ruoyi-ai
An enterprise AI development framework for building AI agents. It provides unified management of multi-provider LLMs, secure enterprise knowledge bases with high-precision retrieval, visual workflow orchestration and multi-agent coordination.
Install / Use
claude mcp add ageerle -- npx -y github:ageerle/ruoyi-aiIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AutomationSupported Platforms
Tags
Skill content
View source on GitHubRuoYi AI
<div align="center">
[![MIT License][license-shield]][license-url]
Enterprise-Grade AI Assistant Platform
An out-of-the-box full-stack AI platform supporting multi-agent collaboration, Supervisor mode orchestration, and multiple decision models, with advanced RAG technology and visual workflow orchestration capabilities
中文 | 📖 Documentation | 🚀 Live Demo | 🐛 Report Issues | 💡 Feature Requests
</div>🚀 Live Demo
| Service | URL | Default Account | |---|---|---| | Admin Panel | http://129.226.199.247:25666 | admin / admin123 | | User Frontend | http://129.226.199.247:25137 | admin / admin123 | | Commercial Edition | https://web.ruoyiai.chat | WeChat QR code login |
✨ Core Features
| Module | Current Capabilities | |:---:|---| | Model Management | Multi-model integration (DeepSeek/Zhipu/MIMO/Bailian/OpenAI), multi-modal understanding, Coze/DIFY/FastGPT/RAGFlow platform integration | | Knowledge Management | Local RAG + Vector DB (Milvus/Weaviate/Qdrant) + Document parsing | | Tool Management | MCP protocol integration, Skills capability + Extensible tool ecosystem | | Workflow Orchestration | Visual workflow designer, drag-and-drop node orchestration, SSE streaming execution, currently supports model calls, email sending, manual review, and other nodes | | Multi-Agent | Agent framework based on Langchain4j, Supervisor mode orchestration, supports multiple decision models, can flexibly combine tools and skills |
Project Repositories
| Module | GitHub Repository | Gitee Repository | GitCode Repository | |----------|-------------------------------------------------------|------------------------------------------------------|--------------------------------------------------------| | 🔧 Backend | ruoyi-ai | ruoyi-ai | ruoyi-ai | | 🎨 User Frontend | ruoyi-web | ruoyi-web | ruoyi-web | | 🛠️ Admin Panel | ruoyi-admin | ruoyi-admin | ruoyi-admin | | 🎬 Drama | ruoyi-drama | ruoyi-drama | ruoyi-drama | | 🤖 Copilot | ruoyi-copilot | ruoyi-copilot | ruoyi-copilot | | 📱 Mini-App | ruoyi-uniapp | ruoyi-uniapp | ruoyi-uniapp |
Partner Projects
| Project Name | GitHub Repository | Gitee Repository | |----------------|-------------------------------------------------------|------------------------------------------------------| | element-plus-x | element-plus-x | element-plus-x |
🛠️ Technical Architecture
Core Framework
- Backend: Spring Boot 3.5.8 + Langchain4j
- Data Storage: MySQL 8.0 + Redis + Vector Databases (Milvus/Weaviate/Qdrant)
- Frontend: Vue 3 + Vben Admin + element-plus-x
- Security: Sa-Token + JWT dual-layer security
- Document Processing: PDF, Word, Excel parsing, intelligent image analysis
- Real-time Communication: WebSocket real-time communication, SSE streaming response
- System Monitoring: Comprehensive logging system, performance monitoring, service health checks
🐳 Docker Deployment
This project provides two Docker deployment methods:
Method 1: One-click Start All Services (Recommended)
Use docker-compose-all.yaml to start all services at once (including backend, admin panel, user frontend, and dependencies):
# Requirements: Docker Engine and Docker Compose V2
# Clone the v3.1.0 release
git clone --depth 1 --branch v3.1.0 https://github.com/ageerle/ruoyi-ai.git
cd ruoyi-ai
# Pin the image version. Public GHCR images do not require docker login.
cp docs/docker/ruoyi-ai/.env.example docs/docker/ruoyi-ai/.env
sed -i 's/^RUIYI_VERSION=.*/RUIYI_VERSION=v3.1.0/' docs/docker/ruoyi-ai/.env
# Pull pre-built images from GHCR and start all services
docker compose --env-file docs/docker/ruoyi-ai/.env \
-f docs/docker/ruoyi-ai/docker-compose-all.yaml pull
docker compose --env-file docs/docker/ruoyi-ai/.env \
-f docs/docker/ruoyi-ai/docker-compose-all.yaml up -d
# Check service status
docker compose --env-file docs/docker/ruoyi-ai/.env \
-f docs/docker/ruoyi-ai/docker-compose-all.yaml ps
# Access services (replace SERVER_IP with the server address)
# Admin Panel: http://SERVER_IP:25666 (admin / admin123)
# User Frontend: http://SERVER_IP:25137
# Backend API: http://SERVER_IP:26039
The default Compose file also publishes MySQL (23306), Redis (26379),
Weaviate (28080), and MinIO (29000/29090). For production deployments,
change the default MySQL and MinIO passwords and expose only the application
ports through the firewall or a reverse proxy.
