# -*- 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. # import dataclasses import json # type: ignore import logging from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union import warnings from google.api_core import exceptions as core_exceptions from google.api_core import gapic_v1, rest_helpers, rest_streaming from google.api_core import retry as retries from google.auth import credentials as ga_credentials # type: ignore from google.auth.transport.requests import AuthorizedSession # type: ignore from google.longrunning import operations_pb2 # type: ignore from google.protobuf import empty_pb2 # type: ignore from google.protobuf import json_format from requests import __version__ as requests_version from google.ai.generativelanguage_v1beta.types import retriever, retriever_service from .base import DEFAULT_CLIENT_INFO as BASE_DEFAULT_CLIENT_INFO from .rest_base import _BaseRetrieverServiceRestTransport 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 = logging.getLogger(__name__) DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( gapic_version=BASE_DEFAULT_CLIENT_INFO.gapic_version, grpc_version=None, rest_version=f"requests@{requests_version}", ) class RetrieverServiceRestInterceptor: """Interceptor for RetrieverService. Interceptors are used to manipulate requests, request metadata, and responses in arbitrary ways. Example use cases include: * Logging * Verifying requests according to service or custom semantics * Stripping extraneous information from responses These use cases and more can be enabled by injecting an instance of a custom subclass when constructing the RetrieverServiceRestTransport. .. code-block:: python class MyCustomRetrieverServiceInterceptor(RetrieverServiceRestInterceptor): def pre_batch_create_chunks(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_batch_create_chunks(self, response): logging.log(f"Received response: {response}") return response def pre_batch_delete_chunks(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def pre_batch_update_chunks(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_batch_update_chunks(self, response): logging.log(f"Received response: {response}") return response def pre_create_chunk(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_create_chunk(self, response): logging.log(f"Received response: {response}") return response def pre_create_corpus(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_create_corpus(self, response): logging.log(f"Received response: {response}") return response def pre_create_document(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_create_document(self, response): logging.log(f"Received response: {response}") return response def pre_delete_chunk(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def pre_delete_corpus(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def pre_delete_document(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def pre_get_chunk(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_get_chunk(self, response): logging.log(f"Received response: {response}") return response def pre_get_corpus(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_get_corpus(self, response): logging.log(f"Received response: {response}") return response def pre_get_document(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_get_document(self, response): logging.log(f"Received response: {response}") return response def pre_list_chunks(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_list_chunks(self, response): logging.log(f"Received response: {response}") return response def pre_list_corpora(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_list_corpora(self, response): logging.log(f"Received response: {response}") return response def pre_list_documents(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_list_documents(self, response): logging.log(f"Received response: {response}") return response def pre_query_corpus(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_query_corpus(self, response): logging.log(f"Received response: {response}") return response def pre_query_document(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_query_document(self, response): logging.log(f"Received response: {response}") return response def pre_update_chunk(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_update_chunk(self, response): logging.log(f"Received response: {response}") return response def pre_update_corpus(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_update_corpus(self, response): logging.log(f"Received response: {response}") return response def pre_update_document(self, request, metadata): logging.log(f"Received request: {request}") return request, metadata def post_update_document(self, response): logging.log(f"Received response: {response}") return response transport = RetrieverServiceRestTransport(interceptor=MyCustomRetrieverServiceInterceptor()) client = RetrieverServiceClient(transport=transport) """ def pre_batch_create_chunks( self, request: retriever_service.BatchCreateChunksRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.BatchCreateChunksRequest, Sequence[Tuple[str, Union[str, bytes]]], ]: """Pre-rpc interceptor for batch_create_chunks Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_batch_create_chunks( self, response: retriever_service.BatchCreateChunksResponse ) -> retriever_service.BatchCreateChunksResponse: """Post-rpc interceptor for batch_create_chunks Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_batch_delete_chunks( self, request: retriever_service.BatchDeleteChunksRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.BatchDeleteChunksRequest, Sequence[Tuple[str, Union[str, bytes]]], ]: """Pre-rpc interceptor for batch_delete_chunks Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def pre_batch_update_chunks( self, request: retriever_service.BatchUpdateChunksRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.BatchUpdateChunksRequest, Sequence[Tuple[str, Union[str, bytes]]], ]: """Pre-rpc interceptor for batch_update_chunks Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_batch_update_chunks( self, response: retriever_service.BatchUpdateChunksResponse ) -> retriever_service.BatchUpdateChunksResponse: """Post-rpc interceptor for batch_update_chunks Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_create_chunk( self, request: retriever_service.CreateChunkRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.CreateChunkRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for create_chunk Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_create_chunk(self, response: retriever.Chunk) -> retriever.Chunk: """Post-rpc interceptor for create_chunk Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_create_corpus( self, request: retriever_service.CreateCorpusRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.CreateCorpusRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for create_corpus Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_create_corpus(self, response: retriever.Corpus) -> retriever.Corpus: """Post-rpc interceptor for create_corpus Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_create_document( self, request: