test code

.flake8

@@ -0,0 +1,13 @@
+[flake8]
+max-line-length = 88
+select = E303,W293,W291,W292,E305,E231,E302
+exclude =
+    .tox,
+    __pycache__,
+    *.pyc,
+    .env
+    venv/*
+    .venv/*
+    reports/*
+    dist/*
+    lib/*

.github/ISSUE_TEMPLATE.md

@@ -27,5 +27,5 @@
 ### 环境
 
  - 操作系统类型  (Mac/Windows/Linux)：
- - Python版本  ( 执行 `python3 -V` )：                      
+ - Python版本  ( 执行 `python3 -V` )：  
  - pip版本  ( 依赖问题此项必填，执行 `pip3 -V`)：

.github/workflows/deploy-image.yml

@@ -49,9 +49,9 @@ jobs:
           file: ./docker/Dockerfile.latest
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}
-      
+
       - uses: actions/delete-package-versions@v4
-        with: 
+        with:
           package-name: 'chatgpt-on-wechat'
           package-type: 'container'
           min-versions-to-keep: 10

.pre-commit-config.yaml

@@ -0,0 +1,29 @@
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.4.0
+    hooks:
+      - id: fix-byte-order-marker
+      - id: check-case-conflict
+      - id: check-merge-conflict
+      - id: debug-statements
+      - id: pretty-format-json
+        types: [text]
+        files: \.json(.template)?$
+        args: [ --autofix , --no-ensure-ascii, --indent=2, --no-sort-keys]
+      - id: trailing-whitespace
+        exclude: '(\/|^)lib\/'
+        args: [ --markdown-linebreak-ext=md ]
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.12.0
+    hooks:
+      - id: isort
+        exclude: '(\/|^)lib\/'
+  - repo: https://github.com/psf/black
+    rev: 23.3.0
+    hooks:
+      - id: black
+        exclude: '(\/|^)lib\/'
+  - repo: https://github.com/PyCQA/flake8
+    rev: 6.0.0
+    hooks:
+      - id: flake8

README.md

@@ -120,15 +120,15 @@ pip3 install azure-cognitiveservices-speech
 
 ```bash
 # config.json文件内容示例
-{ 
+{
   "open_ai_api_key": "YOUR API KEY",                          # 填入上面创建的 OpenAI API KEY
   "model": "gpt-3.5-turbo",                                   # 模型名称。当use_azure_chatgpt为true时，其名称为Azure上model deployment名称
   "proxy": "127.0.0.1:7890",                                  # 代理客户端的ip和端口
   "single_chat_prefix": ["bot", "@bot"],                      # 私聊时文本需要包含该前缀才能触发机器人回复
   "single_chat_reply_prefix": "[bot] ",                       # 私聊时自动回复的前缀，用于区分真人
   "group_chat_prefix": ["@bot"],                              # 群聊时包含该前缀则会触发机器人回复
   "group_name_white_list": ["ChatGPT测试群", "ChatGPT测试群2"], # 开启自动回复的群名称列表
-  "group_chat_in_one_session": ["ChatGPT测试群"],              # 支持会话上下文共享的群名称       
+  "group_chat_in_one_session": ["ChatGPT测试群"],              # 支持会话上下文共享的群名称  
   "image_create_prefix": ["画", "看", "找"],                   # 开启图片回复的前缀
   "conversation_max_tokens": 1000,                            # 支持上下文记忆的最多字符数
   "speech_recognition": false,                                # 是否开启语音识别
@@ -160,7 +160,7 @@ pip3 install azure-cognitiveservices-speech
 **4.其他配置**
 
 + `model`: 模型名称，目前支持 `gpt-3.5-turbo`, `text-davinci-003`, `gpt-4`, `gpt-4-32k`  (其中gpt-4 api暂未开放)
-+ `temperature`,`frequency_penalty`,`presence_penalty`: Chat API接口参数，详情参考[OpenAI官方文档。](https://platform.openai.com/docs/api-reference/chat) 
++ `temperature`,`frequency_penalty`,`presence_penalty`: Chat API接口参数，详情参考[OpenAI官方文档。](https://platform.openai.com/docs/api-reference/chat)
 + `proxy`：由于目前 `openai` 接口国内无法访问，需配置代理客户端的地址，详情参考  [#351](https://github.com/zhayujie/chatgpt-on-wechat/issues/351)
 + 对于图像生成，在满足个人或群组触发条件外，还需要额外的关键词前缀来触发，对应配置 `image_create_prefix `
 + 关于OpenAI对话及图片接口的参数配置（内容自由度、回复字数限制、图片大小等），可以参考 [对话接口](https://beta.openai.com/docs/api-reference/completions) 和 [图像接口](https://beta.openai.com/docs/api-reference/completions)  文档直接在 [代码](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/bot/openai/open_ai_bot.py) `bot/openai/open_ai_bot.py` 中进行调整。
@@ -181,15 +181,15 @@ pip3 install azure-cognitiveservices-speech
 ```bash
 python3 app.py
 ```
-终端输出二维码后，使用微信进行扫码，当输出 "Start auto replying" 时表示自动回复程序已经成功运行了（注意：用于登录的微信需要在支付处已完成实名认证）。扫码登录后你的账号就成为机器人了，可以在微信手机端通过配置的关键词触发自动回复 (任意好友发送消息给你，或是自己发消息给好友)，参考[#142](https://github.com/zhayujie/chatgpt-on-wechat/issues/142)。 
+终端输出二维码后，使用微信进行扫码，当输出 "Start auto replying" 时表示自动回复程序已经成功运行了（注意：用于登录的微信需要在支付处已完成实名认证）。扫码登录后你的账号就成为机器人了，可以在微信手机端通过配置的关键词触发自动回复 (任意好友发送消息给你，或是自己发消息给好友)，参考[#142](https://github.com/zhayujie/chatgpt-on-wechat/issues/142)。
 
 
 ### 2.服务器部署
 
 使用nohup命令在后台运行程序：
 
