# -*- coding: utf-8 -*- # This file is auto-generated, don't edit it. Thanks. from Tea.core import TeaCore from typing import Dict from alibabacloud_tea_openapi.client import Client as OpenApiClient from alibabacloud_tea_openapi import models as open_api_models from alibabacloud_gateway_dingtalk.client import Client as GatewayClientClient from alibabacloud_tea_util.client import Client as UtilClient from alibabacloud_dingtalk.ai_paa_s_1_0 import models as dingtalkai_paa_s__1__0_models from alibabacloud_tea_util import models as util_models from alibabacloud_openapi_util.client import Client as OpenApiUtilClient class Client(OpenApiClient): """ *\ """ def __init__( self, config: open_api_models.Config, ): super().__init__(config) gateway_client = GatewayClientClient() self._spi = gateway_client self._signature_algorithm = 'v2' self._endpoint_rule = '' if UtilClient.empty(self._endpoint): self._endpoint = 'api.dingtalk.com' def exclusive_model_complete_service_with_options( self, request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest, headers: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse: """ @summary 炼丹炉专属模型推理服务 @param request: ExclusiveModelCompleteServiceRequest @param headers: ExclusiveModelCompleteServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: ExclusiveModelCompleteServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.enable_search): body['enable_search'] = request.enable_search if not UtilClient.is_unset(request.max_tokens): body['max_tokens'] = request.max_tokens if not UtilClient.is_unset(request.messages): body['messages'] = request.messages if not UtilClient.is_unset(request.model): body['model'] = request.model if not UtilClient.is_unset(request.stream): body['stream'] = request.stream if not UtilClient.is_unset(request.temperature): body['temperature'] = request.temperature if not UtilClient.is_unset(request.top_p): body['top_p'] = request.top_p real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='ExclusiveModelCompleteService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/complete', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse(), self.execute(params, req, runtime) ) async def exclusive_model_complete_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest, headers: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse: """ @summary 炼丹炉专属模型推理服务 @param request: ExclusiveModelCompleteServiceRequest @param headers: ExclusiveModelCompleteServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: ExclusiveModelCompleteServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.enable_search): body['enable_search'] = request.enable_search if not UtilClient.is_unset(request.max_tokens): body['max_tokens'] = request.max_tokens if not UtilClient.is_unset(request.messages): body['messages'] = request.messages if not UtilClient.is_unset(request.model): body['model'] = request.model if not UtilClient.is_unset(request.stream): body['stream'] = request.stream if not UtilClient.is_unset(request.temperature): body['temperature'] = request.temperature if not UtilClient.is_unset(request.top_p): body['top_p'] = request.top_p real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='ExclusiveModelCompleteService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/complete', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse(), await self.execute_async(params, req, runtime) ) def exclusive_model_complete_service( self, request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest, ) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse: """ @summary 炼丹炉专属模型推理服务 @param request: ExclusiveModelCompleteServiceRequest @return: ExclusiveModelCompleteServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders() return self.exclusive_model_complete_service_with_options(request, headers, runtime) async def exclusive_model_complete_service_async( self, request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest, ) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse: """ @summary 炼丹炉专属模型推理服务 @param request: ExclusiveModelCompleteServiceRequest @return: ExclusiveModelCompleteServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders() return await self.exclusive_model_complete_service_with_options_async(request, headers, runtime) def execute_agent_with_options( self, request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest, headers: dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse: """ @summary 执行AI技能 @param request: ExecuteAgentRequest @param headers: ExecuteAgentHeaders @param runtime: runtime options for this request RuntimeOptions @return: ExecuteAgentResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.agent_code): body['agentCode'] = request.agent_code if not UtilClient.is_unset(request.inputs): body['inputs'] = request.inputs if not UtilClient.is_unset(request.scenario_code): body['scenarioCode'] = request.scenario_code if not UtilClient.is_unset(request.scenario_instance_id): body['scenarioInstanceId'] = request.scenario_instance_id if not UtilClient.is_unset(request.skill_id): body['skillId'] = request.skill_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='ExecuteAgent', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/agents/execute', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.ExecuteAgentResponse(), self.execute(params, req, runtime) ) async def execute_agent_with_options_async( self, request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest, headers: dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse: """ @summary 执行AI技能 @param request: ExecuteAgentRequest @param headers: ExecuteAgentHeaders @param runtime: runtime options for this request RuntimeOptions @return: ExecuteAgentResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.agent_code): body['agentCode'] = request.agent_code if not UtilClient.is_unset(request.inputs): body['inputs'] = request.inputs if not UtilClient.is_unset(request.scenario_code): body['scenarioCode'] = request.scenario_code if not UtilClient.is_unset(request.scenario_instance_id): body['scenarioInstanceId'] = request.scenario_instance_id if not UtilClient.is_unset(request.skill_id): body['skillId'] = request.skill_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='ExecuteAgent', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/agents/execute', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.ExecuteAgentResponse(), await self.execute_async(params, req, runtime) ) def execute_agent( self, request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest, ) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse: """ @summary 执行AI技能 @param request: ExecuteAgentRequest @return: ExecuteAgentResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders() return self.execute_agent_with_options(request, headers, runtime) async def execute_agent_async( self, request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest, ) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse: """ @summary 执行AI技能 @param request: ExecuteAgentRequest @return: ExecuteAgentResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders() return await self.execute_agent_with_options_async(request, headers, runtime) def liandan_text_image_get_with_options( self, request: dingtalkai_paa_s__1__0_models.LiandanTextImageGetRequest, headers: dingtalkai_paa_s__1__0_models.LiandanTextImageGetHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.LiandanTextImageGetResponse: """ @summary 炼丹炉文生图任务结果获取 @param request: LiandanTextImageGetRequest @param headers: LiandanTextImageGetHeaders @param runtime: runtime options for this request RuntimeOptions @return: LiandanTextImageGetResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.module): body['module'] = request.module if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='LiandanTextImageGet', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/textToImage/results/query', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.LiandanTextImageGetResponse(), self.execute(params, req, runtime) ) async def liandan_text_image_get_with_options_async( self, request: dingtalkai_paa_s__1__0_models.LiandanTextImageGetRequest, headers: dingtalkai_paa_s__1__0_models.LiandanTextImageGetHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.LiandanTextImageGetResponse: """ @summary 炼丹炉文生图任务结果获取 @param request: LiandanTextImageGetRequest @param headers: LiandanTextImageGetHeaders @param runtime: runtime options for this request RuntimeOptions @return: LiandanTextImageGetResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.module): body['module'] = request.module if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='LiandanTextImageGet', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/textToImage/results/query', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.LiandanTextImageGetResponse(), await self.execute_async(params, req, runtime) ) def liandan_text_image_get( self, request: dingtalkai_paa_s__1__0_models.LiandanTextImageGetRequest, ) -> dingtalkai_paa_s__1__0_models.LiandanTextImageGetResponse: """ @summary 炼丹炉文生图任务结果获取 @param request: LiandanTextImageGetRequest @return: LiandanTextImageGetResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.LiandanTextImageGetHeaders() return self.liandan_text_image_get_with_options(request, headers, runtime) async def liandan_text_image_get_async( self, request: dingtalkai_paa_s__1__0_models.LiandanTextImageGetRequest, ) -> dingtalkai_paa_s__1__0_models.LiandanTextImageGetResponse: """ @summary 炼丹炉文生图任务结果获取 @param request: LiandanTextImageGetRequest @return: LiandanTextImageGetResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.LiandanTextImageGetHeaders() return await self.liandan_text_image_get_with_options_async(request, headers, runtime) def liandanlu_exclusive_model_with_options( self, request: dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelRequest, headers: dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelResponse: """ @summary 炼丹炉专属模型接口 @param request: LiandanluExclusiveModelRequest @param headers: LiandanluExclusiveModelHeaders @param runtime: runtime options for this request RuntimeOptions @return: LiandanluExclusiveModelResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.model_id): body['modelId'] = request.model_id if not UtilClient.is_unset(request.module): body['module'] = request.module if not UtilClient.is_unset(request.prompt): body['prompt'] = request.prompt if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='LiandanluExclusiveModel', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/generate', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelResponse(), self.execute(params, req, runtime) ) async def liandanlu_exclusive_model_with_options_async( self, request: dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelRequest, headers: dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelResponse: """ @summary 炼丹炉专属模型接口 @param request: LiandanluExclusiveModelRequest @param headers: LiandanluExclusiveModelHeaders @param runtime: runtime options for this request RuntimeOptions @return: LiandanluExclusiveModelResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.model_id): body['modelId'] = request.model_id if not UtilClient.is_unset(request.module): body['module'] = request.module if not UtilClient.is_unset(request.prompt): body['prompt'] = request.prompt if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='LiandanluExclusiveModel', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/generate', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelResponse(), await