webchat / bot /openai /open_ai_bot.py
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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