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https://github.com/zhayujie/chatgpt-on-wechat.git
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239 lines
10 KiB
Python
239 lines
10 KiB
Python
# encoding:utf-8
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from bot.bot import Bot
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from bridge.context import ContextType
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from bridge.reply import Reply, ReplyType
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from config import conf, load_config
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from common.log import logger
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from common.token_bucket import TokenBucket
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from common.expired_dict import ExpiredDict
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import openai
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import time
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# OpenAI对话模型API (可用)
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class ChatGPTBot(Bot):
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def __init__(self):
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openai.api_key = conf().get('open_ai_api_key')
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if conf().get('open_ai_api_base'):
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openai.api_base = conf().get('open_ai_api_base')
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proxy = conf().get('proxy')
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self.sessions = SessionManager()
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if proxy:
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openai.proxy = proxy
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if conf().get('rate_limit_chatgpt'):
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self.tb4chatgpt = TokenBucket(conf().get('rate_limit_chatgpt', 20))
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if conf().get('rate_limit_dalle'):
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self.tb4dalle = TokenBucket(conf().get('rate_limit_dalle', 50))
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def reply(self, query, context=None):
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# acquire reply content
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if context.type == ContextType.TEXT:
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logger.info("[OPEN_AI] query={}".format(query))
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session_id = context['session_id']
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reply = None
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clear_memory_commands = conf().get('clear_memory_commands', ['#清除记忆'])
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if query in clear_memory_commands:
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self.sessions.clear_session(session_id)
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reply = Reply(ReplyType.INFO, '记忆已清除')
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elif query == '#清除所有':
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self.sessions.clear_all_session()
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reply = Reply(ReplyType.INFO, '所有人记忆已清除')
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elif query == '#更新配置':
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load_config()
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reply = Reply(ReplyType.INFO, '配置已更新')
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if reply:
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return reply
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session = self.sessions.build_session_query(query, session_id)
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logger.debug("[OPEN_AI] session query={}".format(session))
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# if context.get('stream'):
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# # reply in stream
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# return self.reply_text_stream(query, new_query, session_id)
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reply_content = self.reply_text(session, session_id, 0)
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logger.debug("[OPEN_AI] new_query={}, session_id={}, reply_cont={}".format(session, session_id, reply_content["content"]))
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if reply_content['completion_tokens'] == 0 and len(reply_content['content']) > 0:
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reply = Reply(ReplyType.ERROR, reply_content['content'])
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elif reply_content["completion_tokens"] > 0:
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self.sessions.save_session(reply_content["content"], session_id, reply_content["total_tokens"])
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reply = Reply(ReplyType.TEXT, reply_content["content"])
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else:
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reply = Reply(ReplyType.ERROR, reply_content['content'])
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logger.debug("[OPEN_AI] reply {} used 0 tokens.".format(reply_content))
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return reply
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elif context.type == ContextType.IMAGE_CREATE:
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ok, retstring = self.create_img(query, 0)
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reply = None
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if ok:
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reply = Reply(ReplyType.IMAGE_URL, retstring)
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else:
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reply = Reply(ReplyType.ERROR, retstring)
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return reply
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else:
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reply = Reply(ReplyType.ERROR, 'Bot不支持处理{}类型的消息'.format(context.type))
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return reply
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def compose_args(self):
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return {
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"model": conf().get("model") or "gpt-3.5-turbo", # 对话模型的名称
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"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
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# "max_tokens":4096, # 回复最大的字符数
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"top_p":1,
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"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
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"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
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}
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def reply_text(self, session, session_id, retry_count=0) -> dict:
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'''
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call openai's ChatCompletion to get the answer
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:param session: a conversation session
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:param session_id: session id
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:param retry_count: retry count
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:return: {}
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'''
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try:
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if conf().get('rate_limit_chatgpt') and not self.tb4chatgpt.get_token():
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return {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
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response = openai.ChatCompletion.create(
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messages=session, **self.compose_args()
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)
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# logger.info("[ChatGPT] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"]))
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return {"total_tokens": response["usage"]["total_tokens"],
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"completion_tokens": response["usage"]["completion_tokens"],
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"content": response.choices[0]['message']['content']}
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except openai.error.RateLimitError as e:
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# rate limit exception
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logger.warn(e)
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if retry_count < 1:
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time.sleep(5)
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logger.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1))
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return self.reply_text(session, session_id, retry_count+1)
