list_foundation_models async ¶

async def list_foundation_models(
    self,
    *,
    config_overrides: Optional[AsyncBedrockClientConfig] = None,
    by_provider: Optional["capo_bedrock.types.provider.Provider"] = None,
    by_customization_type: Optional[
        "capo_bedrock.types.model_customization.ModelCustomization"
    ] = None,
    by_output_modality: Optional[
        "capo_bedrock.types.model_modality.ModelModality"
    ] = None,
    by_inference_type: Optional[
        "capo_bedrock.types.inference_type.InferenceType"
    ] = None,
) -> "capo_bedrock.types.list_foundation_models_response.ListFoundationModelsResponse":
    """<p>Lists Amazon Bedrock foundation models that you can use. You can filter the results with the request parameters. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/foundation-models.html">Foundation models</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>

    Args:
        by_provider: <p>Return models belonging to the model provider that you specify.</p>
        by_customization_type: <p>Return models that support the customization type that you specify. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html">Custom models</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>
        by_output_modality: <p>Return models that support the output modality that you specify.</p>
        by_inference_type: <p>Return models that support the inference type that you specify. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html">Provisioned Throughput</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>

    Raises:
        capo_bedrock.errors.access_denied_exception.AccessDeniedException: <p>The request is denied because of missing access permissions.</p>
        capo_bedrock.errors.internal_server_exception.InternalServerException: <p>An internal server error occurred. Retry your request.</p>
        capo_bedrock.errors.throttling_exception.ThrottlingException: <p>The number of requests exceeds the limit. Resubmit your request later.</p>
        capo_bedrock.errors.validation_exception.ValidationException: <p>Input validation failed. Check your request parameters and retry the request.</p>
        capo_bedrock.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_bedrock.types.list_foundation_models_request.ListFoundationModelsRequest]",
    ) -> AsyncOperationResponse[
        "capo_bedrock.types.list_foundation_models_response.ListFoundationModelsResponse"
    ]:
        import capo_bedrock._operations.amazon_bedrock_control_plane_service.list_foundation_models

        (
            output,
            http_response,
        ) = await capo_bedrock._operations.amazon_bedrock_control_plane_service.list_foundation_models.async_list_foundation_models(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListFoundationModels")
    )
    input_: capo_bedrock.types.list_foundation_models_request.ListFoundationModelsRequest = {}
    if by_provider is not None:
        input_["by_provider"] = by_provider
    if by_customization_type is not None:
        input_["by_customization_type"] = by_customization_type
    if by_output_modality is not None:
        input_["by_output_modality"] = by_output_modality
    if by_inference_type is not None:
        input_["by_inference_type"] = by_inference_type

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output