 ```bash
-touch nohup.out                                   # 首次运行需要新建日志文件                     
+touch nohup.out                                   # 首次运行需要新建日志文件  
 nohup python3 app.py & tail -f nohup.out          # 在后台运行程序并通过日志输出二维码
 ```
 扫码登录后程序即可运行于服务器后台，此时可通过 `ctrl+c` 关闭日志，不会影响后台程序的运行。使用 `ps -ef | grep app.py | grep -v grep` 命令可查看运行于后台的进程，如果想要重新启动程序可以先 `kill` 掉对应的进程。日志关闭后如果想要再次打开只需输入 `tail -f nohup.out`。此外，`scripts` 目录下有一键运行、关闭程序的脚本供使用。

app.py

@@ -1,23 +1,28 @@
 # encoding:utf-8
 
 import os
-from config import conf, load_config
+import signal
+import sys
+
 from channel import channel_factory
 from common.log import logger
+from config import conf, load_config
 from plugins import *
-import signal
-import sys
+
 
 def sigterm_handler_wrap(_signo):
     old_handler = signal.getsignal(_signo)
+
     def func(_signo, _stack_frame):
         logger.info("signal {} received, exiting...".format(_signo))
         conf().save_user_datas()
-        if callable(old_handler): #  check old_handler
+        if callable(old_handler):  #  check old_handler
             return old_handler(_signo, _stack_frame)
         sys.exit(0)
+
     signal.signal(_signo, func)
 
+
 def run():
     try:
         # load config
@@ -28,17 +33,17 @@ def run():
         sigterm_handler_wrap(signal.SIGTERM)
 
         # create channel
-        channel_name=conf().get('channel_type', 'wx')
+        channel_name = conf().get("channel_type", "wx")
 
         if "--cmd" in sys.argv:
-            channel_name = 'terminal'
+            channel_name = "terminal"
 
-        if channel_name == 'wxy':
-            os.environ['WECHATY_LOG']="warn"
+        if channel_name == "wxy":
+            os.environ["WECHATY_LOG"] = "warn"
             # os.environ['WECHATY_PUPPET_SERVICE_ENDPOINT'] = '127.0.0.1:9001'
 
         channel = channel_factory.create_channel(channel_name)
-        if channel_name in ['wx','wxy','terminal','wechatmp','wechatmp_service']:
+        if channel_name in ["wx", "wxy", "terminal", "wechatmp", "wechatmp_service"]:
             PluginManager().load_plugins()
 
         # startup channel
@@ -47,5 +52,6 @@ def run():
         logger.error("App startup failed!")
         logger.exception(e)
 
-if __name__ == '__main__':
-    run()
+
+if __name__ == "__main__":
+    run()

bot/baidu/baidu_unit_bot.py

@@ -1,6 +1,7 @@
 # encoding:utf-8
 
 import requests
+
 from bot.bot import Bot
 from bridge.reply import Reply, ReplyType
 
@@ -9,20 +10,35 @@
 class BaiduUnitBot(Bot):
     def reply(self, query, context=None):
         token = self.get_token()
-        url = 'https://aip.baidubce.com/rpc/2.0/unit/service/v3/chat?access_token=' + token
-        post_data = "{\"version\":\"3.0\",\"service_id\":\"S73177\",\"session_id\":\"\",\"log_id\":\"7758521\",\"skill_ids\":[\"1221886\"],\"request\":{\"terminal_id\":\"88888\",\"query\":\"" + query + "\", \"hyper_params\": {\"chat_custom_bot_profile\": 1}}}"
