feat: 内容函数全局开关支持

pkg/openai/modelmgr.py

@@ -43,157 +43,6 @@ IMAGE_MODELS = {
 }
 
 
-# class ModelRequest:
-#     """模型接口请求父类"""
-
-#     can_chat = False
-#     runtime: threading.Thread = None
-#     ret = {}
-#     proxy: str = None
-#     request_ready = True
-#     error_info: str = "若在没有任何错误的情况下看到这句话，请带着配置文件上报Issues"
-
-#     def __init__(self, model_name, user_name, request_fun, http_proxy:str = None, time_out = None):
-#         self.model_name = model_name
-#         self.user_name = user_name
-#         self.request_fun = request_fun
-#         self.time_out = time_out
-#         if http_proxy != None:
-#             self.proxy = http_proxy
-#             openai.proxy = self.proxy
-#             self.request_ready = False
-
-#     async def __a_request__(self, **kwargs):
-#         """异步请求"""
-
-#         try:
-#             self.ret: dict = await self.request_fun(**kwargs)
-#             self.request_ready = True
-#         except aiE.APIConnectionError as e:
-#             self.error_info = "{}\n请检查网络连接或代理是否正常".format(e)
-#             raise ConnectionError(self.error_info)
-#         except ValueError as e:
-#             self.error_info = "{}\n该错误可能是由于http_proxy格式设置错误引起的"
-#         except Exception as e:
-#             self.error_info = "{}\n由于请求异常产生的未知错误，请查看日志".format(e)
-#             raise type(e)(self.error_info)
-
-#     def request(self, **kwargs):
-#         """向接口发起请求"""
-
-#         if self.proxy != None: #异步请求
-#             self.request_ready = False
-#             loop = asyncio.new_event_loop()
-#             self.runtime = threading.Thread(
-#                 target=loop.run_until_complete,
-#                 args=(self.__a_request__(**kwargs),)
-#             )
-#             self.runtime.start()
-#         else: #同步请求
-#             self.ret = self.request_fun(**kwargs)
-
-#     def __msg_handle__(self, msg):
-#         """将prompt dict转换成接口需要的格式"""
-#         return msg
-    
-#     def ret_handle(self):
-#         '''
-#         API消息返回处理函数
-#         若重写该方法，应检查异步线程状态，或在需要检查处super该方法
-#         '''
-#         if self.runtime != None and isinstance(self.runtime, threading.Thread):
-#             self.runtime.join(self.time_out)
-#         if self.request_ready:
-#             return
-#         raise Exception(self.error_info)
-
-#     def get_total_tokens(self):
-#         try:
-#             return self.ret['usage']['total_tokens']
-#         except:
-#             return 0
-
-#     def get_message(self):
-#         return self.message
-
-#     def get_response(self):
-#         return self.ret
-
-
-# class ChatCompletionModel(ModelRequest):
-#     """ChatCompletion接口的请求实现"""
-
-#     Chat_role = ['system', 'user', 'assistant']
-#     def __init__(self, model_name, user_name, http_proxy:str = None, **kwargs):
-#         if http_proxy == None:
-#             request_fun = openai.ChatCompletion.create
-#         else:
-#             request_fun = openai.ChatCompletion.acreate
-#         self.can_chat = True
-#         super().__init__(model_name, user_name, request_fun, http_proxy, **kwargs)
-
-#     def request(self, prompts, **kwargs):
-#         prompts = self.__msg_handle__(prompts)
-#         kwargs['messages'] = prompts
-#         super().request(**kwargs)
-#         self.ret_handle()
-
-#     def __msg_handle__(self, msgs):
-#         temp_msgs = []
-#         # 把msgs拷贝进temp_msgs
-#         for msg in msgs:
-#             temp_msgs.append(msg.copy())
-#         return temp_msgs
-
-#     def get_message(self):
-#         return self.ret["choices"][0]["message"]['content'] #需要时直接加载加快请求速度，降低内存消耗
-
-
-# class CompletionModel(ModelRequest):
-#     """Completion接口的请求实现"""
-
-#     def __init__(self, model_name, user_name, http_proxy:str = None, **kwargs):
-#         if http_proxy == None:
-#             request_fun = openai.Completion.create
-#         else:
-#             request_fun = openai.Completion.acreate
-#         super().__init__(model_name, user_name, request_fun, http_proxy, **kwargs)
-
-#     def request(self, prompts, **kwargs):
-#         prompts = self.__msg_handle__(prompts)
-#         kwargs['prompt'] = prompts
-#         super().request(**kwargs)
-#         self.ret_handle()
-
-#     def __msg_handle__(self, msgs):
-#         prompt = ''
-#         for msg in msgs:
-#             prompt = prompt + "{}: {}\n".format(msg['role'], msg['content'])
-#         # for msg in msgs:
-#         #     if msg['role'] == 'assistant':
-#         #         prompt = prompt + "{}\n".format(msg['content'])
-#         #     else:
-#         #         prompt = prompt + "{}:{}\n".format(msg['role'] , msg['content'])
-#         prompt = prompt + "assistant: "
-#         return prompt
-
-#     def get_message(self):
-#         return self.ret["choices"][0]["text"]
-
-
-# def create_openai_model_request(model_name: str, user_name: str = 'user', http_proxy:str = None) -> ModelRequest:
-#     """使用给定的模型名称创建模型请求对象"""
-#     if model_name in CHAT_COMPLETION_MODELS:
-#         model = ChatCompletionModel(model_name, user_name, http_proxy)
-#     elif model_name in COMPLETION_MODELS:
-#         model = CompletionModel(model_name, user_name, http_proxy)
-#     else :
-#         log = "找不到模型[{}]，请检查配置文件".format(model_name)
-#         logging.error(log)
-#         raise IndexError(log)
-#     logging.debug("使用接口[{}]创建模型请求[{}]".format(model.__class__.__name__, model_name))
-#     return model
-
 def select_request_cls(model_name: str, messages: list, args: dict) -> RequestBase:
     if model_name in CHAT_COMPLETION_MODELS:
         return ChatCompletionRequest(model_name, messages, **args)