retrieve ¶

def retrieve(
    self,
    knowledge_base_id: "capo_bedrock_agent_runtime.types.knowledge_base_identifier.KnowledgeBaseIdentifier",
    retrieval_query: "capo_bedrock_agent_runtime.types.knowledge_base_query.KnowledgeBaseQuery",
    *,
    config_overrides: Optional[BedrockAgentRuntimeClientConfig] = None,
    retrieval_configuration: Optional[
        "capo_bedrock_agent_runtime.types.knowledge_base_retrieval_configuration.KnowledgeBaseRetrievalConfiguration"
    ] = None,
    guardrail_configuration: Optional[
        "capo_bedrock_agent_runtime.types.guardrail_configuration.GuardrailConfiguration"
    ] = None,
    next_token: Optional[
        "capo_bedrock_agent_runtime.types.next_token.NextToken"
    ] = None,
    user_context: Optional[
        "capo_bedrock_agent_runtime.types.user_context.UserContext"
    ] = None,
) -> "capo_bedrock_agent_runtime.types.retrieve_response.RetrieveResponse":
    """<p>Queries a knowledge base and retrieves information from it.</p>

    Args:
        knowledge_base_id: <p>The unique identifier of the knowledge base to query.</p>
        retrieval_query: <p>Contains the query to send the knowledge base.</p>
        retrieval_configuration: <p>Contains configurations for the knowledge base query and retrieval process. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/kb-test-config.html">Query configurations</a>.</p>
        guardrail_configuration: <p>Guardrail settings.</p>
        next_token: <p>If there are more results than can fit in the response, the response returns a <code>nextToken</code>. Use this token in the <code>nextToken</code> field of another request to retrieve the next batch of results.</p>
        user_context: <p>Contains information about the user making the request. This is used for access control filtering to ensure that retrieval results only include documents the user is authorized to access.</p>

    Raises:
        capo_bedrock_agent_runtime.errors.access_denied_exception.AccessDeniedException: <p>The request is denied because of missing access permissions. Check your permissions and retry your request.</p>
        capo_bedrock_agent_runtime.errors.bad_gateway_exception.BadGatewayException: <p>There was an issue with a dependency due to a server issue. Retry your request.</p>
        capo_bedrock_agent_runtime.errors.conflict_exception.ConflictException: <p>There was a conflict performing an operation. Resolve the conflict and retry your request.</p>
        capo_bedrock_agent_runtime.errors.dependency_failed_exception.DependencyFailedException: <p>There was an issue with a dependency. Check the resource configurations and retry the request.</p>
        capo_bedrock_agent_runtime.errors.internal_server_exception.InternalServerException: <p>An internal server error occurred. Retry your request.</p>
        capo_bedrock_agent_runtime.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.</p>
        capo_bedrock_agent_runtime.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The number of requests exceeds the service quota. Resubmit your request later.</p>
        capo_bedrock_agent_runtime.errors.throttling_exception.ThrottlingException: <p>The number of requests exceeds the limit. Resubmit your request later.</p>
        capo_bedrock_agent_runtime.errors.validation_exception.ValidationException: <p>Input validation failed. Check your request parameters and retry the request.</p>
        capo_bedrock_agent_runtime.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_bedrock_agent_runtime.types.retrieve_request.RetrieveRequest]",
    ) -> OperationResponse[
        "capo_bedrock_agent_runtime.types.retrieve_response.RetrieveResponse"
    ]:
        import capo_bedrock_agent_runtime._operations.amazon_bedrock_agent_run_time_service.retrieve

        output, http_response = (
            capo_bedrock_agent_runtime._operations.amazon_bedrock_agent_run_time_service.retrieve.retrieve(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_bedrock_agent_runtime.types.retrieve_request.RetrieveRequest",
    ) -> dict[str, Any]:
        import capo_bedrock_agent_runtime.types.retrieve_request

        return capo_bedrock_agent_runtime.types.retrieve_request.redact_sensitive(
            input_
        )

    def _redact_output(
        output: "capo_bedrock_agent_runtime.types.retrieve_response.RetrieveResponse",
    ) -> dict[str, Any]:
        import capo_bedrock_agent_runtime.types.retrieve_response

        return capo_bedrock_agent_runtime.types.retrieve_response.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging(
            "Retrieve", redact_input=_redact_input, redact_output=_redact_output
        ),
    )
    input_: capo_bedrock_agent_runtime.types.retrieve_request.RetrieveRequest = {
        "knowledge_base_id": knowledge_base_id,
        "retrieval_query": retrieval_query,
    }
    if retrieval_configuration is not None:
        input_["retrieval_configuration"] = retrieval_configuration
    if guardrail_configuration is not None:
        input_["guardrail_configuration"] = guardrail_configuration
    if next_token is not None:
        input_["next_token"] = next_token
    if user_context is not None:
        input_["user_context"] = user_context

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output