retriever_service.CreateDocumentRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.CreateDocumentRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for create_document Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_create_document(self, response: retriever.Document) -> retriever.Document: """Post-rpc interceptor for create_document Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_delete_chunk( self, request: retriever_service.DeleteChunkRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.DeleteChunkRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for delete_chunk Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def pre_delete_corpus( self, request: retriever_service.DeleteCorpusRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.DeleteCorpusRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for delete_corpus Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def pre_delete_document( self, request: retriever_service.DeleteDocumentRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.DeleteDocumentRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for delete_document Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def pre_get_chunk( self, request: retriever_service.GetChunkRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.GetChunkRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for get_chunk Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_get_chunk(self, response: retriever.Chunk) -> retriever.Chunk: """Post-rpc interceptor for get_chunk Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_get_corpus( self, request: retriever_service.GetCorpusRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.GetCorpusRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for get_corpus Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_get_corpus(self, response: retriever.Corpus) -> retriever.Corpus: """Post-rpc interceptor for get_corpus Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_get_document( self, request: retriever_service.GetDocumentRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.GetDocumentRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for get_document Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_get_document(self, response: retriever.Document) -> retriever.Document: """Post-rpc interceptor for get_document Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_list_chunks( self, request: retriever_service.ListChunksRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.ListChunksRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for list_chunks Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_list_chunks( self, response: retriever_service.ListChunksResponse ) -> retriever_service.ListChunksResponse: """Post-rpc interceptor for list_chunks Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_list_corpora( self, request: retriever_service.ListCorporaRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.ListCorporaRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for list_corpora Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_list_corpora( self, response: retriever_service.ListCorporaResponse ) -> retriever_service.ListCorporaResponse: """Post-rpc interceptor for list_corpora Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_list_documents( self, request: retriever_service.ListDocumentsRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.ListDocumentsRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for list_documents Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_list_documents( self, response: retriever_service.ListDocumentsResponse ) -> retriever_service.ListDocumentsResponse: """Post-rpc interceptor for list_documents Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_query_corpus( self, request: retriever_service.QueryCorpusRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.QueryCorpusRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for query_corpus Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_query_corpus( self, response: retriever_service.QueryCorpusResponse ) -> retriever_service.QueryCorpusResponse: """Post-rpc interceptor for query_corpus Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_query_document( self, request: retriever_service.QueryDocumentRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.QueryDocumentRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for query_document Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_query_document( self, response: retriever_service.QueryDocumentResponse ) -> retriever_service.QueryDocumentResponse: """Post-rpc interceptor for query_document Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_update_chunk( self, request: retriever_service.UpdateChunkRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.UpdateChunkRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for update_chunk Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_update_chunk(self, response: retriever.Chunk) -> retriever.Chunk: """Post-rpc interceptor for update_chunk Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_update_corpus( self, request: retriever_service.UpdateCorpusRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.UpdateCorpusRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for update_corpus Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_update_corpus(self, response: retriever.Corpus) -> retriever.Corpus: """Post-rpc interceptor for update_corpus Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_update_document( self, request: retriever_service.UpdateDocumentRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ retriever_service.UpdateDocumentRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for update_document Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_update_document(self, response: retriever.Document) -> retriever.Document: """Post-rpc interceptor for update_document Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_get_operation( self, request: operations_pb2.GetOperationRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ operations_pb2.GetOperationRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for get_operation Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_get_operation( self, response: operations_pb2.Operation ) -> operations_pb2.Operation: """Post-rpc interceptor for get_operation Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response def pre_list_operations( self, request: operations_pb2.ListOperationsRequest, metadata: Sequence[Tuple[str, Union[str, bytes]]], ) -> Tuple[ operations_pb2.ListOperationsRequest, Sequence[Tuple[str, Union[str, bytes]]] ]: """Pre-rpc interceptor for list_operations Override in a subclass to manipulate the request or metadata before they are sent to the RetrieverService server. """ return request, metadata def post_list_operations( self, response: operations_pb2.ListOperationsResponse ) -> operations_pb2.ListOperationsResponse: """Post-rpc interceptor for list_operations Override in a subclass to manipulate the response after it is returned by the RetrieverService server but before it is returned to user code. """ return response @dataclasses.dataclass class RetrieverServiceRestStub: _session: AuthorizedSession _host: str _interceptor: RetrieverServiceRestInterceptor class RetrieverServiceRestTransport(_BaseRetrieverServiceRestTransport): """REST backend synchronous transport for RetrieverService. An API for semantic search over a corpus of user uploaded content. This class defines the same methods as the primary client, so the primary client can load the underlying transport implementation and call it. It sends JSON representations of protocol buffers over HTTP/1.1 """ def __init__( self, *, host: str = "generativelanguage.googleapis.com", credentials: Optional[ga_credentials.Credentials] = None, credentials_file: Optional[str] = None, scopes: Optional[Sequence[str]] = None, client_cert_source_for_mtls: Optional[Callable[[], Tuple[bytes, bytes]]] = None, quota_project_id: Optional[str] = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, always_use_jwt_access: Optional[bool] = False, url_scheme: str = "https", interceptor: Optional[RetrieverServiceRestInterceptor] = None, api_audience: Optional[str] = None, ) -> None: """Instantiate the transport. Args: host (Optional[str]): The hostname to connect to (default: 'generativelanguage.googleapis.com'). 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. credentials_file (Optional[str]): A file with credentials that can be loaded with :func:`google.auth.load_credentials_from_file`. This argument is ignored if ``channel`` is provided. scopes (Optional(Sequence[str])): A list of scopes. This argument is ignored if ``channel`` is provided. client_cert_source_for_mtls (Callable[[], Tuple[bytes, bytes]]): Client certificate to configure mutual TLS HTTP channel. It is ignored if ``channel`` is provided. quota_project_id (Optional[str]): An optional project to use for billing and quota. 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 are developing your own client library. always_use_jwt_access (Optional[bool]): Whether self signed JWT should be used for service account credentials. url_scheme: the protocol scheme for the API endpoint. Normally "https", but for testing or local servers, "http" can be specified. """ # Run the base constructor # TODO(yon-mg): resolve other ctor params i.e. scopes, quota, etc. # TODO: When custom host (api_endpoint) is set, `scopes` must *also* be set on the # credentials object super().__init__( host=host, credentials=credentials, client_info=client_info, always_use_jwt_access=always_use_jwt_access, url_scheme=url_scheme, api_audience=api_audience, ) self._session = AuthorizedSession( self._credentials, default_host=self.DEFAULT_HOST ) if client_cert_source_for_mtls: self._session.configure_mtls_channel(client_cert_source_for_mtls) self._interceptor = interceptor or RetrieverServiceRestInterceptor() self._prep_wrapped_messages(client_info) class _BatchCreateChunks( _BaseRetrieverServiceRestTransport._BaseBatchCreateChunks, RetrieverServiceRestStub, ): def __hash__(self): return hash("RetrieverServiceRestTransport.BatchCreateChunks") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.BatchCreateChunksRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.BatchCreateChunksResponse: r"""Call the batch create chunks method over HTTP. Args: request (~.retriever_service.BatchCreateChunksRequest): 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: ~.retriever_service.BatchCreateChunksResponse: Response from ``BatchCreateChunks`` containing a list of created ``Chunk``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseBatchCreateChunks._get_http_options() ) request, metadata = self._interceptor.pre_batch_create_chunks( request, metadata ) transcoded_request = _BaseRetrieverServiceRestTransport._BaseBatchCreateChunks._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseBatchCreateChunks._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseBatchCreateChunks._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.BatchCreateChunks", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "BatchCreateChunks", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._BatchCreateChunks._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever_service.BatchCreateChunksResponse() pb_resp = retriever_service.BatchCreateChunksResponse.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_batch_create_chunks(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = ( retriever_service.BatchCreateChunksResponse.to_json(response) ) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.batch_create_chunks", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "BatchCreateChunks", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _BatchDeleteChunks( _BaseRetrieverServiceRestTransport._BaseBatchDeleteChunks, RetrieverServiceRestStub, ): def __hash__(self): return hash("RetrieverServiceRestTransport.BatchDeleteChunks") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.BatchDeleteChunksRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ): r"""Call the batch delete chunks method over HTTP. Args: request (~.retriever_service.BatchDeleteChunksRequest): 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`. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseBatchDeleteChunks._get_http_options() ) request, metadata = self._interceptor.pre_batch_delete_chunks( request, metadata ) transcoded_request = _BaseRetrieverServiceRestTransport._BaseBatchDeleteChunks._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseBatchDeleteChunks._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseBatchDeleteChunks._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = json_format.MessageToJson(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.BatchDeleteChunks", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "BatchDeleteChunks", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._BatchDeleteChunks._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) class _BatchUpdateChunks( _BaseRetrieverServiceRestTransport._BaseBatchUpdateChunks, RetrieverServiceRestStub, ): def __hash__(self): return hash("RetrieverServiceRestTransport.BatchUpdateChunks") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.BatchUpdateChunksRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.BatchUpdateChunksResponse: r"""Call the batch update chunks method over HTTP. Args: request (~.retriever_service.BatchUpdateChunksRequest): 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: ~.retriever_service.BatchUpdateChunksResponse: Response from ``BatchUpdateChunks`` containing a list of updated ``Chunk``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseBatchUpdateChunks._get_http_options() ) request, metadata = self._interceptor.pre_batch_update_chunks( request, metadata ) transcoded_request = _BaseRetrieverServiceRestTransport._BaseBatchUpdateChunks._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseBatchUpdateChunks._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseBatchUpdateChunks._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.BatchUpdateChunks", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "BatchUpdateChunks", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._BatchUpdateChunks._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever_service.BatchUpdateChunksResponse() pb_resp = retriever_service.BatchUpdateChunksResponse.