# -*- 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 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.ai.generativelanguage_v1alpha 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 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__) 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_v1alpha.services.retriever_service import pagers from google.ai.generativelanguage_v1alpha.types import retriever, retriever_service from .transports.base import DEFAULT_CLIENT_INFO, RetrieverServiceTransport from .transports.grpc import RetrieverServiceGrpcTransport from .transports.grpc_asyncio import RetrieverServiceGrpcAsyncIOTransport from .transports.rest import RetrieverServiceRestTransport class RetrieverServiceClientMeta(type): """Metaclass for the RetrieverService 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[RetrieverServiceTransport]] _transport_registry["grpc"] = RetrieverServiceGrpcTransport _transport_registry["grpc_asyncio"] = RetrieverServiceGrpcAsyncIOTransport _transport_registry["rest"] = RetrieverServiceRestTransport def get_transport_class( cls, label: Optional[str] = None, ) -> Type[RetrieverServiceTransport]: """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())) class RetrieverServiceClient(metaclass=RetrieverServiceClientMeta): """An API for semantic search over a corpus of user uploaded content. """ @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[^.]+)(?P\.mtls)?(?P\.sandbox)?(?P\.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 = "generativelanguage.googleapis.com" DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore DEFAULT_ENDPOINT ) _DEFAULT_ENDPOINT_TEMPLATE = "generativelanguage.{UNIVERSE_DOMAIN}" _DEFAULT_UNIVERSE = "googleapis.com" @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: RetrieverServiceClient: The constructed client. """ credentials = service_account.Credentials.from_service_account_info(info) kwargs["credentials"] = credentials return cls(*args, **kwargs) @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: RetrieverServiceClient: 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) -> RetrieverServiceTransport: """Returns the transport used by the client instance. Returns: RetrieverServiceTransport: The transport used by the client instance. """ return self._transport @staticmethod def chunk_path( corpus: str, document: str, chunk: str, ) -> str: """Returns a fully-qualified chunk string.""" return "corpora/{corpus}/documents/{document}/chunks/{chunk}".format( corpus=corpus, document=document, chunk=chunk, ) @staticmethod def parse_chunk_path(path: str) -> Dict[str, str]: """Parses a chunk path into its component segments.""" m = re.match( r"^corpora/(?P.+?)/documents/(?P.+?)/chunks/(?P.+?)$", path, ) return m.groupdict() if m else {} @staticmethod def corpus_path( corpus: str, ) -> str: """Returns a fully-qualified corpus string.""" return "corpora/{corpus}".format( corpus=corpus, ) @staticmethod def parse_corpus_path(path: str) -> Dict[str, str]: """Parses a corpus path into its component segments.""" m = re.match(r"^corpora/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def document_path( corpus: str, document: str, ) -> str: """Returns a fully-qualified document string.""" return "corpora/{corpus}/documents/{document}".format( corpus=corpus, document=document, ) @staticmethod def parse_document_path(path: str) -> Dict[str, str]: """Parses a document path into its component segments.""" m = re.match(r"^corpora/(?P.+?)/documents/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_billing_account_path( billing_account: str, ) -> str: """Returns a fully-qualified billing_account string.""" return "billingAccounts/{billing_account}".format( billing_account=billing_account, ) @staticmethod def parse_common_billing_account_path(path: str) -> Dict[str, str]: """Parse a billing_account path into its component segments.""" m = re.match(r"^billingAccounts/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_folder_path( folder: str, ) -> str: """Returns a fully-qualified folder string.""" return "folders/{folder}".format( folder=folder, ) @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.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_organization_path( organization: str, ) -> str: """Returns a fully-qualified organization string.""" return "organizations/{organization}".format( organization=organization, ) @staticmethod def parse_common_organization_path(path: str) -> Dict[str, str]: """Parse a organization path into its component segments.""" m = re.match(r"^organizations/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_project_path( project: str, ) -> str: """Returns a fully-qualified project string.""" return "projects/{project}".format( project=project, ) @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.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_location_path( project: str, location: str, ) -> str: """Returns a fully-qualified location string.""" return "projects/{project}/locations/{location}".format( project=project, location=location, ) @staticmethod def parse_common_location_path(path: str) -> Dict[str, str]: """Parse a location path into its component segments.""" m = re.match(r"^projects/(?P.+?)/locations/(?P.+?)$", path) return m.groupdict() if m else {} @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 = RetrieverServiceClient._DEFAULT_UNIVERSE if universe_domain != _default_universe: raise MutualTLSChannelError( f"mTLS is not supported in any universe other than {_default_universe}." ) api_endpoint = RetrieverServiceClient.DEFAULT_MTLS_ENDPOINT else: api_endpoint = RetrieverServiceClient._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 = RetrieverServiceClient._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, RetrieverServiceTransport, Callable[..., RetrieverServiceTransport] ] ] = None, client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, ) -> None: """Instantiates the retriever 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,RetrieverServiceTransport,Callable[..., RetrieverServiceTransport]]]): 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 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 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, ) = RetrieverServiceClient._read_environment_variables() self._client_cert_source = RetrieverServiceClient._get_client_cert_source( self._client_options.client_cert_source, self._use_client_cert ) self._universe_domain = RetrieverServiceClient._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 if CLIENT_LOGGING_SUPPORTED: # pragma: NO COVER # Setup logging. client_logging.initialize_logging() 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, RetrieverServiceTransport) if transport_provided: # transport is a RetrieverServiceTransport 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(RetrieverServiceTransport, transport) self._api_endpoint = self._transport.host self._api_endpoint = ( self._api_endpoint or RetrieverServiceClient._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[RetrieverServiceTransport], Callable[..., RetrieverServiceTransport], ] = ( RetrieverServiceClient.get_transport_class(transport) if isinstance(transport, str) or transport is None else cast(Callable[..., RetrieverServiceTransport], 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, ) if "async" not in str(self._transport): if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( std_logging.DEBUG ): # pragma: NO COVER _LOGGER.debug( "Created client `google.ai.generativelanguage_v1alpha.RetrieverServiceClient`.", extra={ "serviceName": "google.ai.generativelanguage.v1alpha.RetrieverService", "universeDomain": getattr( self._transport._credentials, "universe_domain", "" ), "credentialsType": f"{type(self._transport._credentials).__module__}.{type(self._transport._credentials).__qualname__}", "credentialsInfo": getattr( self.transport._credentials, "get_cred_info", lambda: None )(), } if hasattr(self._transport, "_credentials") else { "serviceName": "google.ai.generativelanguage.v1alpha.RetrieverService", "credentialsType": None, }, ) 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_v1alpha def sample_create_corpus(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.CreateCorpusRequest( ) # Make the request response = client.create_corpus(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.CreateCorpusRequest, dict]): The request object. Request to create a ``Corpus``. corpus (google.ai.generativelanguage_v1alpha.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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._transport.create_corpus] # 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 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_v1alpha def sample_get_corpus(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.GetCorpusRequest( name="name_value", ) # Make the request response = client.get_corpus(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.GetCorpusRequest, dict]): The request object. Request for getting information about a specific ``Corpus``. name (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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_update_corpus(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.UpdateCorpusRequest( ) # Make the request response = client.update_corpus(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.UpdateCorpusRequest, dict]): The request object. Request to update a ``Corpus``. corpus (google.ai.generativelanguage_v1alpha.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 (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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_delete_corpus(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.DeleteCorpusRequest( name="name_value", ) # Make the request client.delete_corpus(request=request) Args: request (Union[google.ai.generativelanguage_v1alpha.types.DeleteCorpusRequest, dict]): The request object. Request to delete a ``Corpus``. name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) 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.ListCorporaPager: 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_v1alpha def sample_list_corpora(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.ListCorporaRequest( ) # Make the request page_result = client.list_corpora(request=request) # Handle the response for response in page_result: print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.ListCorporaRequest, dict]): The request object. Request for listing ``Corpora``. 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, 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_v1alpha.services.retriever_service.pagers.ListCorporaPager: 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._transport._wrapped_methods[self._transport.list_corpora] # Validate the universe domain. self._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # This method is paged; wrap the response in a pager, which provides # an `__iter__` convenience method. response = pagers.ListCorporaPager( method=rpc, request=request, response=response, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_query_corpus(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.QueryCorpusRequest( name="name_value", query="query_value", ) # Make the request response = client.query_corpus(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.QueryCorpusRequest, dict]): The request object. Request for querying a ``Corpus``. 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, 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_create_document(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.CreateDocumentRequest( parent="parent_value", ) # Make the request response = client.create_document(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.CreateDocumentRequest, dict]): The request object. Request to create a ``Document``. parent (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 (google.ai.generativelanguage_v1alpha.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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_get_document(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.GetDocumentRequest( name="name_value", ) # Make the request response = client.get_document(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.GetDocumentRequest, dict]): The request object. Request for getting information about a specific ``Document``. name (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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_update_document(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.UpdateDocumentRequest( ) # Make the request response = client.update_document(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.UpdateDocumentRequest, dict]): The request object. Request to update a ``Document``. document (google.ai.generativelanguage_v1alpha.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 (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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_delete_document(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.DeleteDocumentRequest( name="name_value", ) # Make the request client.delete_document(request=request) Args: request (Union[google.ai.generativelanguage_v1alpha.types.DeleteDocumentRequest, dict]): The request object. Request to delete a ``Document``. name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) 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.ListDocumentsPager: 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_v1alpha def sample_list_documents(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.ListDocumentsRequest( parent="parent_value", ) # Make the request page_result = client.list_documents(request=request) # Handle the response for response in page_result: print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.ListDocumentsRequest, dict]): The request object. Request for listing ``Document``\ s. parent (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.Retry): 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_v1alpha.services.retriever_service.pagers.ListDocumentsPager: 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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # This method is paged; wrap the response in a pager, which provides # an `__iter__` convenience method. response = pagers.ListDocumentsPager( method=rpc, request=request, response=response, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_query_document(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.QueryDocumentRequest( name="name_value", query="query_value", ) # Make the request response = client.query_document(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.QueryDocumentRequest, dict]): The request object. Request for querying a ``Document``. 