self.execute_async(params, req, runtime) ) def liandanlu_exclusive_model( self, request: dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelRequest, ) -> dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelResponse: """ @summary 炼丹炉专属模型接口 @param request: LiandanluExclusiveModelRequest @return: LiandanluExclusiveModelResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelHeaders() return self.liandanlu_exclusive_model_with_options(request, headers, runtime) async def liandanlu_exclusive_model_async( self, request: dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelRequest, ) -> dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelResponse: """ @summary 炼丹炉专属模型接口 @param request: LiandanluExclusiveModelRequest @return: LiandanluExclusiveModelResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.LiandanluExclusiveModelHeaders() return await self.liandanlu_exclusive_model_with_options_async(request, headers, runtime) def liandanlu_text_to_image_model_with_options( self, request: dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelRequest, headers: dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelResponse: """ @summary 炼丹炉通过提示词生成图片 @param request: LiandanluTextToImageModelRequest @param headers: LiandanluTextToImageModelHeaders @param runtime: runtime options for this request RuntimeOptions @return: LiandanluTextToImageModelResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.module): body['module'] = request.module if not UtilClient.is_unset(request.number): body['number'] = request.number if not UtilClient.is_unset(request.parameters): body['parameters'] = request.parameters if not UtilClient.is_unset(request.prompt): body['prompt'] = request.prompt if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='LiandanluTextToImageModel', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/textToImage/generate', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelResponse(), self.execute(params, req, runtime) ) async def liandanlu_text_to_image_model_with_options_async( self, request: dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelRequest, headers: dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelResponse: """ @summary 炼丹炉通过提示词生成图片 @param request: LiandanluTextToImageModelRequest @param headers: LiandanluTextToImageModelHeaders @param runtime: runtime options for this request RuntimeOptions @return: LiandanluTextToImageModelResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.module): body['module'] = request.module if not UtilClient.is_unset(request.number): body['number'] = request.number if not UtilClient.is_unset(request.parameters): body['parameters'] = request.parameters if not UtilClient.is_unset(request.prompt): body['prompt'] = request.prompt if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='LiandanluTextToImageModel', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/textToImage/generate', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelResponse(), await self.execute_async(params, req, runtime) ) def liandanlu_text_to_image_model( self, request: dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelRequest, ) -> dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelResponse: """ @summary 炼丹炉通过提示词生成图片 @param request: LiandanluTextToImageModelRequest @return: LiandanluTextToImageModelResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelHeaders() return self.liandanlu_text_to_image_model_with_options(request, headers, runtime) async def liandanlu_text_to_image_model_async( self, request: dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelRequest, ) -> dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelResponse: """ @summary 炼丹炉通过提示词生成图片 @param request: LiandanluTextToImageModelRequest @return: LiandanluTextToImageModelResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.LiandanluTextToImageModelHeaders() return await self.liandanlu_text_to_image_model_with_options_async(request, headers, runtime) def n_lto_frame_service_with_options( self, request: dingtalkai_paa_s__1__0_models.NLToFrameServiceRequest, headers: dingtalkai_paa_s__1__0_models.NLToFrameServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.NLToFrameServiceResponse: """ @summary 通过配置的指令，连接用户和系统，训练大模型 @param request: NLToFrameServiceRequest @param headers: NLToFrameServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: NLToFrameServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.extension_str): body['extensionStr'] = request.extension_str if not UtilClient.is_unset(request.is_new_model): body['isNewModel'] = request.is_new_model if not UtilClient.is_unset(request.model_id): body['modelId'] = request.model_id if not UtilClient.is_unset(request.model_name): body['modelName'] = request.model_name if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='NLToFrameService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/nl2frame', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.NLToFrameServiceResponse(), self.execute(params, req, runtime) ) async def n_lto_frame_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.NLToFrameServiceRequest, headers: dingtalkai_paa_s__1__0_models.NLToFrameServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.NLToFrameServiceResponse: """ @summary 通过配置的指令，连接用户和系统，训练大模型 @param request: NLToFrameServiceRequest @param headers: NLToFrameServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: NLToFrameServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.extension_str): body['extensionStr'] = request.extension_str if not UtilClient.is_unset(request.is_new_model): body['isNewModel'] = request.is_new_model if not UtilClient.is_unset(request.model_id): body['modelId'] = request.model_id