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_batch_update_chunks(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = ( retriever_service.BatchUpdateChunksResponse.to_json(response) ) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.batch_update_chunks", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "BatchUpdateChunks", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _CreateChunk( _BaseRetrieverServiceRestTransport._BaseCreateChunk, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.CreateChunk") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.CreateChunkRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Chunk: r"""Call the create chunk method over HTTP. Args: request (~.retriever_service.CreateChunkRequest): The request object. Request to create a ``Chunk``. 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: ~.retriever.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 ``Chunk``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseCreateChunk._get_http_options() ) request, metadata = self._interceptor.pre_create_chunk(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseCreateChunk._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseCreateChunk._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseCreateChunk._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.CreateChunk", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "CreateChunk", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._CreateChunk._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Chunk() pb_resp = retriever.Chunk.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_create_chunk(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Chunk.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.create_chunk", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "CreateChunk", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _CreateCorpus( _BaseRetrieverServiceRestTransport._BaseCreateCorpus, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.CreateCorpus") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.CreateCorpusRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Corpus: r"""Call the create corpus method over HTTP. Args: request (~.retriever_service.CreateCorpusRequest): The request object. Request to create 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: ~.retriever.Corpus: A ``Corpus`` is a collection of ``Document``\ s. A project can create up to 5 corpora. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseCreateCorpus._get_http_options() ) request, metadata = self._interceptor.pre_create_corpus(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseCreateCorpus._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseCreateCorpus._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseCreateCorpus._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.CreateCorpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "CreateCorpus", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._CreateCorpus._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Corpus() pb_resp = retriever.Corpus.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_create_corpus(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Corpus.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.create_corpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "CreateCorpus", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _CreateDocument( _BaseRetrieverServiceRestTransport._BaseCreateDocument, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.CreateDocument") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.CreateDocumentRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Document: r"""Call the create document method over HTTP. Args: request (~.retriever_service.CreateDocumentRequest): The request object. Request to create 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: ~.retriever.Document: A ``Document`` is a collection of ``Chunk``\ s. A ``Corpus`` can have a maximum of 10,000 ``Document``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseCreateDocument._get_http_options() ) request, metadata = self._interceptor.pre_create_document(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseCreateDocument._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseCreateDocument._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseCreateDocument._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.CreateDocument", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "CreateDocument", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._CreateDocument._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Document() pb_resp = retriever.Document.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_create_document(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Document.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.create_document", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "CreateDocument", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _DeleteChunk( _BaseRetrieverServiceRestTransport._BaseDeleteChunk, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.DeleteChunk") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.DeleteChunkRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ): r"""Call the delete chunk method over HTTP. Args: request (~.retriever_service.DeleteChunkRequest): The request object. Request to delete a ``Chunk``. 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`. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseDeleteChunk._get_http_options() ) request, metadata = self._interceptor.pre_delete_chunk(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseDeleteChunk._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseDeleteChunk._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = json_format.MessageToJson(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.DeleteChunk", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "DeleteChunk", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._DeleteChunk._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) class _DeleteCorpus( _BaseRetrieverServiceRestTransport._BaseDeleteCorpus, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.DeleteCorpus") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.DeleteCorpusRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ): r"""Call the delete corpus method over HTTP. Args: request (~.retriever_service.DeleteCorpusRequest): The request object. Request to delete 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`. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseDeleteCorpus._get_http_options() ) request, metadata = self._interceptor.pre_delete_corpus(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseDeleteCorpus._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseDeleteCorpus._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = json_format.MessageToJson(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.DeleteCorpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "DeleteCorpus", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._DeleteCorpus._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) class _DeleteDocument( _BaseRetrieverServiceRestTransport._BaseDeleteDocument, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.DeleteDocument") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.DeleteDocumentRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ): r"""Call the delete document method over HTTP. Args: request (~.retriever_service.DeleteDocumentRequest): The request object. Request to delete 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`. