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- # encoding:utf-8
-
- import time
-
- import openai
- import openai.error
-
- 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 common.log import logger
- from config import conf
-
- 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")
- self.args = {
- "model": conf().get("model") or "text-davinci-003", # 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": 1200, # 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
- "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
- "timeout": conf().get("request_timeout", None), # 重试超时时间，在这个时间内，将会自动重试
- "stop": ["\n\n\n"],
- }
-
- 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)
- result = self.reply_text(session)
- total_tokens, completion_tokens, reply_content = (
- result["total_tokens"],
- result["completion_tokens"],
- result["content"],
- )
- logger.debug(
- "[OPEN_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(str(session), 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, session: OpenAISession, retry_count=0):
- try:
- response = openai.Completion.create(prompt=str(session), **self.args)
- 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": total_tokens,
- "completion_tokens": completion_tokens,
- "content": res_content,
- }
- except Exception as e:
- need_retry = retry_count < 2
- result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
- if isinstance(e, openai.error.RateLimitError):
- logger.warn("[OPEN_AI] RateLimitError: {}".format(e))
- result["content"] = "提问太快啦，请休息一下再问我吧"
- if need_retry:
- time.sleep(20)
- elif isinstance(e, openai.error.Timeout):
- logger.warn("[OPEN_AI] Timeout: {}".format(e))
- result["content"] = "我没有收到你的消息"
- if need_retry:
- time.sleep(5)
- elif isinstance(e, openai.error.APIConnectionError):
- logger.warn("[OPEN_AI] APIConnectionError: {}".format(e))
- need_retry = False
- result["content"] = "我连接不到你的网络"
- else:
- logger.warn("[OPEN_AI] Exception: {}".format(e))
- need_retry = False
- self.sessions.clear_session(session.session_id)
-
- if need_retry:
- logger.warn("[OPEN_AI] 第{}次重试".format(retry_count + 1))
- return self.reply_text(session, retry_count + 1)
- else:
- return result
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