if not UtilClient.is_unset(request.model_name): body['modelName'] = request.model_name if not UtilClient.is_unset(request.user_id): body['userId'] = request.user_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='NLToFrameService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/ai/nl2frame', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.NLToFrameServiceResponse(), await self.execute_async(params, req, runtime) ) def n_lto_frame_service( self, request: dingtalkai_paa_s__1__0_models.NLToFrameServiceRequest, ) -> dingtalkai_paa_s__1__0_models.NLToFrameServiceResponse: """ @summary 通过配置的指令，连接用户和系统，训练大模型 @param request: NLToFrameServiceRequest @return: NLToFrameServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.NLToFrameServiceHeaders() return self.n_lto_frame_service_with_options(request, headers, runtime) async def n_lto_frame_service_async( self, request: dingtalkai_paa_s__1__0_models.NLToFrameServiceRequest, ) -> dingtalkai_paa_s__1__0_models.NLToFrameServiceResponse: """ @summary 通过配置的指令，连接用户和系统，训练大模型 @param request: NLToFrameServiceRequest @return: NLToFrameServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.NLToFrameServiceHeaders() return await self.n_lto_frame_service_with_options_async(request, headers, runtime) def query_baymax_skill_log_with_options( self, request: dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogRequest, headers: dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogResponse: """ @summary Baymax技能执行日志 @param request: QueryBaymaxSkillLogRequest @param headers: QueryBaymaxSkillLogHeaders @param runtime: runtime options for this request RuntimeOptions @return: QueryBaymaxSkillLogResponse """ UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.from_): query['from'] = request.from_ if not UtilClient.is_unset(request.log_level): query['logLevel'] = request.log_level if not UtilClient.is_unset(request.skill_execute_id): query['skillExecuteId'] = request.skill_execute_id if not UtilClient.is_unset(request.to): query['to'] = request.to real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='QueryBaymaxSkillLog', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/skills/logs', method='GET', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogResponse(), self.execute(params, req, runtime) ) async def query_baymax_skill_log_with_options_async( self, request: dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogRequest, headers: dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogResponse: """ @summary Baymax技能执行日志 @param request: QueryBaymaxSkillLogRequest @param headers: QueryBaymaxSkillLogHeaders @param runtime: runtime options for this request RuntimeOptions @return: QueryBaymaxSkillLogResponse """ UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.from_): query['from'] = request.from_ if not UtilClient.is_unset(request.log_level): query['logLevel'] = request.log_level if not UtilClient.is_unset(request.skill_execute_id): query['skillExecuteId'] = request.skill_execute_id if not UtilClient.is_unset(request.to): query['to'] = request.to real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='QueryBaymaxSkillLog', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/skills/logs', method='GET', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogResponse(), await self.execute_async(params, req, runtime) ) def query_baymax_skill_log( self, request: dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogRequest, ) -> dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogResponse: """ @summary Baymax技能执行日志 @param request: QueryBaymaxSkillLogRequest @return: QueryBaymaxSkillLogResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogHeaders() return self.query_baymax_skill_log_with_options(request, headers, runtime) async def query_baymax_skill_log_async( self, request: dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogRequest, ) -> dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogResponse: """ @summary Baymax技能执行日志 @param request: QueryBaymaxSkillLogRequest @return: QueryBaymaxSkillLogResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.QueryBaymaxSkillLogHeaders() return await self.query_baymax_skill_log_with_options_async(request, headers, runtime) def query_conversation_message_for_aiwith_options( self, cid: str, tmp_req: dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIRequest, headers: dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIResponse: """ @summary 查询会话消息并以大模型友好的协议返回 @param tmp_req: QueryConversationMessageForAIRequest @param headers: QueryConversationMessageForAIHeaders @param runtime: runtime options for this request RuntimeOptions @return: QueryConversationMessageForAIResponse """ UtilClient.validate_model(tmp_req) request = dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIShrinkRequest() OpenApiUtilClient.convert(tmp_req, request) if not UtilClient.is_unset(tmp_req.open_msg_ids): request.open_msg_ids_shrink = OpenApiUtilClient.array_to_string_with_specified_style(tmp_req.open_msg_ids, 'openMsgIds', 'json') query = {} if not UtilClient.is_unset(request.open_msg_ids_shrink): query['openMsgIds'] = request.open_msg_ids_shrink if not UtilClient.is_unset(request.recent_days): query['recentDays'] = request.recent_days if not UtilClient.is_unset(request.recent_hours): query['recentHours'] = request.recent_hours if not UtilClient.is_unset(request.recent_n): query['recentN'] = request.recent_n real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='QueryConversationMessageForAI', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/memory/im/{cid}/messages', method='GET', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIResponse(), self.execute(params, req, runtime) ) async def