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseDeleteDocument._get_http_options() ) request, metadata = self._interceptor.pre_delete_document(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseDeleteDocument._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseDeleteDocument._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = json_format.MessageToJson(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.DeleteDocument", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "DeleteDocument", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._DeleteDocument._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) class _GetChunk( _BaseRetrieverServiceRestTransport._BaseGetChunk, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.GetChunk") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.GetChunkRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Chunk: r"""Call the get chunk method over HTTP. Args: request (~.retriever_service.GetChunkRequest): The request object. Request for getting information about a specific ``Chunk``. 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: ~.retriever.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 ``Chunk``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseGetChunk._get_http_options() ) request, metadata = self._interceptor.pre_get_chunk(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseGetChunk._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = ( _BaseRetrieverServiceRestTransport._BaseGetChunk._get_query_params_json( transcoded_request ) ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.GetChunk", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetChunk", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._GetChunk._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Chunk() pb_resp = retriever.Chunk.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_get_chunk(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Chunk.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.get_chunk", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetChunk", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _GetCorpus( _BaseRetrieverServiceRestTransport._BaseGetCorpus, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.GetCorpus") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.GetCorpusRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Corpus: r"""Call the get corpus method over HTTP. Args: request (~.retriever_service.GetCorpusRequest): The request object. Request for getting information about a specific ``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: ~.retriever.Corpus: A ``Corpus`` is a collection of ``Document``\ s. A project can create up to 5 corpora. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseGetCorpus._get_http_options() ) request, metadata = self._interceptor.pre_get_corpus(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseGetCorpus._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseGetCorpus._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.GetCorpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetCorpus", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._GetCorpus._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Corpus() pb_resp = retriever.Corpus.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_get_corpus(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Corpus.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.get_corpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetCorpus", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _GetDocument( _BaseRetrieverServiceRestTransport._BaseGetDocument, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.GetDocument") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.GetDocumentRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Document: r"""Call the get document method over HTTP. Args: request (~.retriever_service.GetDocumentRequest): The request object. Request for getting information about a specific ``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: ~.retriever.Document: A ``Document`` is a collection of ``Chunk``\ s. A ``Corpus`` can have a maximum of 10,000 ``Document``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseGetDocument._get_http_options() ) request, metadata = self._interceptor.pre_get_document(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseGetDocument._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseGetDocument._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.GetDocument", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetDocument", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._GetDocument._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Document() pb_resp = retriever.Document.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_get_document(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Document.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.get_document", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetDocument", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _ListChunks( _BaseRetrieverServiceRestTransport._BaseListChunks, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.ListChunks") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.ListChunksRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.ListChunksResponse: r"""Call the list chunks method over HTTP. Args: request (~.retriever_service.ListChunksRequest): The request object. Request for listing ``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: ~.retriever_service.ListChunksResponse: Response from ``ListChunks`` containing a paginated list of ``Chunk``\ s. The ``Chunk``\ s are sorted by ascending ``chunk.create_time``. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseListChunks._get_http_options() ) request, metadata = self._interceptor.pre_list_chunks(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseListChunks._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseListChunks._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.ListChunks", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListChunks", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._ListChunks._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever_service.ListChunksResponse() pb_resp = retriever_service.ListChunksResponse.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_list_chunks(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever_service.ListChunksResponse.to_json( response ) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.list_chunks", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListChunks", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _ListCorpora( _BaseRetrieverServiceRestTransport._BaseListCorpora, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.ListCorpora") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.ListCorporaRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.ListCorporaResponse: r"""Call the list corpora method over HTTP. Args: request (~.retriever_service.ListCorporaRequest): 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: ~.retriever_service.ListCorporaResponse: Response from ``ListCorpora`` containing a paginated list of ``Corpora``. The results are sorted by ascending ``corpus.create_time``. