associate_agent_knowledge_base ¶

def associate_agent_knowledge_base(
    self,
    agent_id: "capo_bedrock_agent.types.id.Id",
    agent_version: "capo_bedrock_agent.types.draft_version.DraftVersion",
    knowledge_base_id: "capo_bedrock_agent.types.id.Id",
    description: "capo_bedrock_agent.types.description.Description",
    *,
    config_overrides: Optional[BedrockAgentClientConfig] = None,
    knowledge_base_state: Optional[
        "capo_bedrock_agent.types.knowledge_base_state.KnowledgeBaseState"
    ] = None,
) -> "capo_bedrock_agent.types.associate_agent_knowledge_base_response.AssociateAgentKnowledgeBaseResponse":
    """<p>Associates a knowledge base with an agent. If a knowledge base is associated and its <code>indexState</code> is set to <code>Enabled</code>, the agent queries the knowledge base for information to augment its response to the user.</p>

    Args:
        agent_id: <p>The unique identifier of the agent with which you want to associate the knowledge base.</p>
        agent_version: <p>The version of the agent with which you want to associate the knowledge base.</p>
        knowledge_base_id: <p>The unique identifier of the knowledge base to associate with the agent.</p>
        description: <p>A description of what the agent should use the knowledge base for.</p>
        knowledge_base_state: <p>Specifies whether to use the knowledge base or not when sending an <a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_agent-runtime_InvokeAgent.html">InvokeAgent</a> request.</p>

    Raises:
        capo_bedrock_agent.errors.access_denied_exception.AccessDeniedException: <p>The request is denied because of missing access permissions.</p>
        capo_bedrock_agent.errors.conflict_exception.ConflictException: <p>There was a conflict performing an operation.</p>
        capo_bedrock_agent.errors.internal_server_exception.InternalServerException: <p>An internal server error occurred. Retry your request.</p>
        capo_bedrock_agent.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.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The number of requests exceeds the service quota. Resubmit your request later.</p>
        capo_bedrock_agent.errors.throttling_exception.ThrottlingException: <p>The number of requests exceeds the limit. Resubmit your request later.</p>
        capo_bedrock_agent.errors.validation_exception.ValidationException: <p>Input validation failed. Check your request parameters and retry the request.</p>
        capo_bedrock_agent.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_bedrock_agent.types.associate_agent_knowledge_base_request.AssociateAgentKnowledgeBaseRequest]",
    ) -> OperationResponse[
        "capo_bedrock_agent.types.associate_agent_knowledge_base_response.AssociateAgentKnowledgeBaseResponse"
    ]:
        import capo_bedrock_agent._operations.amazon_bedrock_agent_build_time_lambda.associate_agent_knowledge_base

        output, http_response = (
            capo_bedrock_agent._operations.amazon_bedrock_agent_build_time_lambda.associate_agent_knowledge_base.associate_agent_knowledge_base(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("AssociateAgentKnowledgeBase")
    )
    input_: capo_bedrock_agent.types.associate_agent_knowledge_base_request.AssociateAgentKnowledgeBaseRequest = {
        "agent_id": agent_id,
        "agent_version": agent_version,
        "knowledge_base_id": knowledge_base_id,
        "description": description,
    }
    if knowledge_base_state is not None:
        input_["knowledge_base_state"] = knowledge_base_state

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