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- # encoding:utf-8
-
- from bot.bot import Bot
- 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
- from common.expired_dict import ExpiredDict
- import openai
- import time
-
-
- # OpenAI对话模型API (可用)
- class ChatGPTBot(Bot):
- def __init__(self):
- 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')
- self.sessions = SessionManager()
- if proxy:
- openai.proxy = proxy
- if conf().get('rate_limit_chatgpt'):
- self.tb4chatgpt = TokenBucket(conf().get('rate_limit_chatgpt', 20))
- if conf().get('rate_limit_dalle'):
- self.tb4dalle = TokenBucket(conf().get('rate_limit_dalle', 50))
-
- def reply(self, query, context=None):
- # acquire reply content
- if context.type == ContextType.TEXT:
- logger.info("[OPEN_AI] 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.build_session_query(query, session_id)
- logger.debug("[OPEN_AI] session query={}".format(session))
-
- # 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, 0)
- logger.debug("[OPEN_AI] new_query={}, session_id={}, reply_cont={}".format(session, session_id, reply_content["content"]))
- 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.save_session(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("[OPEN_AI] 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
- }
-
- def reply_text(self, session, session_id, 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():
- return {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
- response = openai.ChatCompletion.create(
- messages=session, **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 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(session, session_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)
- self.sessions.clear_session(session_id)
- return {"completion_tokens": 0, "content": "请再问我一次吧"}
-
- def create_img(self, query, retry_count=0):
- try:
- if conf().get('rate_limit_dalle') and not self.tb4dalle.get_token():
- return False, "请求太快了，请休息一下再问我吧"
- 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 True, 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 False, "提问太快啦，请休息一下再问我吧"
- except Exception as e:
- logger.exception(e)
- return False, str(e)
-
-
- 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["engine"] = args["model"]
- del(args["model"])
- return args
-
-
- class SessionManager(object):
- def __init__(self):
- if conf().get('expires_in_seconds'):
- sessions = ExpiredDict(conf().get('expires_in_seconds'))
- else:
- sessions = dict()
- self.sessions = sessions
-
- def build_session(self, session_id, system_prompt=None):
- session = self.sessions.get(session_id, [])
- if len(session) == 0:
- if system_prompt is None:
- system_prompt = conf().get("character_desc", "")
- system_item = {'role': 'system', 'content': system_prompt}
- session.append(system_item)
- self.sessions[session_id] = session
- return session
-
- def build_session_query(self, query, session_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 session_id: session id
- :return: query content with conversaction
- '''
- session = self.build_session(session_id)
- user_item = {'role': 'user', 'content': query}
- session.append(user_item)
- return session
-
- def save_session(self, answer, session_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 = self.sessions.get(session_id)
- if session:
- # append conversation
- gpt_item = {'role': 'assistant', 'content': answer}
- session.append(gpt_item)
-
- # discard exceed limit conversation
- self.discard_exceed_conversation(session, max_tokens, total_tokens)
-
- def discard_exceed_conversation(self, 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
-
- def clear_session(self, session_id):
- self.sessions[session_id] = []
-
- def clear_all_session(self):
- self.sessions.clear()
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