2100 lines
89 KiB
Python
2100 lines
89 KiB
Python
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# -*- coding: utf-8 -*-
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# This file is auto-generated, don't edit it. Thanks.
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from Tea.core import TeaCore
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from typing import Dict
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from alibabacloud_tea_openapi.client import Client as OpenApiClient
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from alibabacloud_tea_openapi import models as open_api_models
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from alibabacloud_gateway_dingtalk.client import Client as GatewayClientClient
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from alibabacloud_tea_util.client import Client as UtilClient
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from alibabacloud_dingtalk.ai_paa_s_1_0 import models as dingtalkai_paa_s__1__0_models
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from alibabacloud_tea_util import models as util_models
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from alibabacloud_openapi_util.client import Client as OpenApiUtilClient
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class Client(OpenApiClient):
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"""
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*\
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"""
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def __init__(
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self,
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config: open_api_models.Config,
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):
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super().__init__(config)
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gateway_client = GatewayClientClient()
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self._spi = gateway_client
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self._signature_algorithm = 'v2'
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self._endpoint_rule = ''
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if UtilClient.empty(self._endpoint):
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self._endpoint = 'api.dingtalk.com'
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def exclusive_model_complete_service_with_options(
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self,
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request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest,
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headers: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders,
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runtime: util_models.RuntimeOptions,
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) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse:
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"""
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@summary 炼丹炉专属模型推理服务
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@param request: ExclusiveModelCompleteServiceRequest
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@param headers: ExclusiveModelCompleteServiceHeaders
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@param runtime: runtime options for this request RuntimeOptions
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@return: ExclusiveModelCompleteServiceResponse
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"""
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UtilClient.validate_model(request)
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body = {}
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if not UtilClient.is_unset(request.enable_search):
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body['enable_search'] = request.enable_search
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if not UtilClient.is_unset(request.max_tokens):
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body['max_tokens'] = request.max_tokens
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if not UtilClient.is_unset(request.messages):
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body['messages'] = request.messages
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if not UtilClient.is_unset(request.model):
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body['model'] = request.model
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if not UtilClient.is_unset(request.stream):
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body['stream'] = request.stream
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if not UtilClient.is_unset(request.temperature):
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body['temperature'] = request.temperature
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if not UtilClient.is_unset(request.top_p):
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body['top_p'] = request.top_p
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real_headers = {}
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if not UtilClient.is_unset(headers.common_headers):
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real_headers = headers.common_headers
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if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token):
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real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token)
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req = open_api_models.OpenApiRequest(
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headers=real_headers,
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body=OpenApiUtilClient.parse_to_map(body)
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)
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params = open_api_models.Params(
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action='ExclusiveModelCompleteService',
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version='aiPaaS_1.0',
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protocol='HTTP',
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pathname=f'/v1.0/aiPaaS/ai/complete',
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method='POST',
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auth_type='AK',
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style='ROA',
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req_body_type='none',
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body_type='json'
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)
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return TeaCore.from_map(
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dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse(),
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self.execute(params, req, runtime)
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)
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async def exclusive_model_complete_service_with_options_async(
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self,
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request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest,
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headers: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders,
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runtime: util_models.RuntimeOptions,
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) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse:
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"""
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@summary 炼丹炉专属模型推理服务
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@param request: ExclusiveModelCompleteServiceRequest
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@param headers: ExclusiveModelCompleteServiceHeaders
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@param runtime: runtime options for this request RuntimeOptions
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@return: ExclusiveModelCompleteServiceResponse
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"""
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UtilClient.validate_model(request)
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body = {}
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if not UtilClient.is_unset(request.enable_search):
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body['enable_search'] = request.enable_search
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if not UtilClient.is_unset(request.max_tokens):
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body['max_tokens'] = request.max_tokens
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if not UtilClient.is_unset(request.messages):
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body['messages'] = request.messages
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if not UtilClient.is_unset(request.model):
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body['model'] = request.model
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if not UtilClient.is_unset(request.stream):
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body['stream'] = request.stream
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if not UtilClient.is_unset(request.temperature):
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body['temperature'] = request.temperature
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if not UtilClient.is_unset(request.top_p):
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body['top_p'] = request.top_p
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real_headers = {}
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if not UtilClient.is_unset(headers.common_headers):
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real_headers = headers.common_headers
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if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token):
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real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token)
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req = open_api_models.OpenApiRequest(
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headers=real_headers,
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body=OpenApiUtilClient.parse_to_map(body)
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)
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params = open_api_models.Params(
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action='ExclusiveModelCompleteService',
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version='aiPaaS_1.0',
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protocol='HTTP',
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pathname=f'/v1.0/aiPaaS/ai/complete',
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method='POST',
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auth_type='AK',
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style='ROA',
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req_body_type='none',
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body_type='json'
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)
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return TeaCore.from_map(
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dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse(),
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await self.execute_async(params, req, runtime)
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)
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def exclusive_model_complete_service(
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self,
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request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest,
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) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse:
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"""
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@summary 炼丹炉专属模型推理服务
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@param request: ExclusiveModelCompleteServiceRequest
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@return: ExclusiveModelCompleteServiceResponse
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"""
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runtime = util_models.RuntimeOptions()
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headers = dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders()
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return self.exclusive_model_complete_service_with_options(request, headers, runtime)
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async def exclusive_model_complete_service_async(
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self,
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request: dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceRequest,
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) -> dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceResponse:
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"""
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@summary 炼丹炉专属模型推理服务
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@param request: ExclusiveModelCompleteServiceRequest