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseListCorpora._get_http_options() ) request, metadata = self._interceptor.pre_list_corpora(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseListCorpora._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseListCorpora._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.ListCorpora", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListCorpora", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._ListCorpora._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever_service.ListCorporaResponse() pb_resp = retriever_service.ListCorporaResponse.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_list_corpora(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever_service.ListCorporaResponse.to_json( response ) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.list_corpora", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListCorpora", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _ListDocuments( _BaseRetrieverServiceRestTransport._BaseListDocuments, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.ListDocuments") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: retriever_service.ListDocumentsRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.ListDocumentsResponse: r"""Call the list documents method over HTTP. Args: request (~.retriever_service.ListDocumentsRequest): The request object. Request for listing ``Document``\ 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: ~.retriever_service.ListDocumentsResponse: Response from ``ListDocuments`` containing a paginated list of ``Document``\ s. The ``Document``\ s are sorted by ascending ``document.create_time``. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseListDocuments._get_http_options() ) request, metadata = self._interceptor.pre_list_documents(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseListDocuments._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseListDocuments._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.ListDocuments", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListDocuments", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._ListDocuments._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever_service.ListDocumentsResponse() pb_resp = retriever_service.ListDocumentsResponse.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_list_documents(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever_service.ListDocumentsResponse.to_json( response ) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.list_documents", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListDocuments", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _QueryCorpus( _BaseRetrieverServiceRestTransport._BaseQueryCorpus, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.QueryCorpus") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.QueryCorpusRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.QueryCorpusResponse: r"""Call the query corpus method over HTTP. Args: request (~.retriever_service.QueryCorpusRequest): 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: ~.retriever_service.QueryCorpusResponse: Response from ``QueryCorpus`` containing a list of relevant chunks. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseQueryCorpus._get_http_options() ) request, metadata = self._interceptor.pre_query_corpus(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseQueryCorpus._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseQueryCorpus._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseQueryCorpus._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.QueryCorpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "QueryCorpus", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._QueryCorpus._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever_service.QueryCorpusResponse() pb_resp = retriever_service.QueryCorpusResponse.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_query_corpus(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever_service.QueryCorpusResponse.to_json( response ) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.query_corpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "QueryCorpus", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _QueryDocument( _BaseRetrieverServiceRestTransport._BaseQueryDocument, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.QueryDocument") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.QueryDocumentRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever_service.QueryDocumentResponse: r"""Call the query document method over HTTP. Args: request (~.retriever_service.QueryDocumentRequest): 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: ~.retriever_service.QueryDocumentResponse: Response from ``QueryDocument`` containing a list of relevant chunks. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseQueryDocument._get_http_options() ) request, metadata = self._interceptor.pre_query_document(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseQueryDocument._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseQueryDocument._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseQueryDocument._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.QueryDocument", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "QueryDocument", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._QueryDocument._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever_service.QueryDocumentResponse() pb_resp = retriever_service.QueryDocumentResponse.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_query_document(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever_service.QueryDocumentResponse.to_json( response ) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.query_document", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "QueryDocument", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _UpdateChunk( _BaseRetrieverServiceRestTransport._BaseUpdateChunk, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.UpdateChunk") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.UpdateChunkRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Chunk: r"""Call the update chunk method over HTTP. Args: request (~.retriever_service.UpdateChunkRequest): The request object. Request to update a ``Chunk``. 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: ~.retriever.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 ``Chunk``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseUpdateChunk._get_http_options() ) request, metadata = self._interceptor.pre_update_chunk(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseUpdateChunk._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseUpdateChunk._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseUpdateChunk._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.UpdateChunk", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "UpdateChunk", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._UpdateChunk._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Chunk() pb_resp = retriever.Chunk.