list_recommended_intents ¶

def list_recommended_intents(
    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,
    next_token: Optional["capo_lex_models_v2.types.next_token.NextToken"] = None,
    max_results: Optional["capo_lex_models_v2.types.max_results.MaxResults"] = None,
) -> "capo_lex_models_v2.types.list_recommended_intents_response.ListRecommendedIntentsResponse":
    """<p>Gets a list of recommended intents provided by the bot recommendation that you can use in your bot. Intents in the response are ordered by relevance.</p>

    Args:
        bot_id: <p>The unique identifier of the bot associated with the recommended intents.</p>
        bot_version: <p>The version of the bot that contains the recommended intents.</p>
        locale_id: <p>The identifier of the language and locale of the recommended intents.</p>
        bot_recommendation_id: <p>The identifier of the bot recommendation that contains the recommended intents.</p>
        next_token: <p>If the response from the ListRecommendedIntents operation contains more results than specified in the maxResults parameter, a token is returned in the response. Use that token in the nextToken parameter to return the next page of results.</p>
        max_results: <p>The maximum number of bot recommendations to return in each page of results. If there are fewer results than the max page size, only the actual number of results are returned.</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.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>You have reached a quota for your bot. </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.list_recommended_intents_request.ListRecommendedIntentsRequest]",
    ) -> OperationResponse[
        "capo_lex_models_v2.types.list_recommended_intents_response.ListRecommendedIntentsResponse"
    ]:
        import capo_lex_models_v2._operations.lex_model_building_service_v2.list_recommended_intents

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListRecommendedIntents")
    )
    input_: capo_lex_models_v2.types.list_recommended_intents_request.ListRecommendedIntentsRequest = {
        "bot_id": bot_id,
        "bot_version": bot_version,
        "locale_id": locale_id,
        "bot_recommendation_id": bot_recommendation_id,
    }
    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