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@return: ExclusiveModelCompleteServiceResponse
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"""
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runtime = util_models.RuntimeOptions()
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headers = dingtalkai_paa_s__1__0_models.ExclusiveModelCompleteServiceHeaders()
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return await self.exclusive_model_complete_service_with_options_async(request, headers, runtime)
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def execute_agent_with_options(
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self,
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request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest,
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headers: dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders,
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runtime: util_models.RuntimeOptions,
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) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse:
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"""
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@summary 执行AI技能
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@param request: ExecuteAgentRequest
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@param headers: ExecuteAgentHeaders
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@param runtime: runtime options for this request RuntimeOptions
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@return: ExecuteAgentResponse
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"""
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UtilClient.validate_model(request)
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body = {}
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if not UtilClient.is_unset(request.agent_code):
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body['agentCode'] = request.agent_code
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if not UtilClient.is_unset(request.inputs):
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body['inputs'] = request.inputs
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if not UtilClient.is_unset(request.scenario_code):
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body['scenarioCode'] = request.scenario_code
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if not UtilClient.is_unset(request.scenario_instance_id):
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body['scenarioInstanceId'] = request.scenario_instance_id
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if not UtilClient.is_unset(request.skill_id):
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body['skillId'] = request.skill_id
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real_headers = {}
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if not UtilClient.is_unset(headers.common_headers):
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real_headers = headers.common_headers
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if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token):
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real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token)
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req = open_api_models.OpenApiRequest(
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headers=real_headers,
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body=OpenApiUtilClient.parse_to_map(body)
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)
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params = open_api_models.Params(
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action='ExecuteAgent',
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version='aiPaaS_1.0',
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protocol='HTTP',
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pathname=f'/v1.0/aiPaaS/me/agents/execute',
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method='POST',
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auth_type='AK',
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style='ROA',
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req_body_type='none',
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body_type='json'
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)
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return TeaCore.from_map(
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dingtalkai_paa_s__1__0_models.ExecuteAgentResponse(),
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self.execute(params, req, runtime)
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)
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async def execute_agent_with_options_async(
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self,
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request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest,
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headers: dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders,
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runtime: util_models.RuntimeOptions,
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) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse:
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"""
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@summary 执行AI技能
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@param request: ExecuteAgentRequest
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@param headers: ExecuteAgentHeaders
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@param runtime: runtime options for this request RuntimeOptions
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@return: ExecuteAgentResponse
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"""
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UtilClient.validate_model(request)
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body = {}
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if not UtilClient.is_unset(request.agent_code):
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body['agentCode'] = request.agent_code
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if not UtilClient.is_unset(request.inputs):
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body['inputs'] = request.inputs
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if not UtilClient.is_unset(request.scenario_code):
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body['scenarioCode'] = request.scenario_code
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if not UtilClient.is_unset(request.scenario_instance_id):
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body['scenarioInstanceId'] = request.scenario_instance_id
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if not UtilClient.is_unset(request.skill_id):
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body['skillId'] = request.skill_id
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real_headers = {}
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if not UtilClient.is_unset(headers.common_headers):
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real_headers = headers.common_headers
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if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token):
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real_headers['x-acs-dingtalk-access-token'] = UtilClient.to_jsonstring(headers.x_acs_dingtalk_access_token)
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req = open_api_models.OpenApiRequest(
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headers=real_headers,
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body=OpenApiUtilClient.parse_to_map(body)
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)
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params = open_api_models.Params(
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action='ExecuteAgent',
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version='aiPaaS_1.0',
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protocol='HTTP',
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pathname=f'/v1.0/aiPaaS/me/agents/execute',
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method='POST',
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auth_type='AK',
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style='ROA',
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req_body_type='none',
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body_type='json'
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)
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return TeaCore.from_map(
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dingtalkai_paa_s__1__0_models.ExecuteAgentResponse(),
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await self.execute_async(params, req, runtime)
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)
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def execute_agent(
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self,
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request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest,
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) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse:
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"""
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@summary 执行AI技能
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@param request: ExecuteAgentRequest
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@return: ExecuteAgentResponse
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"""
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runtime = util_models.RuntimeOptions()
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headers = dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders()
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return self.execute_agent_with_options(request, headers, runtime)
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async def execute_agent_async(
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self,
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request: dingtalkai_paa_s__1__0_models.ExecuteAgentRequest,
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) -> dingtalkai_paa_s__1__0_models.ExecuteAgentResponse:
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"""
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|||
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|
@summary 执行AI技能
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@param request: ExecuteAgentRequest
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@return: ExecuteAgentResponse
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"""
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runtime = util_models.RuntimeOptions()
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headers = dingtalkai_paa_s__1__0_models.ExecuteAgentHeaders()
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return await self.execute_agent_with_options_async(request, headers, runtime)
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def liandan_text_image_get_with_options(
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self,
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request: dingtalkai_paa_s__1__0_models.LiandanTextImageGetRequest,
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headers: dingtalkai_paa_s__1__0_models.LiandanTextImageGetHeaders,
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runtime: util_models.RuntimeOptions,
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) -> dingtalkai_paa_s__1__0_models.LiandanTextImageGetResponse:
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"""
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@summary 炼丹炉文生图任务结果获取
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@param request: LiandanTextImageGetRequest
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@param headers: LiandanTextImageGetHeaders
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@param runtime: runtime options for this request RuntimeOptions
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@return: LiandanTextImageGetResponse
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"""
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UtilClient.validate_model(request)
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body = {}
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if not UtilClient.is_unset(request.module):
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body['module'] = request.module
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if not UtilClient.is_unset(request.task_id):
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body['taskId'] = request.task_id
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if not UtilClient.is_unset(request.user_id):
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body['userId'] = request.user_id
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real_headers = {}
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|||
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if not UtilClient.is_unset(headers.common_headers):
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|||
|
|
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)
|