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_update_chunk(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Chunk.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.update_chunk", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "UpdateChunk", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _UpdateCorpus( _BaseRetrieverServiceRestTransport._BaseUpdateCorpus, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.UpdateCorpus") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.UpdateCorpusRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Corpus: r"""Call the update corpus method over HTTP. Args: request (~.retriever_service.UpdateCorpusRequest): The request object. Request to update 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: ~.retriever.Corpus: A ``Corpus`` is a collection of ``Document``\ s. A project can create up to 5 corpora. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseUpdateCorpus._get_http_options() ) request, metadata = self._interceptor.pre_update_corpus(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseUpdateCorpus._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseUpdateCorpus._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseUpdateCorpus._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.UpdateCorpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "UpdateCorpus", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._UpdateCorpus._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Corpus() pb_resp = retriever.Corpus.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_update_corpus(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Corpus.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.update_corpus", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "UpdateCorpus", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp class _UpdateDocument( _BaseRetrieverServiceRestTransport._BaseUpdateDocument, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.UpdateDocument") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), data=body, ) return response def __call__( self, request: retriever_service.UpdateDocumentRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> retriever.Document: r"""Call the update document method over HTTP. Args: request (~.retriever_service.UpdateDocumentRequest): The request object. Request to update 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: ~.retriever.Document: A ``Document`` is a collection of ``Chunk``\ s. A ``Corpus`` can have a maximum of 10,000 ``Document``\ s. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseUpdateDocument._get_http_options() ) request, metadata = self._interceptor.pre_update_document(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseUpdateDocument._get_transcoded_request( http_options, request ) body = _BaseRetrieverServiceRestTransport._BaseUpdateDocument._get_request_body_json( transcoded_request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseUpdateDocument._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = type(request).to_json(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.UpdateDocument", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "UpdateDocument", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._UpdateDocument._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, body, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) # Return the response resp = retriever.Document() pb_resp = retriever.Document.pb(resp) json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True) resp = self._interceptor.post_update_document(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = retriever.Document.to_json(response) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceClient.update_document", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "UpdateDocument", "metadata": http_response["headers"], "httpResponse": http_response, }, ) return resp @property def batch_create_chunks( self, ) -> Callable[ [retriever_service.BatchCreateChunksRequest], retriever_service.BatchCreateChunksResponse, ]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._BatchCreateChunks(self._session, self._host, self._interceptor) # type: ignore @property def batch_delete_chunks( self, ) -> Callable[[retriever_service.BatchDeleteChunksRequest], empty_pb2.Empty]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._BatchDeleteChunks(self._session, self._host, self._interceptor) # type: ignore @property def batch_update_chunks( self, ) -> Callable[ [retriever_service.BatchUpdateChunksRequest], retriever_service.BatchUpdateChunksResponse, ]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._BatchUpdateChunks(self._session, self._host, self._interceptor) # type: ignore @property def create_chunk( self, ) -> Callable[[retriever_service.CreateChunkRequest], retriever.Chunk]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._CreateChunk(self._session, self._host, self._interceptor) # type: ignore @property def create_corpus( self, ) -> Callable[[retriever_service.CreateCorpusRequest], retriever.Corpus]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._CreateCorpus(self._session, self._host, self._interceptor) # type: ignore @property def create_document( self, ) -> Callable[[retriever_service.CreateDocumentRequest], retriever.Document]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._CreateDocument(self._session, self._host, self._interceptor) # type: ignore @property def delete_chunk( self, ) -> Callable[[retriever_service.DeleteChunkRequest], empty_pb2.Empty]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._DeleteChunk(self._session, self._host, self._interceptor) # type: ignore @property def delete_corpus( self, ) -> Callable[[retriever_service.DeleteCorpusRequest], empty_pb2.Empty]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._DeleteCorpus(self._session, self._host, self._interceptor) # type: ignore @property def delete_document( self, ) -> Callable[[retriever_service.DeleteDocumentRequest], empty_pb2.Empty]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._DeleteDocument(self._session, self._host, self._interceptor) # type: ignore @property def get_chunk( self, ) -> Callable[[retriever_service.GetChunkRequest], retriever.Chunk]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._GetChunk(self._session, self._host, self._interceptor) # type: ignore @property def get_corpus( self, ) -> Callable[[retriever_service.GetCorpusRequest], retriever.Corpus]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._GetCorpus(self._session, self._host, self._interceptor) # type: ignore @property def get_document( self, ) -> Callable[[retriever_service.GetDocumentRequest], retriever.Document]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._GetDocument(self._session, self._host, self._interceptor) # type: ignore @property def list_chunks( self, ) -> Callable[ [retriever_service.ListChunksRequest], retriever_service.ListChunksResponse ]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._ListChunks(self._session, self._host, self._interceptor) # type: ignore @property def list_corpora( self, ) -> Callable[ [retriever_service.ListCorporaRequest], retriever_service.ListCorporaResponse ]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._ListCorpora(self._session, self._host, self._interceptor) # type: ignore @property def list_documents( self, ) -> Callable[ [retriever_service.ListDocumentsRequest], retriever_service.ListDocumentsResponse, ]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._ListDocuments(self._session, self._host, self._interceptor) # type: ignore @property def query_corpus( self, ) -> Callable[ [retriever_service.QueryCorpusRequest], retriever_service.QueryCorpusResponse ]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._QueryCorpus(self._session, self._host, self._interceptor) # type: ignore @property def query_document( self, ) -> Callable[ [retriever_service.QueryDocumentRequest], retriever_service.QueryDocumentResponse, ]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._QueryDocument(self._session, self._host, self._interceptor) # type: ignore @property def update_chunk( self, ) -> Callable[[retriever_service.UpdateChunkRequest], retriever.Chunk]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._UpdateChunk(self._session, self._host, self._interceptor) # type: ignore @property def update_corpus( self, ) -> Callable[[retriever_service.UpdateCorpusRequest], retriever.Corpus]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._UpdateCorpus(self._session, self._host, self._interceptor) # type: ignore @property def update_document( self, ) -> Callable[[retriever_service.UpdateDocumentRequest], retriever.Document]: # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here. # In C++ this would require a dynamic_cast return self._UpdateDocument(self._session, self._host, self._interceptor) # type: ignore @property def get_operation(self): return self._GetOperation(self._session, self._host, self._interceptor) # type: ignore class _GetOperation( _BaseRetrieverServiceRestTransport._BaseGetOperation, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.GetOperation") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: operations_pb2.GetOperationRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> operations_pb2.Operation: r"""Call the get operation method over HTTP. Args: request (operations_pb2.GetOperationRequest): The request object 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: Response from GetOperation method. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseGetOperation._get_http_options() ) request, metadata = self._interceptor.pre_get_operation(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseGetOperation._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseGetOperation._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = json_format.MessageToJson(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.GetOperation", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetOperation", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._GetOperation._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) content = response.content.decode("utf-8") resp = operations_pb2.Operation() resp = json_format.Parse(content, resp) resp = self._interceptor.post_get_operation(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = json_format.MessageToJson(resp) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceAsyncClient.GetOperation", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "GetOperation", "httpResponse": http_response, "metadata": http_response["headers"], }, ) return resp @property def list_operations(self): return self._ListOperations(self._session, self._host, self._interceptor) # type: ignore class _ListOperations( _BaseRetrieverServiceRestTransport._BaseListOperations, RetrieverServiceRestStub ): def __hash__(self): return hash("RetrieverServiceRestTransport.ListOperations") @staticmethod def _get_response( host, metadata, query_params, session, timeout, transcoded_request, body=None, ): uri = transcoded_request["uri"] method = transcoded_request["method"] headers = dict(metadata) headers["Content-Type"] = "application/json" response = getattr(session, method)( "{host}{uri}".format(host=host, uri=uri), timeout=timeout, headers=headers, params=rest_helpers.flatten_query_params(query_params, strict=True), ) return response def __call__( self, request: operations_pb2.ListOperationsRequest, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> operations_pb2.ListOperationsResponse: r"""Call the list operations method over HTTP. Args: request (operations_pb2.ListOperationsRequest): The request object 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 from ListOperations method. """ http_options = ( _BaseRetrieverServiceRestTransport._BaseListOperations._get_http_options() ) request, metadata = self._interceptor.pre_list_operations(request, metadata) transcoded_request = _BaseRetrieverServiceRestTransport._BaseListOperations._get_transcoded_request( http_options, request ) # Jsonify the query params query_params = _BaseRetrieverServiceRestTransport._BaseListOperations._get_query_params_json( transcoded_request ) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER request_url = "{host}{uri}".format( host=self._host, uri=transcoded_request["uri"] ) method = transcoded_request["method"] try: request_payload = json_format.MessageToJson(request) except: request_payload = None http_request = { "payload": request_payload, "requestMethod": method, "requestUrl": request_url, "headers": dict(metadata), } _LOGGER.debug( f"Sending request for google.ai.generativelanguage_v1beta.RetrieverServiceClient.ListOperations", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListOperations", "httpRequest": http_request, "metadata": http_request["headers"], }, ) # Send the request response = RetrieverServiceRestTransport._ListOperations._get_response( self._host, metadata, query_params, self._session, timeout, transcoded_request, ) # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception # subclass. if response.status_code >= 400: raise core_exceptions.from_http_response(response) content = response.content.decode("utf-8") resp = operations_pb2.ListOperationsResponse() resp = json_format.Parse(content, resp) resp = self._interceptor.post_list_operations(resp) if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( logging.DEBUG ): # pragma: NO COVER try: response_payload = json_format.MessageToJson(resp) except: response_payload = None http_response = { "payload": response_payload, "headers": dict(response.headers), "status": response.status_code, } _LOGGER.debug( "Received response for google.ai.generativelanguage_v1beta.RetrieverServiceAsyncClient.ListOperations", extra={ "serviceName": "google.ai.generativelanguage.v1beta.RetrieverService", "rpcName": "ListOperations", "httpResponse": http_response, "metadata": http_response["headers"], }, ) return resp @property def kind(self) -> str: return "rest" def close(self): self._session.close() __all__ = ("RetrieverServiceRestTransport",)