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else:
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return {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
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except openai.error.APIConnectionError as e:
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# api connection exception
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logger.warn(e)
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logger.warn("[OPEN_AI] APIConnection failed")
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return {"completion_tokens": 0, "content": "我连接不到你的网络"}
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except openai.error.Timeout as e:
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logger.warn(e)
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logger.warn("[OPEN_AI] Timeout")
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return {"completion_tokens": 0, "content": "我没有收到你的消息"}
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except Exception as e:
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# unknown exception
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logger.exception(e)
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self.sessions.clear_session(session_id)
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return {"completion_tokens": 0, "content": "请再问我一次吧"}
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def create_img(self, query, retry_count=0):
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try:
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if conf().get('rate_limit_dalle') and not self.tb4dalle.get_token():
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return False, "请求太快了，请休息一下再问我吧"
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logger.info("[OPEN_AI] image_query={}".format(query))
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response = openai.Image.create(
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prompt=query, #图片描述
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n=1, #每次生成图片的数量
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size="256x256" #图片大小,可选有 256x256, 512x512, 1024x1024
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)
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image_url = response['data'][0]['url']
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logger.info("[OPEN_AI] image_url={}".format(image_url))
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return True, image_url
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except openai.error.RateLimitError as e:
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logger.warn(e)
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if retry_count < 1:
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time.sleep(5)
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logger.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count+1))
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return self.create_img(query, retry_count+1)
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else:
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return False, "提问太快啦，请休息一下再问我吧"
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except Exception as e:
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logger.exception(e)
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return False, str(e)
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class AzureChatGPTBot(ChatGPTBot):
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def __init__(self):
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super().__init__()
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openai.api_type = "azure"
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openai.api_version = "2023-03-15-preview"
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def compose_args(self):
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args = super().compose_args()
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args["engine"] = args["model"]
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del(args["model"])
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return args
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class SessionManager(object):
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def __init__(self):
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if conf().get('expires_in_seconds'):
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sessions = ExpiredDict(conf().get('expires_in_seconds'))
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else:
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sessions = dict()
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self.sessions = sessions
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def build_session(self, session_id, system_prompt=None):
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session = self.sessions.get(session_id, [])
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if len(session) == 0:
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if system_prompt is None:
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system_prompt = conf().get("character_desc", "")
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system_item = {'role': 'system', 'content': system_prompt}
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session.append(system_item)
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self.sessions[session_id] = session
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return session
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def build_session_query(self, query, session_id):
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'''
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build query with conversation history
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e.g. [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Who won the world series in 2020?"},
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{"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
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{"role": "user", "content": "Where was it played?"}
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]
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:param query: query content
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:param session_id: session id
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:return: query content with conversaction
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'''
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session = self.build_session(session_id)
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user_item = {'role': 'user', 'content': query}
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session.append(user_item)
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return session
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def save_session(self, answer, session_id, total_tokens):
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max_tokens = conf().get("conversation_max_tokens")
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if not max_tokens:
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# default 3000
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max_tokens = 1000
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max_tokens = int(max_tokens)
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session = self.sessions.get(session_id)
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if session:
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# append conversation
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gpt_item = {'role': 'assistant', 'content': answer}
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session.append(gpt_item)
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# discard exceed limit conversation
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self.discard_exceed_conversation(session, max_tokens, total_tokens)
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def discard_exceed_conversation(self, session, max_tokens, total_tokens):
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dec_tokens = int(total_tokens)
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# logger.info("prompt tokens used={},max_tokens={}".format(used_tokens,max_tokens))
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while dec_tokens > max_tokens:
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# pop first conversation
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if len(session) > 3:
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session.pop(1)
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session.pop(1)
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else:
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break
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dec_tokens = dec_tokens - max_tokens
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def clear_session(self, session_id):
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self.sessions[session_id] = []
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def clear_all_session(self):
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self.sessions.clear()
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