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- # 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 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, user_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 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 0,0, "提问太快啦，请休息一下再问我吧"
- except Exception as e:
- # unknown exception
- logger.exception(e)
- self.sessions.clear_session(user_id)
- return 0,0, "请再问我一次吧"
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