# encoding:utf-8
from bot.bot import Bot
from bot.chatgpt.chat_gpt_session import ChatGPTSession
from bot.openai.open_ai_image import OpenAIImage
from bot.session_manager import Session, SessionManager
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 openai.error
import time
# OpenAI对话模型API (可用)
class ChatGPTBot(Bot,OpenAIImage):
def __init__(self):
super().__init__()
# set the default api_key
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
if conf().get('rate_limit_chatgpt'):
self.tb4chatgpt = TokenBucket(conf().get('rate_limit_chatgpt', 20))
self.sessions = SessionManager(ChatGPTSession, model= conf().get("model") or "gpt-3.5-turbo")
def reply(self, query, context=None):
# acquire reply content
if context.type == ContextType.TEXT:
logger.info("[CHATGPT] 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.session_query(query, session_id)
logger.debug("[CHATGPT] session query={}".format(session.messages))
api_key = context.get('openai_api_key')
# 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, api_key, 0)
logger.debug("[CHATGPT] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(session.messages, session_id, reply_content["content"], reply_content["completion_tokens"]))
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.session_reply(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("[CHATGPT] 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
"request_timeout": conf().get('request_timeout', 60), # 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', 120), #重试超时时间，在这个时间内，将会自动重试
}
def reply_text(self, session:ChatGPTSession, session_id, api_key, 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():
raise openai.error.RateLimitError("RateLimitError: rate limit exceeded")
# if api_key == None, the default openai.api_key will be used
response = openai.ChatCompletion.create(
api_key=api_key, messages=session.messages, **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 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("[CHATGPT] RateLimitError: {}".format(e))
result['content'] = "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("[CHATGPT] 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("[CHATGPT] APIConnectionError: {}".format(e))
need_retry = False
result['content'] = "我连接不到你的网络"
else:
logger.warn("[CHATGPT] Exception: {}".format(e))
need_retry = False
self.sessions.clear_session(session_id)
if need_retry:
logger.warn("[CHATGPT] 第{}次重试".format(retry_count+1))
return self.reply_text(session, session_id, api_key, retry_count+1)
else:
return result
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