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get_ingested_document_acl

get_ingested_document_acl(
    knowledge_base_id: KnowledgeBaseIdentifier,
    data_source_id: DataSourceId,
    document_id: DocumentId,
    *,
    config_overrides: Optional[BedrockAgentRuntimeClientConfig] = None,
) -> GetIngestedDocumentAclResponse

Retrieves the ingested access control list (ACL) for a specific document in a knowledge base. Use this operation to inspect the allow and deny lists that were ingested for a document to troubleshoot access control issues. To use this operation, you must have the bedrock:GetIngestedDocumentAcl permission.

Parameters:

  • knowledge_base_id (KnowledgeBaseIdentifier) –

    The unique identifier of the knowledge base that contains the document.

  • data_source_id (DataSourceId) –

    The unique identifier of the data source that contains the document.

  • document_id (DocumentId) –

    The unique identifier of the document to retrieve the ingested access control list (ACL) for.

Raises:

  • AccessDeniedException –

    The request is denied because of missing access permissions. Check your permissions and retry your request.

  • InternalServerException –

    An internal server error occurred. Retry your request.

  • ResourceNotFoundException –

    The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.

  • ThrottlingException –

    The number of requests exceeds the limit. Resubmit your request later.

  • ValidationException –

    Input validation failed. Check your request parameters and retry the request.

  • UnknownServiceError –

    The service returned an error code this client does not model.

Source code in docs_src/capo_bedrock_agent_runtime/_services/bedrock_agent_runtime.py
def get_ingested_document_acl(
    self,
    knowledge_base_id: "capo_bedrock_agent_runtime.types.knowledge_base_identifier.KnowledgeBaseIdentifier",
    data_source_id: "capo_bedrock_agent_runtime.types.data_source_id.DataSourceId",
    document_id: "capo_bedrock_agent_runtime.types.document_id.DocumentId",
    *,
    config_overrides: Optional[BedrockAgentRuntimeClientConfig] = None,
) -> "capo_bedrock_agent_runtime.types.get_ingested_document_acl_response.GetIngestedDocumentAclResponse":
    """<p>Retrieves the ingested access control list (ACL) for a specific document in a knowledge base. Use this operation to inspect the allow and deny lists that were ingested for a document to troubleshoot access control issues. To use this operation, you must have the <code>bedrock:GetIngestedDocumentAcl</code> permission.</p>

    Args:
        knowledge_base_id: <p>The unique identifier of the knowledge base that contains the document.</p>
        data_source_id: <p>The unique identifier of the data source that contains the document.</p>
        document_id: <p>The unique identifier of the document to retrieve the ingested access control list (ACL) for.</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.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.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.get_ingested_document_acl_request.GetIngestedDocumentAclRequest]",
    ) -> OperationResponse[
        "capo_bedrock_agent_runtime.types.get_ingested_document_acl_response.GetIngestedDocumentAclResponse"
    ]:
        import capo_bedrock_agent_runtime._operations.amazon_bedrock_agent_run_time_service.get_ingested_document_acl

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

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

        return capo_bedrock_agent_runtime.types.get_ingested_document_acl_response.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("GetIngestedDocumentAcl", redact_output=_redact_output),
    )
    input_: capo_bedrock_agent_runtime.types.get_ingested_document_acl_request.GetIngestedDocumentAclRequest = {
        "knowledge_base_id": knowledge_base_id,
        "data_source_id": data_source_id,
        "document_id": document_id,
    }

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