query_conversation_message_for_aiwith_options_async( self, cid: str, tmp_req: dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIRequest, headers: dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIResponse: """ @summary 查询会话消息并以大模型友好的协议返回 @param tmp_req: QueryConversationMessageForAIRequest @param headers: QueryConversationMessageForAIHeaders @param runtime: runtime options for this request RuntimeOptions @return: QueryConversationMessageForAIResponse """ UtilClient.validate_model(tmp_req) request = dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIShrinkRequest() OpenApiUtilClient.convert(tmp_req, request) if not UtilClient.is_unset(tmp_req.open_msg_ids): request.open_msg_ids_shrink = OpenApiUtilClient.array_to_string_with_specified_style(tmp_req.open_msg_ids, 'openMsgIds', 'json') query = {} if not UtilClient.is_unset(request.open_msg_ids_shrink): query['openMsgIds'] = request.open_msg_ids_shrink if not UtilClient.is_unset(request.recent_days): query['recentDays'] = request.recent_days if not UtilClient.is_unset(request.recent_hours): query['recentHours'] = request.recent_hours if not UtilClient.is_unset(request.recent_n): query['recentN'] = request.recent_n real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='QueryConversationMessageForAI', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/memory/im/{cid}/messages', method='GET', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIResponse(), await self.execute_async(params, req, runtime) ) def query_conversation_message_for_ai( self, cid: str, request: dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIRequest, ) -> dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIResponse: """ @summary 查询会话消息并以大模型友好的协议返回 @param request: QueryConversationMessageForAIRequest @return: QueryConversationMessageForAIResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIHeaders() return self.query_conversation_message_for_aiwith_options(cid, request, headers, runtime) async def query_conversation_message_for_ai_async( self, cid: str, request: dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIRequest, ) -> dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIResponse: """ @summary 查询会话消息并以大模型友好的协议返回 @param request: QueryConversationMessageForAIRequest @return: QueryConversationMessageForAIResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.QueryConversationMessageForAIHeaders() return await self.query_conversation_message_for_aiwith_options_async(cid, request, headers, runtime) def query_memory_learning_task_with_options( self, request: dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskRequest, headers: dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskResponse: """ @summary 查询记忆学习进度 @param request: QueryMemoryLearningTaskRequest @param headers: QueryMemoryLearningTaskHeaders @param runtime: runtime options for this request RuntimeOptions @return: QueryMemoryLearningTaskResponse """ UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.agent_code): query['agentCode'] = request.agent_code if not UtilClient.is_unset(request.learning_code): query['learningCode'] = request.learning_code real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='QueryMemoryLearningTask', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/memory/learningTask/get', method='GET', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskResponse(), self.execute(params, req, runtime) ) async def query_memory_learning_task_with_options_async( self, request: dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskRequest, headers: dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskResponse: """ @summary 查询记忆学习进度 @param request: QueryMemoryLearningTaskRequest @param headers: QueryMemoryLearningTaskHeaders @param runtime: runtime options for this request RuntimeOptions @return: QueryMemoryLearningTaskResponse """ UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.agent_code): query['agentCode'] = request.agent_code if not UtilClient.is_unset(request.learning_code): query['learningCode'] = request.learning_code real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='QueryMemoryLearningTask', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/memory/learningTask/get', method='GET', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskResponse(), await self.execute_async(params, req, runtime) ) def query_memory_learning_task( self, request: dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskRequest, ) -> dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskResponse: """ @summary 查询记忆学习进度 @param request: QueryMemoryLearningTaskRequest @return: QueryMemoryLearningTaskResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskHeaders() return self.query_memory_learning_task_with_options(request, headers, runtime) async def query_memory_learning_task_async( self, request: dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskRequest, ) -> dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskResponse: """ @summary 查询记忆学习进度 @param request: QueryMemoryLearningTaskRequest @return: QueryMemoryLearningTaskResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.QueryMemoryLearningTaskHeaders() return await self.query_memory_learning_task_with_options_async(request, headers, runtime) def smart_formula_result_service_with_options( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceResponse: """ @summary 中信金属智能配料任务结果 @param request: SmartFormulaResultServiceRequest @param headers: map @param runtime: runtime options for this request RuntimeOptions @return: SmartFormulaResultServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartFormulaResultService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartFormulas/results/query', method='POST', auth_type='Anonymous', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceResponse(), self.execute(params, req, runtime) ) async