describe_bot_recommendation ¶

def describe_bot_recommendation(
    self,
    bot_id: "capo_lex_models_v2.types.id.Id",
    bot_version: "capo_lex_models_v2.types.draft_bot_version.DraftBotVersion",
    locale_id: "capo_lex_models_v2.types.locale_id.LocaleId",
    bot_recommendation_id: "capo_lex_models_v2.types.id.Id",
    *,
    config_overrides: Optional[LexModelsV2ClientConfig] = None,
) -> "capo_lex_models_v2.types.describe_bot_recommendation_response.DescribeBotRecommendationResponse":
    """<p>Provides metadata information about a bot recommendation. This information will enable you to get a description on the request inputs, to download associated transcripts after processing is complete, and to download intents and slot-types generated by the bot recommendation.</p>

    Args:
        bot_id: <p>The unique identifier of the bot associated with the bot recommendation.</p>
        bot_version: <p>The version of the bot associated with the bot recommendation.</p>
        locale_id: <p>The identifier of the language and locale of the bot recommendation to describe. The string must match one of the supported locales. For more information, see <a href="https://docs.aws.amazon.com/lexv2/latest/dg/how-languages.html">Supported languages</a>.</p>
        bot_recommendation_id: <p>The identifier of the bot recommendation to describe.</p>

    Raises:
        capo_lex_models_v2.errors.internal_server_exception.InternalServerException: <p>The service encountered an unexpected condition. Try your request again.</p>
        capo_lex_models_v2.errors.resource_not_found_exception.ResourceNotFoundException: <p>You asked to describe a resource that doesn't exist. Check the resource that you are requesting and try again.</p>
        capo_lex_models_v2.errors.throttling_exception.ThrottlingException: <p>Your request rate is too high. Reduce the frequency of requests.</p>
        capo_lex_models_v2.errors.validation_exception.ValidationException: <p>One of the input parameters in your request isn't valid. Check the parameters and try your request again.</p>
        capo_lex_models_v2.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_lex_models_v2.types.describe_bot_recommendation_request.DescribeBotRecommendationRequest]",
    ) -> OperationResponse[
        "capo_lex_models_v2.types.describe_bot_recommendation_response.DescribeBotRecommendationResponse"
    ]:
        import capo_lex_models_v2._operations.lex_model_building_service_v2.describe_bot_recommendation

        output, http_response = (
            capo_lex_models_v2._operations.lex_model_building_service_v2.describe_bot_recommendation.describe_bot_recommendation(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_lex_models_v2.types.describe_bot_recommendation_response.DescribeBotRecommendationResponse",
    ) -> dict[str, Any]:
        import capo_lex_models_v2.types.describe_bot_recommendation_response

        return capo_lex_models_v2.types.describe_bot_recommendation_response.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("DescribeBotRecommendation", redact_output=_redact_output),
    )
    input_: capo_lex_models_v2.types.describe_bot_recommendation_request.DescribeBotRecommendationRequest = {
        "bot_id": bot_id,
        "bot_version": bot_version,
        "locale_id": locale_id,
        "bot_recommendation_id": bot_recommendation_id,
    }

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