create_dataset ¶

def create_dataset(
    self,
    dataset_name: "capo_bedrock_agentcore_control.types.dataset_name.DatasetName",
    source: "capo_bedrock_agentcore_control.types.data_source_type.DataSourceType",
    schema_type: "capo_bedrock_agentcore_control.types.dataset_schema_type.DatasetSchemaType",
    *,
    config_overrides: Optional[BedrockAgentCoreControlClientConfig] = None,
    client_token: Optional[
        "capo_bedrock_agentcore_control.types.client_token.ClientToken"
    ] = None,
    description: Optional[str] = None,
    kms_key_arn: Optional[
        "capo_bedrock_agentcore_control.types.kms_key_arn.KmsKeyArn"
    ] = None,
    tags: Optional["capo_bedrock_agentcore_control.types.tags_map.TagsMap"] = None,
) -> "capo_bedrock_agentcore_control.types.create_dataset_response.CreateDatasetResponse":
    """<p> Creates a new dataset resource asynchronously. Returns immediately with status CREATING. Poll <code>GetDataset</code> until status transitions to ACTIVE or CREATE_FAILED. </p>

    Args:
        client_token: <p>A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If you don't specify this field, a value is randomly generated for you. If this token matches a previous request, the service ignores the request, but doesn't return an error. For more information, see <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a>.</p>
        dataset_name: <p> Human-readable name for the dataset. Must be unique within the account. Immutable after creation. </p>
        description: <p> A description of the dataset. </p>
        source: <p> Source of initial examples. Provide either inline examples or an S3 URI pointing to a JSONL file. </p>
        schema_type: <p> Versioned schema type governing the structure of examples. Immutable after creation. </p>
        kms_key_arn: <p> Optional KMS key ARN for server-side encryption on service Amazon S3 writes. </p>
        tags: <p> A map of tag keys and values to assign to the dataset. </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.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>This exception is thrown when a request is made beyond the service quota</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.create_dataset_request.CreateDatasetRequest]",
    ) -> OperationResponse[
        "capo_bedrock_agentcore_control.types.create_dataset_response.CreateDatasetResponse"
    ]:
        import capo_bedrock_agentcore_control._operations.amazon_bedrock_agent_core_control.create_dataset

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

    def _redact_input(
        input_: "capo_bedrock_agentcore_control.types.create_dataset_request.CreateDatasetRequest",
    ) -> dict[str, Any]:
        import capo_bedrock_agentcore_control.types.create_dataset_request

        return capo_bedrock_agentcore_control.types.create_dataset_request.redact_sensitive(
            input_
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("CreateDataset", redact_input=_redact_input),
    )
    input_: capo_bedrock_agentcore_control.types.create_dataset_request.CreateDatasetRequest = {
        "dataset_name": dataset_name,
        "source": source,
        "schema_type": schema_type,
    }
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token
    if description is not None:
        input_["description"] = description
    if kms_key_arn is not None:
        input_["kms_key_arn"] = kms_key_arn
    if tags is not None:
        input_["tags"] = tags

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