chatgpt-on-wechat / bot /openai /open_ai_bot.py
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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 openai.error
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, session_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 Exception as e:
need_retry = retry_count < 2
result = [0,0,"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[2] = "提问太快啦,请休息一下再问我吧"
if need_retry:
time.sleep(5)
elif isinstance(e, openai.error.Timeout):
logger.warn("[OPEN_AI] Timeout: {}".format(e))
result[2] = "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[2] = "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_id)
if need_retry:
logger.warn("[OPEN_AI] 第{}次重试".format(retry_count+1))
return self.reply_text(query, session_id, retry_count+1)
else:
return result