mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
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157 lines
7.2 KiB
Python
157 lines
7.2 KiB
Python
# encoding:utf-8
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from bot.bot import Bot
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from bot.chatgpt.chat_gpt_session import ChatGPTSession
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from bot.openai.open_ai_image import OpenAIImage
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from bot.session_manager import SessionManager
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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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import openai
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import openai.error
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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,OpenAIImage):
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def __init__(self):
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super().__init__()
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# set the default api_key
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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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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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self.sessions = SessionManager(ChatGPTSession, model= conf().get("model") or "gpt-3.5-turbo")
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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("[CHATGPT] 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.session_query(query, session_id)
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logger.debug("[CHATGPT] session query={}".format(session.messages))
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api_key = context.get('openai_api_key')
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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, api_key, 0)
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logger.debug("[CHATGPT] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(session.messages, session_id, reply_content["content"], reply_content["completion_tokens"]))
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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.session_reply(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("[CHATGPT] 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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"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
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"timeout": conf().get('request_timeout', None), #重试超时时间,在这个时间内,将会自动重试
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}
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def reply_text(self, session:ChatGPTSession, session_id, api_key, 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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raise openai.error.RateLimitError("RateLimitError: rate limit exceeded")
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# if api_key == None, the default openai.api_key will be used
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response = openai.ChatCompletion.create(
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api_key=api_key, messages=session.messages, **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 Exception as e:
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need_retry = retry_count < 2
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result = {"completion_tokens": 0, "content": "我现在有点累了,等会再来吧"}
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if isinstance(e, openai.error.RateLimitError):
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logger.warn("[CHATGPT] RateLimitError: {}".format(e))
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result['content'] = "提问太快啦,请休息一下再问我吧"
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if need_retry:
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time.sleep(5)
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elif isinstance(e, openai.error.Timeout):
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logger.warn("[CHATGPT] Timeout: {}".format(e))
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result['content'] = "我没有收到你的消息"
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if need_retry:
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time.sleep(5)
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elif isinstance(e, openai.error.APIConnectionError):
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logger.warn("[CHATGPT] APIConnectionError: {}".format(e))
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need_retry = False
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result['content'] = "我连接不到你的网络"
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else:
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logger.warn("[CHATGPT] Exception: {}".format(e))
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need_retry = False
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self.sessions.clear_session(session_id)
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if need_retry:
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logger.warn("[CHATGPT] 第{}次重试".format(retry_count+1))
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return self.reply_text(session, session_id, api_key, retry_count+1)
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else:
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return result
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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["deployment_id"] = conf().get("azure_deployment_id")
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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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