mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
synced 2026-02-14 08:16:32 +08:00
using pickle instead of redis
This commit is contained in:
1
.gitignore
vendored
1
.gitignore
vendored
@@ -10,3 +10,4 @@ nohup.out
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tmp
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plugins.json
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itchat.pkl
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user_datas.pkl
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11
app.py
11
app.py
@@ -4,13 +4,22 @@ import os
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from config import conf, load_config
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from channel import channel_factory
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from common.log import logger
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from plugins import *
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import signal
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import sys
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def sigterm_handler(_signo, _stack_frame):
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conf().save_user_datas()
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sys.exit(0)
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def run():
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try:
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# load config
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load_config()
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# ctrl + c
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signal.signal(signal.SIGINT, sigterm_handler)
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# kill signal
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signal.signal(signal.SIGTERM, sigterm_handler)
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# create channel
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channel_name=conf().get('channel_type', 'wx')
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@@ -13,7 +13,6 @@ from common.expired_dict import ExpiredDict
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import openai
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import openai.error
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import time
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import redis
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# OpenAI对话模型API (可用)
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class ChatGPTBot(Bot,OpenAIImage):
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@@ -8,18 +8,15 @@
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在开始部署前,你需要一个拥有公网IP的服务器,以提供微信服务器和我们自己服务器的连接。或者你需要进行内网穿透,否则微信服务器无法将消息发送给我们的服务器。
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此外,需要在我们的服务器上安装额外的依赖web.py和redis,其中redis用来储存用户私有的配置信息。
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此外,需要在我们的服务器上安装python的web框架web.py。
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以ubuntu为例(在ubuntu 22.04上测试):
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```
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sudo apt-get install redis
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sudo systemctl start redis
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pip3 install redis
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pip3 install web.py
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```
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然后在[微信公众平台](mp.weixin.qq.com)注册一个自己的公众号,类型选择订阅号,主体为个人即可。
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然后根据[接入指南](https://developers.weixin.qq.com/doc/offiaccount/Basic_Information/Access_Overview.html)的说明,在[微信公众平台](mp.weixin.qq.com)的“设置与开发”-“基本配置”-“服务器配置”中填写服务器地址(URL)和令牌(Token)。这个Token是你自己编的一个特定的令牌。消息加解密方式目前选择的是明文模式。相关的服务器验证代码已经写好,你不需要再添加任何代码。你只需要将本项目根目录的`app.py`中channel_name改成"mp",将上述的Token填写在本项目根目录的`config.json`中,例如`"wechatmp_token": "Your Token",` 然后运行`python3 app.py`启动web服务器,然后在刚才的“服务器配置”中点击`提交`即可验证你的服务器。
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然后根据[接入指南](https://developers.weixin.qq.com/doc/offiaccount/Basic_Information/Access_Overview.html)的说明,在[微信公众平台](mp.weixin.qq.com)的“设置与开发”-“基本配置”-“服务器配置”中填写服务器地址(URL)和令牌(Token)。这个Token是你自己编的一个特定的令牌。消息加解密方式目前选择的是明文模式。相关的服务器验证代码已经写好,你不需要再添加任何代码。你只需要在本项目根目录的`config.json`中添加`"channel_type": "wechatmp", "wechatmp_token": "your Token", ` 然后运行`python3 app.py`启动web服务器,然后在刚才的“服务器配置”中点击`提交`即可验证你的服务器。
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随后在[微信公众平台](mp.weixin.qq.com)启用服务器,关闭手动填写规则的自动回复,即可实现ChatGPT的自动回复。
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@@ -29,7 +26,7 @@ pip3 install web.py
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另外,由于微信官方的限制,自动回复有长度限制。因此这里将ChatGPT的回答拆分,分成每段600字回复(限制大约在700字)。
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## 私有api_key
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公共api有访问频率限制(免费账号每分钟最多20次ChatGPT的API调用),这在服务多人的时候会遇到问题。因此这里多加了一个设置私有api_key的功能,私有的api_key将储存在redis中。另外后续计划利用redis储存更多的用户个人配置。目前通过godcmd插件的命令来设置私有api_key。
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公共api有访问频率限制(免费账号每分钟最多20次ChatGPT的API调用),这在服务多人的时候会遇到问题。因此这里多加了一个设置私有api_key的功能。目前通过godcmd插件的命令来设置私有api_key。
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## 命令优化
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之前plugin中#和$符号混用,且$这个符号在微信中和中文会有较大间隔,体验实在不好。这里我将所有命令更改成了以#开头。添加了一个叫finish的plugin来最后处理所有#结尾的命令,防止未知命令变成ChatGPT的query。
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@@ -13,7 +13,6 @@ from bridge.reply import *
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from bridge.context import *
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from plugins import *
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import traceback
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import redis
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# If using SSL, uncomment the following lines, and modify the certificate path.
