get_prompt async ¶

async def get_prompt(
    self,
    prompt_identifier: "capo_bedrock_agent.types.prompt_identifier.PromptIdentifier",
    *,
    config_overrides: Optional[AsyncBedrockAgentClientConfig] = None,
    prompt_version: Optional["capo_bedrock_agent.types.version.Version"] = None,
    included_data: Optional[
        "capo_bedrock_agent.types.included_data.IncludedData"
    ] = None,
) -> "capo_bedrock_agent.types.get_prompt_response.GetPromptResponse":
    """<p>Retrieves information about the working draft (<code>DRAFT</code> version) of a prompt or a version of it, depending on whether you include the <code>promptVersion</code> field or not. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-management-manage.html#prompt-management-view.html">View information about prompts using Prompt management</a> and <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-management-deploy.html#prompt-management-versions-view.html">View information about a version of your prompt</a> in the Amazon Bedrock User Guide.</p>

    Args:
        prompt_identifier: <p>The unique identifier of the prompt.</p>
        prompt_version: <p>The version of the prompt about which you want to retrieve information. Omit this field to return information about the working draft of the prompt.</p>
        included_data: <p>Controls the scope of data returned. Set to <code>METADATA_ONLY</code> to return only resource metadata. Set to <code>ALL_DATA</code> or omit this field to return the full response.</p>

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

    async def _handler(
        req: "AsyncOperationRequest[capo_bedrock_agent.types.get_prompt_request.GetPromptRequest]",
    ) -> AsyncOperationResponse[
        "capo_bedrock_agent.types.get_prompt_response.GetPromptResponse"
    ]:
        import capo_bedrock_agent._operations.amazon_bedrock_agent_build_time_lambda.get_prompt

        (
            output,
            http_response,
        ) = await capo_bedrock_agent._operations.amazon_bedrock_agent_build_time_lambda.get_prompt.async_get_prompt(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_bedrock_agent.types.get_prompt_response.GetPromptResponse",
    ) -> dict[str, Any]:
        import capo_bedrock_agent.types.get_prompt_response

        return capo_bedrock_agent.types.get_prompt_response.redact_sensitive(output)

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("GetPrompt", redact_output=_redact_output),
    )
    input_: capo_bedrock_agent.types.get_prompt_request.GetPromptRequest = {
        "prompt_identifier": prompt_identifier
    }
    if prompt_version is not None:
        input_["prompt_version"] = prompt_version
    if included_data is not None:
        input_["included_data"] = included_data

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