Files
gpt_academic/crazy_functions/Social_Helper.py
binary-husky a01ca93362 Merge Latest Frontier (#1991)
* logging sys to loguru: stage 1 complete

* import loguru: stage 2

* logging -> loguru: stage 3

* support o1-preview and o1-mini

* logging -> loguru stage 4

* update social helper

* logging -> loguru: final stage

* fix: console output

* update translation matrix

* fix: loguru argument error with proxy enabled (#1977)

* relax llama index version

* remove comment

* Added some modules to support openrouter (#1975)

* Added some modules for supporting openrouter model

Added some modules for supporting openrouter model

* Update config.py

* Update .gitignore

* Update bridge_openrouter.py

* Not changed actually

* Refactor logging in bridge_openrouter.py

---------

Co-authored-by: binary-husky <qingxu.fu@outlook.com>

* remove logging extra

---------

Co-authored-by: Steven Moder <java20131114@gmail.com>
Co-authored-by: Ren Lifei <2602264455@qq.com>
2024-10-05 17:09:18 +08:00

168 lines
7.3 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

import pickle, os, random
from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
from crazy_functions.crazy_utils import input_clipping
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from request_llms.bridge_all import predict_no_ui_long_connection
from crazy_functions.json_fns.select_tool import structure_output, select_tool
from pydantic import BaseModel, Field
from loguru import logger
from typing import List
SOCIAL_NETWOK_WORKER_REGISTER = {}
class SocialNetwork():
def __init__(self):
self.people = []
class SaveAndLoad():
def __init__(self, user_name, llm_kwargs, auto_load_checkpoint=True, checkpoint_dir=None) -> None:
self.user_name = user_name
self.checkpoint_dir = checkpoint_dir
if auto_load_checkpoint:
self.social_network = self.load_from_checkpoint(checkpoint_dir)
else:
self.social_network = SocialNetwork()
def does_checkpoint_exist(self, checkpoint_dir=None):
import os, glob
if checkpoint_dir is None: checkpoint_dir = self.checkpoint_dir
if not os.path.exists(checkpoint_dir): return False
if len(glob.glob(os.path.join(checkpoint_dir, "social_network.pkl"))) == 0: return False
return True
def save_to_checkpoint(self, checkpoint_dir=None):
if checkpoint_dir is None: checkpoint_dir = self.checkpoint_dir
with open(os.path.join(checkpoint_dir, 'social_network.pkl'), "wb+") as f:
pickle.dump(self.social_network, f)
return
def load_from_checkpoint(self, checkpoint_dir=None):
if checkpoint_dir is None: checkpoint_dir = self.checkpoint_dir
if self.does_checkpoint_exist(checkpoint_dir=checkpoint_dir):
with open(os.path.join(checkpoint_dir, 'social_network.pkl'), "rb") as f:
social_network = pickle.load(f)
return social_network
else:
return SocialNetwork()
class Friend(BaseModel):
friend_name: str = Field(description="name of a friend")
friend_description: str = Field(description="description of a friend (everything about this friend)")
friend_relationship: str = Field(description="The relationship with a friend (e.g. friend, family, colleague)")
class FriendList(BaseModel):
friends_list: List[Friend] = Field(description="The list of friends")
class SocialNetworkWorker(SaveAndLoad):
def ai_socail_advice(self, prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, run_gpt_fn, intention_type):
pass
def ai_remove_friend(self, prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, run_gpt_fn, intention_type):
pass
def ai_list_friends(self, prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, run_gpt_fn, intention_type):
pass
def ai_add_multi_friends(self, prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, run_gpt_fn, intention_type):
friend, err_msg = structure_output(
txt=prompt,
prompt="根据提示, 解析多个联系人的身份信息\n\n",
err_msg=f"不能理解该联系人",
run_gpt_fn=run_gpt_fn,
pydantic_cls=FriendList
)
if friend.friends_list:
for f in friend.friends_list:
self.add_friend(f)
msg = f"成功添加{len(friend.friends_list)}个联系人: {str(friend.friends_list)}"
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
def run(self, txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
prompt = txt
run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
self.tools_to_select = {
"SocialAdvice":{
"explain_to_llm": "如果用户希望获取社交指导调用SocialAdvice生成一些社交建议",
"callback": self.ai_socail_advice,
},
"AddFriends":{
"explain_to_llm": "如果用户给出了联系人调用AddMultiFriends把联系人添加到数据库",
"callback": self.ai_add_multi_friends,
},
"RemoveFriend":{
"explain_to_llm": "如果用户希望移除某个联系人调用RemoveFriend",
"callback": self.ai_remove_friend,
},
"ListFriends":{
"explain_to_llm": "如果用户列举联系人调用ListFriends",
"callback": self.ai_list_friends,
}
}
try:
Explaination = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
class UserSociaIntention(BaseModel):
intention_type: str = Field(
description=
f"The type of user intention. You must choose from {self.tools_to_select.keys()}.\n\n"
f"Explaination:\n{Explaination}",
default="SocialAdvice"
)
pydantic_cls_instance, err_msg = select_tool(
prompt=txt,
run_gpt_fn=run_gpt_fn,
pydantic_cls=UserSociaIntention
)
except Exception as e:
yield from update_ui_lastest_msg(
lastmsg=f"无法理解用户意图 {err_msg}",
chatbot=chatbot,
history=history,
delay=0
)
return
intention_type = pydantic_cls_instance.intention_type
intention_callback = self.tools_to_select[pydantic_cls_instance.intention_type]['callback']
yield from intention_callback(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, run_gpt_fn, intention_type)
def add_friend(self, friend):
# check whether the friend is already in the social network
for f in self.social_network.people:
if f.friend_name == friend.friend_name:
f.friend_description = friend.friend_description
f.friend_relationship = friend.friend_relationship
logger.info(f"Repeated friend, update info: {friend}")
return
logger.info(f"Add a new friend: {friend}")
self.social_network.people.append(friend)
return
@CatchException
def I人助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
# 1. we retrieve worker from global context
user_name = chatbot.get_user()
checkpoint_dir=get_log_folder(user_name, plugin_name='experimental_rag')
if user_name in SOCIAL_NETWOK_WORKER_REGISTER:
social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name]
else:
social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
user_name,
llm_kwargs,
checkpoint_dir=checkpoint_dir,
auto_load_checkpoint=True
)
# 2. save
yield from social_network_worker.run(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
social_network_worker.save_to_checkpoint(checkpoint_dir)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面