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# from cheroot.server import HTTPServer
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@@ -181,12 +180,8 @@ class WechatMPChannel(Channel):
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context = Context()
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context.kwargs = {'isgroup': False, 'receiver': fromUser, 'session_id': fromUser}
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R = redis.Redis(host='localhost', port=6379, db=0)
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user_openai_api_key = "openai_api_key_" + fromUser
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api_key = R.get(user_openai_api_key)
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if api_key != None:
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api_key = api_key.decode("utf-8")
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context['openai_api_key'] = api_key # None or user openai_api_key
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user_data = conf().get_user_data(fromUser)
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context['openai_api_key'] = user_data.get('openai_api_key') # None or user openai_api_key
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img_match_prefix = check_prefix(message, conf().get('image_create_prefix'))
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if img_match_prefix:
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31
config.py
31
config.py
@@ -3,6 +3,7 @@
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import json
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import os
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from common.log import logger
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import pickle
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# 将所有可用的配置项写在字典里, 请使用小写字母
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available_setting = {
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@@ -88,6 +89,11 @@ available_setting = {
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class Config(dict):
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def __init__(self, d:dict={}):
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super().__init__(d)
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# user_datas: 用户数据,key为用户名,value为用户数据,也是dict
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self.user_datas = {}
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def __getitem__(self, key):
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if key not in available_setting:
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raise Exception("key {} not in available_setting".format(key))
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@@ -106,6 +112,30 @@ class Config(dict):
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except Exception as e:
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raise e
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# Make sure to return a dictionary to ensure atomic
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def get_user_data(self, user) -> dict:
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if self.user_datas.get(user) is None:
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self.user_datas[user] = {}
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return self.user_datas[user]
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def load_user_datas(self):
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try:
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with open('user_datas.pkl', 'rb') as f:
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self.user_datas = pickle.load(f)
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logger.info("[Config] User datas loaded.")
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except FileNotFoundError as e:
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logger.info("[Config] User datas file not found, ignore.")
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except Exception as e:
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logger.info("[Config] User datas error: {}".format(e))
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self.user_datas = {}
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def save_user_datas(self):
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try:
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with open('user_datas.pkl', 'wb') as f:
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pickle.dump(self.user_datas, f)
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logger.info("[Config] User datas saved.")
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except Exception as e:
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logger.info("[Config] User datas error: {}".format(e))
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config = Config()
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@@ -142,6 +172,7 @@ def load_config():
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logger.info("[INIT] load config: {}".format(config))
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config.load_user_datas()
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def get_root():
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return os.path.dirname(os.path.abspath(__file__))
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@@ -7,11 +7,12 @@ from typing import Tuple
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from bridge.bridge import Bridge
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from bridge.context import ContextType
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from bridge.reply import Reply, ReplyType
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from config import load_config
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from config import conf, load_config
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import plugins
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from plugins import *
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from common import const
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from common.log import logger
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import pickle
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# 定义指令集
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COMMANDS = {
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@@ -195,20 +196,18 @@ class Godcmd(Plugin):
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ok, result = False, "unknown args"
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elif cmd == "set_openai_api_key":
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if len(args) == 1:
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import redis
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R = redis.Redis(host='localhost', port=6379, db=0)
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user_openai_api_key = "openai_api_key_" + user
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R.set(user_openai_api_key, args[0])
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# R.sadd("openai_api_key", args[0])
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user_data = conf().get_user_data(user)
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user_data['openai_api_key'] = args[0]
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ok, result = True, "你的OpenAI私有api_key已设置为" + args[0]
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else:
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ok, result = False, "请提供一个api_key"
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elif cmd == "reset_openai_api_key":
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import redis
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R = redis.Redis(host='localhost', port=6379, db=0)
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user_openai_api_key = "openai_api_key_" + user
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R.delete(user_openai_api_key)
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ok, result = True, "OpenAI的api_key已重置"
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try:
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user_data = conf().get_user_data(user)
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user_data.pop('openai_api_key')
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except Exception as e:
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ok, result = False, "你没有设置私有api_key"
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ok, result = True, "你的OpenAI私有api_key已清除"
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# elif cmd == "helpp":
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# if len(args) != 1:
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# ok, result = False, "请提供插件名"
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