list_language_models ¶

def list_language_models(
    self,
    *,
    config_overrides: Optional[TranscribeClientConfig] = None,
    status_equals: Optional[
        "capo_transcribe.types.model_status.ModelStatus"
    ] = None,
    name_contains: Optional["capo_transcribe.types.model_name.ModelName"] = None,
    next_token: Optional["capo_transcribe.types.next_token.NextToken"] = None,
    max_results: Optional["capo_transcribe.types.max_results.MaxResults"] = None,
) -> (
    "capo_transcribe.types.list_language_models_response.ListLanguageModelsResponse"
):
    """<p>Provides a list of custom language models that match the specified criteria. If no criteria are specified, all custom language models are returned.</p> <p>To get detailed information about a specific custom language model, use the operation.</p>

    Args:
        status_equals: <p>Returns only custom language models with the specified status. Language models are ordered by creation date, with the newest model first. If you do not include <code>StatusEquals</code>, all custom language models are returned.</p>
        name_contains: <p>Returns only the custom language models that contain the specified string. The search is not case sensitive.</p>
        next_token: <p>If your <code>ListLanguageModels</code> request returns more results than can be displayed, <code>NextToken</code> is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including <code>NextToken</code> with the value of the copied string. Repeat as needed to view all your results.</p>
        max_results: <p>The maximum number of custom language models to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.</p>

    Raises:
        capo_transcribe.errors.bad_request_exception.BadRequestException: <p>Your request didn't pass one or more validation tests. This can occur when the entity you're trying to delete doesn't exist or if it's in a non-terminal state (such as <code>IN PROGRESS</code>). See the exception message field for more information.</p>
        capo_transcribe.errors.internal_failure_exception.InternalFailureException: <p>There was an internal error. Check the error message, correct the issue, and try your request again.</p>
        capo_transcribe.errors.limit_exceeded_exception.LimitExceededException: <p>You've either sent too many requests or your input file is too long. Wait before retrying your request, or use a smaller file and try your request again.</p>
        capo_transcribe.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_transcribe.types.list_language_models_request.ListLanguageModelsRequest]",
    ) -> OperationResponse[
        "capo_transcribe.types.list_language_models_response.ListLanguageModelsResponse"
    ]:
        import capo_transcribe._operations.transcribe.list_language_models

        output, http_response = (
            capo_transcribe._operations.transcribe.list_language_models.list_language_models(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListLanguageModels")
    )
    input_: capo_transcribe.types.list_language_models_request.ListLanguageModelsRequest = {}
    if status_equals is not None:
        input_["status_equals"] = status_equals
    if name_contains is not None:
        input_["name_contains"] = name_contains
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results

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