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get_ingestion_job

get_ingestion_job(
    knowledge_base_id: Id,
    data_source_id: Id,
    ingestion_job_id: Id,
    *,
    config_overrides: Optional[BedrockAgentClientConfig] = None,
) -> GetIngestionJobResponse

Gets information about a data ingestion job. Data sources are ingested into your knowledge base so that Large Language Models (LLMs) can use your data.

Parameters:

  • knowledge_base_id (Id) –

    The unique identifier of the knowledge base for the data ingestion job you want to get information on.

  • data_source_id (Id) –

    The unique identifier of the data source for the data ingestion job you want to get information on.

  • ingestion_job_id (Id) –

    The unique identifier of the data ingestion job you want to get information on.

Raises:

Source code in docs_src/capo_bedrock_agent/_services/bedrock_agent.py
def get_ingestion_job(
    self,
    knowledge_base_id: "capo_bedrock_agent.types.id.Id",
    data_source_id: "capo_bedrock_agent.types.id.Id",
    ingestion_job_id: "capo_bedrock_agent.types.id.Id",
    *,
    config_overrides: Optional[BedrockAgentClientConfig] = None,
) -> "capo_bedrock_agent.types.get_ingestion_job_response.GetIngestionJobResponse":
    """<p>Gets information about a data ingestion job. Data sources are ingested into your knowledge base so that Large Language Models (LLMs) can use your data.</p>

    Args:
        knowledge_base_id: <p>The unique identifier of the knowledge base for the data ingestion job you want to get information on.</p>
        data_source_id: <p>The unique identifier of the data source for the data ingestion job you want to get information on.</p>
        ingestion_job_id: <p>The unique identifier of the data ingestion job you want to get information on.</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.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.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.get_ingestion_job_request.GetIngestionJobRequest]",
    ) -> OperationResponse[
        "capo_bedrock_agent.types.get_ingestion_job_response.GetIngestionJobResponse"
    ]:
        import capo_bedrock_agent._operations.amazon_bedrock_agent_build_time_lambda.get_ingestion_job

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetIngestionJob")
    )
    input_: capo_bedrock_agent.types.get_ingestion_job_request.GetIngestionJobRequest = {
        "knowledge_base_id": knowledge_base_id,
        "data_source_id": data_source_id,
        "ingestion_job_id": ingestion_job_id,
    }

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