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, 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_create_chunk(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) chunk = generativelanguage_v1alpha.Chunk() chunk.data.string_value = "string_value_value" request = generativelanguage_v1alpha.CreateChunkRequest( parent="parent_value", chunk=chunk, ) # Make the request response = client.create_chunk(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.CreateChunkRequest, dict]): The request object. Request to create a ``Chunk``. parent (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 (google.ai.generativelanguage_v1alpha.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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_batch_create_chunks(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) requests = generativelanguage_v1alpha.CreateChunkRequest() requests.parent = "parent_value" requests.chunk.data.string_value = "string_value_value" request = generativelanguage_v1alpha.BatchCreateChunksRequest( requests=requests, ) # Make the request response = client.batch_create_chunks(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.BatchCreateChunksRequest, dict]): The request object. Request to batch create ``Chunk``\ s. 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, 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_get_chunk(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.GetChunkRequest( name="name_value", ) # Make the request response = client.get_chunk(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.GetChunkRequest, dict]): The request object. Request for getting information about a specific ``Chunk``. name (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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_update_chunk(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) chunk = generativelanguage_v1alpha.Chunk() chunk.data.string_value = "string_value_value" request = generativelanguage_v1alpha.UpdateChunkRequest( chunk=chunk, ) # Make the request response = client.update_chunk(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.UpdateChunkRequest, dict]): The request object. Request to update a ``Chunk``. chunk (google.ai.generativelanguage_v1alpha.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 (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.Retry): 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_batch_update_chunks(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) requests = generativelanguage_v1alpha.UpdateChunkRequest() requests.chunk.data.string_value = "string_value_value" request = generativelanguage_v1alpha.BatchUpdateChunksRequest( requests=requests, ) # Make the request response = client.batch_update_chunks(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.BatchUpdateChunksRequest, dict]): The request object. Request to batch update ``Chunk``\ s. 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, 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_v1alpha.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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response 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_v1alpha def sample_delete_chunk(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.DeleteChunkRequest( name="name_value", ) # Make the request client.delete_chunk(request=request) Args: request (Union[google.ai.generativelanguage_v1alpha.types.DeleteChunkRequest, dict]): The request object. Request to delete a ``Chunk``. name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) 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_v1alpha def sample_batch_delete_chunks(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) requests = generativelanguage_v1alpha.DeleteChunkRequest() requests.name = "name_value" request = generativelanguage_v1alpha.BatchDeleteChunksRequest( requests=requests, ) # Make the request client.batch_delete_chunks(request=request) Args: request (Union[google.ai.generativelanguage_v1alpha.types.BatchDeleteChunksRequest, dict]): The request object. Request to batch delete ``Chunk``\ s. 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, 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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) 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.ListChunksPager: 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_v1alpha def sample_list_chunks(): # Create a client client = generativelanguage_v1alpha.RetrieverServiceClient() # Initialize request argument(s) request = generativelanguage_v1alpha.ListChunksRequest( parent="parent_value", ) # Make the request page_result = client.list_chunks(request=request) # Handle the response for response in page_result: print(response) Args: request (Union[google.ai.generativelanguage_v1alpha.types.ListChunksRequest, dict]): The request object. Request for listing ``Chunk``\ s. parent (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.Retry): 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_v1alpha.services.retriever_service.pagers.ListChunksPager: 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._transport._wrapped_methods[self._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._validate_universe_domain() # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # This method is paged; wrap the response in a pager, which provides # an `__iter__` convenience method. response = pagers.ListChunksPager( method=rpc, request=request, response=response, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response def __enter__(self) -> "RetrieverServiceClient": return self 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() 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.Retry): 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._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 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.Retry): 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._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__ = ("RetrieverServiceClient",)