list_dataset_examples ¶

def list_dataset_examples(
    self,
    dataset_id: "capo_bedrock_agentcore_control.types.dataset_id.DatasetId",
    *,
    config_overrides: Optional[BedrockAgentCoreControlClientConfig] = None,
    dataset_version: Optional[
        "capo_bedrock_agentcore_control.types.dataset_version.DatasetVersion"
    ] = None,
    max_results: Optional[int] = None,
    next_token: Optional[str] = None,
) -> "capo_bedrock_agentcore_control.types.list_dataset_examples_response.ListDatasetExamplesResponse":
    """<p> Returns paginated examples from the dataset. The server embeds the resolved version in the pagination token. Once pagination begins, all subsequent pages are pinned to that version regardless of concurrent mutations. </p>

    Args:
        dataset_id: <p> The unique identifier of the dataset. </p>
        dataset_version: <p> Version to paginate: "DRAFT" or a version number. Defaults to DRAFT if absent. Only used on the first request; for subsequent pages, the version is extracted from the pagination token. </p>
        max_results: <p> Maximum number of examples to return per page. </p>
        next_token: <p> The token for the next page of results. </p>

    Raises:
        capo_bedrock_agentcore_control.errors.access_denied_exception.AccessDeniedException: <p>This exception is thrown when a request is denied per access permissions</p>
        capo_bedrock_agentcore_control.errors.conflict_exception.ConflictException: <p>This exception is thrown when there is a conflict performing an operation</p>
        capo_bedrock_agentcore_control.errors.internal_server_exception.InternalServerException: <p>This exception is thrown if there was an unexpected error during processing of request</p>
        capo_bedrock_agentcore_control.errors.resource_not_found_exception.ResourceNotFoundException: <p>This exception is thrown when a resource referenced by the operation does not exist</p>
        capo_bedrock_agentcore_control.errors.throttling_exception.ThrottlingException: <p>This exception is thrown when the number of requests exceeds the limit</p>
        capo_bedrock_agentcore_control.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by the service.</p>
        capo_bedrock_agentcore_control.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_bedrock_agentcore_control.types.list_dataset_examples_request.ListDatasetExamplesRequest]",
    ) -> OperationResponse[
        "capo_bedrock_agentcore_control.types.list_dataset_examples_response.ListDatasetExamplesResponse"
    ]:
        import capo_bedrock_agentcore_control._operations.amazon_bedrock_agent_core_control.list_dataset_examples

        output, http_response = (
            capo_bedrock_agentcore_control._operations.amazon_bedrock_agent_core_control.list_dataset_examples.list_dataset_examples(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_bedrock_agentcore_control.types.list_dataset_examples_response.ListDatasetExamplesResponse",
    ) -> dict[str, Any]:
        import capo_bedrock_agentcore_control.types.list_dataset_examples_response

        return capo_bedrock_agentcore_control.types.list_dataset_examples_response.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("ListDatasetExamples", redact_output=_redact_output),
    )
    input_: capo_bedrock_agentcore_control.types.list_dataset_examples_request.ListDatasetExamplesRequest = {
        "dataset_id": dataset_id
    }
    if dataset_version is not None:
        input_["dataset_version"] = dataset_version
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token

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