def smart_formula_result_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceResponse: """ @summary 中信金属智能配料任务结果 @param request: SmartFormulaResultServiceRequest @param headers: map @param runtime: runtime options for this request RuntimeOptions @return: SmartFormulaResultServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartFormulaResultService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartFormulas/results/query', method='POST', auth_type='Anonymous', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceResponse(), await self.execute_async(params, req, runtime) ) def smart_formula_result_service( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceResponse: """ @summary 中信金属智能配料任务结果 @param request: SmartFormulaResultServiceRequest @return: SmartFormulaResultServiceResponse """ runtime = util_models.RuntimeOptions() headers = {} return self.smart_formula_result_service_with_options(request, headers, runtime) async def smart_formula_result_service_async( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaResultServiceResponse: """ @summary 中信金属智能配料任务结果 @param request: SmartFormulaResultServiceRequest @return: SmartFormulaResultServiceResponse """ runtime = util_models.RuntimeOptions() headers = {} return await self.smart_formula_result_service_with_options_async(request, headers, runtime) def smart_formula_trigger_service_with_options( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceResponse: """ @summary 中信金属智能配料任务触发 @param request: SmartFormulaTriggerServiceRequest @param headers: map @param runtime: runtime options for this request RuntimeOptions @return: SmartFormulaTriggerServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartFormulaTriggerService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartFormulas/trigger', method='POST', auth_type='Anonymous', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceResponse(), self.execute(params, req, runtime) ) async def smart_formula_trigger_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceResponse: """ @summary 中信金属智能配料任务触发 @param request: SmartFormulaTriggerServiceRequest @param headers: map @param runtime: runtime options for this request RuntimeOptions @return: SmartFormulaTriggerServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartFormulaTriggerService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartFormulas/trigger', method='POST', auth_type='Anonymous', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceResponse(), await self.execute_async(params, req, runtime) ) def smart_formula_trigger_service( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceResponse: """ @summary 中信金属智能配料任务触发 @param request: SmartFormulaTriggerServiceRequest @return: SmartFormulaTriggerServiceResponse """ runtime = util_models.RuntimeOptions() headers = {} return self.smart_formula_trigger_service_with_options(request, headers, runtime) async def smart_formula_trigger_service_async( self, request: dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartFormulaTriggerServiceResponse: """ @summary 中信金属智能配料任务触发 @param request: SmartFormulaTriggerServiceRequest @return: SmartFormulaTriggerServiceResponse """ runtime = util_models.RuntimeOptions() headers = {} return await self.smart_formula_trigger_service_with_options_async(request, headers, runtime) def smart_quote_batch_query_result_service_with_options( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceResponse: """ @summary 批量查询智能报价结果 @param request: SmartQuoteBatchQueryResultServiceRequest @param headers: SmartQuoteBatchQueryResultServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteBatchQueryResultServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteBatchQueryResultService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/results/batchQuery', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceResponse(), self.execute(params, req, runtime) ) async def smart_quote_batch_query_result_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceResponse: """ @summary 批量查询智能报价结果 @param request: SmartQuoteBatchQueryResultServiceRequest @param headers: SmartQuoteBatchQueryResultServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteBatchQueryResultServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteBatchQueryResultService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/results/batchQuery', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceResponse(), await self.execute_async(params, req, runtime) ) def smart_quote_batch_query_result_service( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceResponse: """ @summary 批量查询智能报价结果 @param request: SmartQuoteBatchQueryResultServiceRequest @return: SmartQuoteBatchQueryResultServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceHeaders() return self.smart_quote_batch_query_result_service_with_options(request, headers, runtime) async def smart_quote_batch_query_result_service_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceResponse: """ @summary 批量查询智能报价结果 @param request: SmartQuoteBatchQueryResultServiceRequest @return: SmartQuoteBatchQueryResultServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryResultServiceHeaders() return await self.smart_quote_batch_query_result_service_with_options_async(request, headers, runtime) def smart_quote_batch_query_service_with_options( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceResponse: """ @summary 批量查询智能报价 @param request: SmartQuoteBatchQueryServiceRequest @param headers: SmartQuoteBatchQueryServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteBatchQueryServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteBatchQueryService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/batchQuery', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceResponse(), self.execute(params, req, runtime) ) async def smart_quote_batch_query_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceResponse: """ @summary 批量查询智能报价 @param request: SmartQuoteBatchQueryServiceRequest @param headers: SmartQuoteBatchQueryServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteBatchQueryServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteBatchQueryService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/batchQuery', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceResponse(), await self.execute_async(params, req, runtime) ) def smart_quote_batch_query_service( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceResponse: """ @summary 批量查询智能报价 @param request: SmartQuoteBatchQueryServiceRequest @return: SmartQuoteBatchQueryServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceHeaders() return self.smart_quote_batch_query_service_with_options(request, headers, runtime) async def smart_quote_batch_query_service_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceResponse: """ @summary 批量查询智能报价 @param request: SmartQuoteBatchQueryServiceRequest @return: SmartQuoteBatchQueryServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteBatchQueryServiceHeaders() return await self.smart_quote_batch_query_service_with_options_async(request, headers, runtime) def smart_quote_data_service_with_options( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceResponse: """ @summary 添加智能报价数据 @param request: SmartQuoteDataServiceRequest @param headers: SmartQuoteDataServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteDataServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteDataService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/datas', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceResponse(), self.execute(params, req, runtime) ) async def smart_quote_data_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceResponse: """ @summary 添加智能报价数据 @param request: SmartQuoteDataServiceRequest @param headers: SmartQuoteDataServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteDataServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteDataService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/datas', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceResponse(), await self.execute_async(params, req, runtime) ) def smart_quote_data_service( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceResponse: """ @summary 添加智能报价数据 @param request: SmartQuoteDataServiceRequest @return: SmartQuoteDataServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceHeaders() return self.smart_quote_data_service_with_options(request, headers, runtime) async def smart_quote_data_service_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceResponse: """ @summary 添加智能报价数据 @param request: SmartQuoteDataServiceRequest @return: SmartQuoteDataServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteDataServiceHeaders() return await self.smart_quote_data_service_with_options_async(request, headers, runtime) def smart_quote_query_result_service_with_options( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceResponse: """ @summary 查询智能报价结果 @param request: SmartQuoteQueryResultServiceRequest @param headers: SmartQuoteQueryResultServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteQueryResultServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteQueryResultService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/results/query', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceResponse(), self.execute(params, req, runtime) ) async def smart_quote_query_result_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceResponse: """ @summary 查询智能报价结果 @param request: SmartQuoteQueryResultServiceRequest @param headers: SmartQuoteQueryResultServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteQueryResultServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.task_id): body['taskId'] = request.task_id real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteQueryResultService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/results/query', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceResponse(), await self.execute_async(params, req, runtime) ) def smart_quote_query_result_service( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceResponse: """ @summary 查询智能报价结果 @param request: SmartQuoteQueryResultServiceRequest @return: SmartQuoteQueryResultServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceHeaders() return self.smart_quote_query_result_service_with_options(request, headers, runtime) async def smart_quote_query_result_service_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceResponse: """ @summary 查询智能报价结果 @param request: SmartQuoteQueryResultServiceRequest @return: SmartQuoteQueryResultServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteQueryResultServiceHeaders() return await self.smart_quote_query_result_service_with_options_async(request, headers, runtime) def smart_quote_query_service_with_options( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceResponse: """ @summary 查询智能报价 @param request: SmartQuoteQueryServiceRequest @param headers: SmartQuoteQueryServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteQueryServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteQueryService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/triggerQuery', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceResponse(), self.execute(params, req, runtime) ) async def smart_quote_query_service_with_options_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceRequest, headers: dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceResponse: """ @summary 查询智能报价 @param request: SmartQuoteQueryServiceRequest @param headers: SmartQuoteQueryServiceHeaders @param runtime: runtime options for this request RuntimeOptions @return: SmartQuoteQueryServiceResponse """ UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.request): body['request'] = request.request real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='SmartQuoteQueryService', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/nl2x/smartQuotations/triggerQuery', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceResponse(), await self.execute_async(params, req, runtime) ) def smart_quote_query_service( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceResponse: """ @summary 查询智能报价 @param request: SmartQuoteQueryServiceRequest @return: SmartQuoteQueryServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceHeaders() return self.smart_quote_query_service_with_options(request, headers, runtime) async def smart_quote_query_service_async( self, request: dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceRequest, ) -> dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceResponse: """ @summary 查询智能报价 @param request: SmartQuoteQueryServiceRequest @return: SmartQuoteQueryServiceResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SmartQuoteQueryServiceHeaders() return await self.smart_quote_query_service_with_options_async(request, headers, runtime) def submit_memory_learning_task_with_options( self, tmp_req: dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskRequest, headers: dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskResponse: """ @summary 提交记忆学习任务 @param tmp_req: SubmitMemoryLearningTaskRequest @param headers: SubmitMemoryLearningTaskHeaders @param runtime: runtime options for this request RuntimeOptions @return: SubmitMemoryLearningTaskResponse """ UtilClient.validate_model(tmp_req) request = dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskShrinkRequest() OpenApiUtilClient.convert(tmp_req, request) if not UtilClient.is_unset(tmp_req.content): request.content_shrink = OpenApiUtilClient.array_to_string_with_specified_style(tmp_req.content, 'content', 'json') query = {} if not UtilClient.is_unset(request.agent_code): query['agentCode'] = request.agent_code if not UtilClient.is_unset(request.content_shrink): query['content'] = request.content_shrink if not UtilClient.is_unset(request.learning_mode): query['learningMode'] = request.learning_mode if not UtilClient.is_unset(request.memory_key): query['memoryKey'] = request.memory_key real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='SubmitMemoryLearningTask', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/memory/learningTask/put', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskResponse(), self.execute(params, req, runtime) ) async def submit_memory_learning_task_with_options_async( self, tmp_req: dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskRequest, headers: dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskHeaders, runtime: util_models.RuntimeOptions, ) -> dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskResponse: """ @summary 提交记忆学习任务 @param tmp_req: SubmitMemoryLearningTaskRequest @param headers: SubmitMemoryLearningTaskHeaders @param runtime: runtime options for this request RuntimeOptions @return: SubmitMemoryLearningTaskResponse """ UtilClient.validate_model(tmp_req) request = dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskShrinkRequest() OpenApiUtilClient.convert(tmp_req, request) if not UtilClient.is_unset(tmp_req.content): request.content_shrink = OpenApiUtilClient.array_to_string_with_specified_style(tmp_req.content, 'content', 'json') query = {} if not UtilClient.is_unset(request.agent_code): query['agentCode'] = request.agent_code if not UtilClient.is_unset(request.content_shrink): query['content'] = request.content_shrink if not UtilClient.is_unset(request.learning_mode): query['learningMode'] = request.learning_mode if not UtilClient.is_unset(request.memory_key): query['memoryKey'] = request.memory_key real_headers = {} if not UtilClient.is_unset(headers.common_headers): real_headers = headers.common_headers if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token): real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token) req = open_api_models.OpenApiRequest( headers=real_headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='SubmitMemoryLearningTask', version='aiPaaS_1.0', protocol='HTTP', pathname=f'/v1.0/aiPaaS/me/memory/learningTask/put', method='POST', auth_type='AK', style='ROA', req_body_type='none', body_type='json' ) return TeaCore.from_map( dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskResponse(), await self.execute_async(params, req, runtime) ) def submit_memory_learning_task( self, request: dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskRequest, ) -> dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskResponse: """ @summary 提交记忆学习任务 @param request: SubmitMemoryLearningTaskRequest @return: SubmitMemoryLearningTaskResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskHeaders() return self.submit_memory_learning_task_with_options(request, headers, runtime) async def submit_memory_learning_task_async( self, request: dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskRequest, ) -> dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskResponse: """ @summary 提交记忆学习任务 @param request: SubmitMemoryLearningTaskRequest @return: SubmitMemoryLearningTaskResponse """ runtime = util_models.RuntimeOptions() headers = dingtalkai_paa_s__1__0_models.SubmitMemoryLearningTaskHeaders() return await self.submit_memory_learning_task_with_options_async(request, headers, runtime)