response from ListChunks containing a paginated list of Chunks. The Chunks are sorted by ascending chunk.create_time. Iterating over this object will yield results and resolve additional pages automatically. """ # 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, retriever_service.ListChunksRequest): request = retriever_service.ListChunksRequest(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._client._transport._wrapped_methods[ self._client._transport.list_chunks ] # 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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # This method is paged; wrap the response in a pager, which provides # an `__aiter__` convenience method. response = pagers.ListChunksAsyncPager( method=rpc, request=request, response=response, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async 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, Union[str, bytes]]] = (), ) -> 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_async.AsyncRetry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. 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._client._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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async 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, Union[str, bytes]]] = (), ) -> 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_async.AsyncRetry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. 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._client._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._client._validate_universe_domain() # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def __aenter__(self) -> "RetrieverServiceAsyncClient": return self async def __aexit__(self, exc_type, exc, tb): await self.transport.close() DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( gapic_version=package_version.__version__ ) __all__ = ("RetrieverServiceAsyncClient",)