# encoding:utf-8 from bot.bot import Bot from config import conf from common.log import logger from common.expired_dict import ExpiredDict import openai import time if conf().get('expires_in_seconds'): user_session = ExpiredDict(conf().get('expires_in_seconds')) else: user_session = dict() # OpenAI对话模型API (可用) class ChatGPTBot(Bot): def __init__(self): openai.api_key = conf().get('open_ai_api_key') proxy = conf().get('proxy') if proxy: openai.proxy = proxy def reply(self, query, context=None): # acquire reply content if not context or not context.get('type') or context.get('type') == 'TEXT': logger.info("[OPEN_AI] query={}".format(query)) from_user_id = context['from_user_id'] if query == '#清除记忆': Session.clear_session(from_user_id) return '记忆已清除' elif query == '#清除所有': Session.clear_all_session() return '所有人记忆已清除' new_query = Session.build_session_query(query, from_user_id) logger.debug("[OPEN_AI] session query={}".format(new_query)) # if context.get('stream'): # # reply in stream # return self.reply_text_stream(query, new_query, from_user_id) reply_content = self.reply_text(new_query, from_user_id, 0) logger.debug("[OPEN_AI] new_query={}, user={}, reply_cont={}".format(new_query, from_user_id, reply_content["content"])) if reply_content["completion_tokens"] > 0: Session.save_session(reply_content["content"], from_user_id, reply_content["total_tokens"]) return reply_content["content"] elif context.get('type', None) == 'IMAGE_CREATE': return self.create_img(query, 0) def reply_text(self, query, user_id, retry_count=0) ->dict: ''' call openai's ChatCompletion to get the answer :param query: query content :param user_id: from user id :param retry_count: retry count :return: {} ''' try: response = openai.ChatCompletion.create( model="gpt-3.5-turbo", # 对话模型的名称 messages=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=4096, # 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 ) 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 openai.error.RateLimitError as e: # rate limit exception logger.warn(e) if retry_count < 1: time.sleep(5) logger.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1)) return self.reply_text(query, user_id, retry_count+1) else: return {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"} except openai.error.APIConnectionError as e: # api connection exception logger.warn(e) logger.warn("[OPEN_AI] APIConnection failed") return {"completion_tokens": 0, "content":"我连接不到你的网络"} except openai.error.Timeout as e: logger.warn(e) logger.warn("[OPEN_AI] Timeout") return {"completion_tokens": 0, "content":"我没有收到你的消息"} except Exception as e: # unknown exception logger.exception(e) Session.clear_session(user_id) return {"completion_tokens": 0, "content": "请再问我一次吧"} def create_img(self, query, retry_count=0): try: logger.info("[OPEN_AI] image_query={}".format(query)) response = openai.Image.create( prompt=query, #图片描述 n=1, #每次生成图片的数量 size="256x256" #图片大小,可选有 256x256, 512x512, 1024x1024 ) image_url = response['data'][0]['url'] logger.info("[OPEN_AI] image_url={}".format(image_url)) return image_url except openai.error.RateLimitError as e: logger.warn(e) if retry_count < 1: time.sleep(5) logger.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count+1)) return self.create_img(query, retry_count+1) else: return "提问太快啦，请休息一下再问我吧" except Exception as e: logger.exception(e) return None class Session(object): @staticmethod def build_session_query(query, user_id): ''' build query with conversation history e.g. [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Who won the world series in 2020?"}, {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."}, {"role": "user", "content": "Where was it played?"} ] :param query: query content :param user_id: from user id :return: query content with conversaction ''' session = user_session.get(user_id, []) if len(session) == 0: system_prompt = conf().get("character_desc", "") system_item = {'role': 'system', 'content': system_prompt} session.append(system_item) user_session[user_id] = session user_item = {'role': 'user', 'content': query} session.append(user_item) return session @staticmethod def save_session(answer, user_id, total_tokens): max_tokens = conf().get("conversation_max_tokens") if not max_tokens: # default 3000 max_tokens = 1000 max_tokens=int(max_tokens) session = user_session.get(user_id) if session: # append conversation gpt_item = {'role': 'assistant', 'content': answer} session.append(gpt_item) # discard exceed limit conversation Session.discard_exceed_conversation(session, max_tokens, total_tokens) @staticmethod def discard_exceed_conversation(session, max_tokens, total_tokens): dec_tokens = int(total_tokens) # logger.info("prompt tokens used={},max_tokens={}".format(used_tokens,max_tokens)) while dec_tokens > max_tokens: # pop first conversation if len(session) > 3: session.pop(1) session.pop(1) else: break dec_tokens = dec_tokens - max_tokens @staticmethod def clear_session(user_id): user_session[user_id] = [] @staticmethod def clear_all_session(): user_session.clear()