- 自动签到 — 自动完成签到(模拟通过 APP 扫二维码进入课堂)
- 自动答题 — 支持单选、多选、投票和简答题,可配置答题策略(随机、空白或 AI)
- 自动弹幕 — 当一段时间内出现超过特定条数的相同弹幕时自动跟发
- 自动抢红包 — 收到红包时自动抢
- 点名提醒 — 点名时发送通知提醒
- 语音通知 — 支持语音播报课程事件
- 手机推送 — 支持 PushDeer 将课堂事件推送到手机(支持自建服务器)
- 分课程设置 — 对每门课程进行精细化的自动化控制
- 多服务器支持 — 支持多个雨课堂服务器
- 多账号支持 — 支持同时登录多个账号
- 多平台支持 — 提供 Windows、macOS、Linux 可执行文件,支持 Python 源码运行和 Docker 部署
- 双语界面 — 支持中英文切换
- STAR 此项目()
- 前往 Releases 页面,下载对应平台的可执行文件
- 运行可执行文件,浏览器会自动打开 http://localhost:8500
Tip
macOS/linux 用户需先运行 chmod +x YuketangHelper-<OS>-<VERSION>(自行补全文件名); macOS 用户如遇安全提示请前往 系统设置 → 隐私与安全性 点击"仍要打开"
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下载源代码 ZIP 并解压,或使用 Git Clone
-
在项目根目录下运行:
python start.py
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在浏览器中打开 http://localhost:5173 即可使用
-
下载并安装 Docker
-
打开 Docker 并拉取镜像
docker pull dvdyyz/yuketang-helper:latest -
运行:
docker run -d --name yuketang-helper --restart unless-stopped -p 8500:8500 -v yuketang-data:/data dvdyyz/yuketang-helper:latest
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在浏览器中打开 http://localhost:8500 即可使用
Tip
服务器部署可通过端口转发在本地浏览器访问; 服务器推荐使用账号密码登录,以获得更长久的登录状态; 如需24小时服务器运行,可联系作者。
- 可执行文件:关闭终端窗口
- Python:运行
python stop.py - Docker:运行
docker stop yuketang-helper
- ModelScope: 登录 ModelScope,前往访问控制,点击 新建访问令牌
Important
使用 ModelScope API 需同时满足以下两点,否则即使创建了访问令牌也无法调用模型 API,本助手会调用失败:
- 在 ModelScope 账号设置 中绑定阿里云账号
- 完成实名认证
- Google: 登录 Google AI Studio,进入 Get API Key page,点击 Create API Key
- 支持多种 LLM API
- 支持填空题答题
- 自动预习
- 自动刷回放
- Based on RainClassroomAssitant and THU-Yuketang-Helper
- Auto Sign-in — Automatically checks in (simulates scanning the QR code via the app to enter the classroom)
- Auto Quiz Answering — Handles single/multiple choice, voting, and short-answer questions with configurable strategies (random, blank, or AI)
- Auto Danmu — Automatically follows up when more than a configured number of identical danmu appear within a period of time
- Auto Red Packet — Automatically grabs red packets when received
- Roll Call Notifications — Alerts you when roll call happens
- Voice Notifications — Text-to-speech announcements for lesson events
- Mobile Push — Push lesson events to your phone via PushDeer (self-hosted servers supported)
- Per-Course Settings — Fine-grained control over automation for each course
- Multi-Server Support — Supports multiple Yuketang servers
- Multi-Account Support — Supports logging in with multiple accounts simultaneously
- Multi-Platform Support — Provides Windows, macOS, and Linux executables, with support for Python source and Docker deployment
- Bilingual UI — English and Chinese interface
- STAR this project ()
- Go to the Releases page and download the executable for your platform
- Run the executable — your browser will automatically open http://localhost:8500
Tip
macOS/Linux users: run chmod +x YuketangHelper-<OS>-<VERSION> first (replace with actual filename); macOS users: if you see a security warning, go to System Settings → Privacy & Security and click "Open Anyway"
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Download source code ZIP and extract, or use Git Clone
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Run the following command in the project root directory:
python start.py
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Open http://localhost:5173 in your browser to use the app
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Download and install Docker
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Open Docker and pull the image
docker pull dvdyyz/yuketang-helper:latest -
Run:
docker run -d --name yuketang-helper --restart unless-stopped -p 8500:8500 -v yuketang-data:/data dvdyyz/yuketang-helper:latest
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Open http://localhost:8500 in your browser to use the app
Tip
Server deployments can be accessed from a local browser via port forwarding; Username/password login is recommended on servers for a more persistent session; Contact the author if you need a 24/7 server.
- Executable: Close the terminal window
- Python: Run
python stop.py - Docker: Run
docker stop yuketang-helper
- ModelScope: Log in at ModelScope, go to Access Control and click Create Your Token
Important
Using the ModelScope API requires both of the following; otherwise model API calls will fail even with a valid access token, and this helper will not be able to answer with AI:
- Bind an Alibaba Cloud account in ModelScope Account Settings
- Complete real-name verification
- Google: Log in at Google AI Studio, go to the Get API Key page, and click Create API Key
- Support multiple LLM APIs
- Support Fill-in-the-blank answering
- Auto preview
- Auto replay watching