sdk/dingding-sdk/alibabacloud_dingtalk/ai_paa_s_1_0/client.py

2100 lines
89 KiB
Python

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