# encoding:utf-8 from bot.bot import Bot from bot.chatgpt.chat_gpt_session import ChatGPTSession from bot.openai.open_ai_image import OpenAIImage from bot.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from config import conf, load_config from common.log import logger from common.token_bucket import TokenBucket import openai import openai.error import time # OpenAI对话模型API (可用) class ChatGPTBot(Bot,OpenAIImage): def __init__(self): super().__init__() # set the default api_key openai.api_key = conf().get('open_ai_api_key') if conf().get('open_ai_api_base'): openai.api_base = conf().get('open_ai_api_base') proxy = conf().get('proxy') if proxy: openai.proxy = proxy if conf().get('rate_limit_chatgpt'): self.tb4chatgpt = TokenBucket(conf().get('rate_limit_chatgpt', 20)) self.sessions = SessionManager(ChatGPTSession, model= conf().get("model") or "gpt-3.5-turbo") def reply(self, query, context=None): # acquire reply content if context.type == ContextType.TEXT: logger.info("[CHATGPT] query={}".format(query)) session_id = context['session_id'] reply = None clear_memory_commands = conf().get('clear_memory_commands', ['#清除记忆']) if query in clear_memory_commands: self.sessions.clear_session(session_id) reply = Reply(ReplyType.INFO, '记忆已清除') elif query == '#清除所有': self.sessions.clear_all_session() reply = Reply(ReplyType.INFO, '所有人记忆已清除') elif query == '#更新配置': load_config() reply = Reply(ReplyType.INFO, '配置已更新') if reply: return reply session = self.sessions.session_query(query, session_id) logger.debug("[CHATGPT] session query={}".format(session.messages)) api_key = context.get('openai_api_key') # if context.get('stream'): # # reply in stream # return self.reply_text_stream(query, new_query, session_id) reply_content = self.reply_text(session, session_id, api_key, 0) logger.debug("[CHATGPT] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(session.messages, session_id, reply_content["content"], reply_content["completion_tokens"])) if reply_content['completion_tokens'] == 0 and len(reply_content['content']) > 0: reply = Reply(ReplyType.ERROR, reply_content['content']) elif reply_content["completion_tokens"] > 0: self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"]) reply = Reply(ReplyType.TEXT, reply_content["content"]) else: reply = Reply(ReplyType.ERROR, reply_content['content']) logger.debug("[CHATGPT] reply {} used 0 tokens.".format(reply_content)) return reply elif context.type == ContextType.IMAGE_CREATE: ok, retstring = self.create_img(query, 0) reply = None if ok: reply = Reply(ReplyType.IMAGE_URL, retstring) else: reply = Reply(ReplyType.ERROR, retstring) return reply else: reply = Reply(ReplyType.ERROR, 'Bot不支持处理{}类型的消息'.format(context.type)) return reply def compose_args(self): return { "model": conf().get("model") or "gpt-3.5-turbo", # 对话模型的名称 "temperature":conf().get('temperature', 0.9), # 值在[0,1]之间，越大表示回复越具有不确定性 # "max_tokens":4096, # 回复最大的字符数 "top_p":1, "frequency_penalty":conf().get('frequency_penalty', 0.0), # [-2,2]之间，该值越大则更倾向于产生不同的内容 "presence_penalty":conf().get('presence_penalty', 0.0), # [-2,2]之间，该值越大则更倾向于产生不同的内容 "request_timeout": conf().get('request_timeout', None), # 请求超时时间，openai接口默认设置为600，对于难问题一般需要较长时间 "timeout": conf().get('request_timeout', None), #重试超时时间，在这个时间内，将会自动重试 } def reply_text(self, session:ChatGPTSession, session_id, api_key, retry_count=0) -> dict: ''' call openai's ChatCompletion to get the answer :param session: a conversation session :param session_id: session id :param retry_count: retry count :return: {} ''' try: if conf().get('rate_limit_chatgpt') and not self.tb4chatgpt.get_token(): raise openai.error.RateLimitError("RateLimitError: rate limit exceeded") # if api_key == None, the default openai.api_key will be used response = openai.ChatCompletion.create( api_key=api_key, messages=session.messages, **self.compose_args() ) # logger.info("[ChatGPT] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"])) return {"total_tokens": response["usage"]["total_tokens"], "completion_tokens": response["usage"]["completion_tokens"], "content": response.choices[0]['message']['content']} except Exception as e: need_retry = retry_count < 2 result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"} if isinstance(e, openai.error.RateLimitError): logger.warn("[CHATGPT] RateLimitError: {}".format(e)) result['content'] = "提问太快啦，请休息一下再问我吧" if need_retry: time.sleep(5) elif isinstance(e, openai.error.Timeout): logger.warn("[CHATGPT] Timeout: {}".format(e)) result['content'] = "我没有收到你的消息" if need_retry: time.sleep(5) elif isinstance(e, openai.error.APIConnectionError): logger.warn("[CHATGPT] APIConnectionError: {}".format(e)) need_retry = False result['content'] = "我连接不到你的网络" else: logger.warn("[CHATGPT] Exception: {}".format(e)) need_retry = False self.sessions.clear_session(session_id) if need_retry: logger.warn("[CHATGPT] 第{}次重试".format(retry_count+1)) return self.reply_text(session, session_id, api_key, retry_count+1) else: return result class AzureChatGPTBot(ChatGPTBot): def __init__(self): super().__init__() openai.api_type = "azure" openai.api_version = "2023-03-15-preview" def compose_args(self): args = super().compose_args() args["deployment_id"] = conf().get("azure_deployment_id") #args["engine"] = args["model"] #del(args["model"]) return args