# encoding:utf-8 from bot.bot import Bot from bot.openai.open_ai_image import OpenAIImage from bot.openai.open_ai_session import OpenAISession from bot.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from config import conf from common.log import logger import openai import openai.error import time user_session = dict() # OpenAI对话模型API (可用) class OpenAIBot(Bot, OpenAIImage): def __init__(self): super().__init__() 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 self.sessions = SessionManager(OpenAISession, model= conf().get("model") or "text-davinci-003") def reply(self, query, context=None): # acquire reply content if context and context.type: if context.type == ContextType.TEXT: logger.info("[OPEN_AI] query={}".format(query)) session_id = context['session_id'] reply = None if query == '#清除记忆': 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') else: session = self.sessions.session_query(query, session_id) new_query = str(session) logger.debug("[OPEN_AI] session query={}".format(new_query)) total_tokens, completion_tokens, reply_content = self.reply_text(new_query, session_id, 0) logger.debug("[OPEN_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(new_query, session_id, reply_content, completion_tokens)) if total_tokens == 0 : reply = Reply(ReplyType.ERROR, reply_content) else: self.sessions.session_reply(reply_content, session_id, total_tokens) reply = Reply(ReplyType.TEXT, 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 def reply_text(self, query, session_id, retry_count=0): try: response = openai.Completion.create( model= conf().get("model") or "text-davinci-003", # 对话模型的名称 prompt=query, temperature=0.9, # 值在[0,1]之间,越大表示回复越具有不确定性 max_tokens=1200, # 回复最大的字符数 top_p=1, 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=0.0, # [-2,2]之间,该值越大则更倾向于产生不同的内容 stop=["\n\n\n"] ) res_content = response.choices[0]['text'].strip().replace('<|endoftext|>', '') total_tokens = response["usage"]["total_tokens"] completion_tokens = response["usage"]["completion_tokens"] logger.info("[OPEN_AI] reply={}".format(res_content)) return total_tokens, completion_tokens, res_content except Exception as e: need_retry = retry_count < 2 result = [0,0,"我现在有点累了,等会再来吧"] if isinstance(e, openai.error.RateLimitError): logger.warn("[OPEN_AI] RateLimitError: {}".format(e)) result[2] = "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("[OPEN_AI] Timeout: {}".format(e)) result[2] = "我没有收到你的消息" if need_retry: time.sleep(5) elif isinstance(e, openai.error.APIConnectionError): logger.warn("[OPEN_AI] APIConnectionError: {}".format(e)) need_retry = False result[2] = "我连接不到你的网络" else: logger.warn("[OPEN_AI] Exception: {}".format(e)) need_retry = False self.sessions.clear_session(session_id) if need_retry: logger.warn("[OPEN_AI] 第{}次重试".format(retry_count+1)) return self.reply_text(query, session_id, retry_count+1) else: return result