"""OpenAI 接口底层封装 目前使用的对话接口有： ChatCompletion - gpt-3.5-turbo 等模型 Completion - text-davinci-003 等模型 此模块封装此两个接口的请求实现，为上层提供统一的调用方式 """ import openai, logging, threading, asyncio import openai.error as aiE from pkg.openai.api.model import RequestBase from pkg.openai.api.completion import CompletionRequest from pkg.openai.api.chat_completion import ChatCompletionRequest COMPLETION_MODELS = { 'text-davinci-003', 'text-davinci-002', 'code-davinci-002', 'code-cushman-001', 'text-curie-001', 'text-babbage-001', 'text-ada-001', } CHAT_COMPLETION_MODELS = { 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', # 'gpt-3.5-turbo-0301', 'gpt-4', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-32k-0613' } EDIT_MODELS = { } 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) elif model_name in COMPLETION_MODELS: return CompletionRequest(model_name, messages, **args) raise ValueError("不支持模型[{}]，请检查配置文件".format(model_name))