+        url = (
+            "https://aip.baidubce.com/rpc/2.0/unit/service/v3/chat?access_token="
+            + token
+        )
+        post_data = (
+            '{"version":"3.0","service_id":"S73177","session_id":"","log_id":"7758521","skill_ids":["1221886"],"request":{"terminal_id":"88888","query":"'
+            + query
+            + '", "hyper_params": {"chat_custom_bot_profile": 1}}}'
+        )
         print(post_data)
-        headers = {'content-type': 'application/x-www-form-urlencoded'}
+        headers = {"content-type": "application/x-www-form-urlencoded"}
         response = requests.post(url, data=post_data.encode(), headers=headers)
         if response:
-            reply = Reply(ReplyType.TEXT, response.json()['result']['context']['SYS_PRESUMED_HIST'][1])
+            reply = Reply(
+                ReplyType.TEXT,
+                response.json()["result"]["context"]["SYS_PRESUMED_HIST"][1],
+            )
             return reply
 
     def get_token(self):
-        access_key = 'YOUR_ACCESS_KEY'
-        secret_key = 'YOUR_SECRET_KEY'
-        host = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=' + access_key + '&client_secret=' + secret_key
+        access_key = "YOUR_ACCESS_KEY"
+        secret_key = "YOUR_SECRET_KEY"
+        host = (
+            "https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id="
+            + access_key
+            + "&client_secret="
+            + secret_key
+        )
         response = requests.get(host)
         if response:
             print(response.json())
-            return response.json()['access_token']
+            return response.json()["access_token"]

bot/bot.py

@@ -8,7 +8,7 @@
 
 
 class Bot(object):
-    def reply(self, query, context : Context =None) -> Reply:
+    def reply(self, query, context: Context = None) -> Reply:
         """
         bot auto-reply content
         :param req: received message

bot/bot_factory.py

@@ -13,20 +13,24 @@ def create_bot(bot_type):
     if bot_type == const.BAIDU:
         # Baidu Unit对话接口
         from bot.baidu.baidu_unit_bot import BaiduUnitBot
+
         return BaiduUnitBot()
 
     elif bot_type == const.CHATGPT:
         # ChatGPT 网页端web接口
         from bot.chatgpt.chat_gpt_bot import ChatGPTBot
+
         return ChatGPTBot()
 
     elif bot_type == const.OPEN_AI:
         # OpenAI 官方对话模型API
         from bot.openai.open_ai_bot import OpenAIBot
+
         return OpenAIBot()
 
     elif bot_type == const.CHATGPTONAZURE:
         # Azure chatgpt service https://azure.microsoft.com/en-in/products/cognitive-services/openai-service/
         from bot.chatgpt.chat_gpt_bot import AzureChatGPTBot
+
         return AzureChatGPTBot()
     raise RuntimeError