To upgrade to another published release, update RUIYI_VERSION in
docs/docker/ruoyi-ai/.env, then run docker compose pull and
docker compose up -d with the same --env-file and -f options. Do not use
docker compose down -v unless you intend to delete persistent data volumes.
Method 2: Step-by-step Deployment (Source Build)
If you need to build backend services from source, follow these steps:
Step 1: Deploy Backend Service
# Enter backend project directory
cd ruoyi-ai
# Start backend service (build from source)
docker-compose up -d --build
# Wait for backend service to start
docker-compose logs -f backend
Step 2: Deploy Admin Panel
# Enter admin panel project directory
cd ruoyi-admin
# Build and start admin panel
docker-compose up -d --build
# Access admin panel
# URL: http://localhost:5666
Step 3: Deploy User Frontend (Optional)
# Enter user frontend project directory
cd ruoyi-web
# Build and start user frontend
docker-compose up -d --build
# Access user frontend
# URL: http://localhost:5137
Service Ports
| Service | One-click Port | Step-by-step Port | Description | |------|-------------|-------------|------| | Admin Panel | 25666 | 5666 | Admin backend access | | User Frontend | 25137 | 5137 | User frontend access | | Backend Service | 26039 | 6039 | Backend API service | | MySQL | 23306 | 23306 | Database service | | Redis | 26379 | 6379 | Cache service | | Weaviate | 28080 | 28080 | Vector database | | MinIO API | 29000 | 9000 | Object storage API | | MinIO Console | 29090 | 9090 | Object storage console |
📚 Documentation
Want to learn more about installation, deployment, configuration, and secondary development?
🤝 Contributing
We warmly welcome community contributions! Whether you are a seasoned developer or just getting started, you can contribute to the project 💪
How to Contribute
- Fork the project to your account
- Create a branch (
git checkout -b feature/new-feature-name) - Commit your changes (
git commit -m 'Add new feature') - Push to the branch (
git push origin feature/new-feature-name) - Create a Pull Request
💡 Tip: We recommend submitting PRs to GitHub, we will automatically sync to other code hosting platforms
📄 License
This project is licensed under the MIT License. See the LICENSE file for details.
🙏 Acknowledgments
Thanks to the following excellent open-source projects for their support:
- Langchain4j - Powerful Java LLM development framework
- RuoYi-Vue-Plus - Mature enterprise-level rapid development framework
- Vben Admin - Modern Vue admin template
💎 Sponsors
Thanks to the following sponsors for supporting this project:
<a href="https://www.atlascloud.ai?ref=89F97E"> <img src="docs/image/sponsor/atlascloud_banner.png" alt="Atlas Cloud" width="160" height="80"> </a>Visit Atlas Cloud · Coding Plan Promotion A full-modal AI inference platform that gives developers a unified AI API, supporting video generation, image generation, and LLMs. Connect once to access 300+ curated models.
<a href="https://www.volcengine.com/activity/codingplan?utm_campaign=hw&utm_content=hw&utm_medium=devrel_tool_web&utm_source=OWO&utm_term=ageerle-ruoyi-ai"> <img src="docs/image/sponsor/huoshan.png" alt="Volcengine CodingPlan" width="160" height="80"> </a>Sign up to claim 25 million tokens — go now Enjoy ByteDance's in-house Doubao models plus full-power open-source SOTA models, covering text, VLM, and image generation — all modalities in one stop: Seed-2.1, Seedream-5.0, GLM-5.2, DeepSeek, and more. Not just for coding — it can also tackle complex long-horizon Agent tasks!
💬 Community Chat
<div align="center"> <table> <tr> <td align="center"> <img src="docs/image/wx.png" alt="WeChat QR Code" width="200" height="200"><br> <strong>Scan to add author on WeChat</strong><br> <em>Join group for learning</em> </td> <td align="center"> <img src="docs/image/douyin.png" alt="Douyin QR Code" width="200" height="200"><br> <strong>Douyin Video Tutorials</strong><br> <em>Open Douyin, scan & follow to watch video tutorials</em> </td> <td align="center"> <img src="docs/image/qq.png" alt="QQ Group QR Code" width="200" height="200"><br> <strong>QQ Tech Exchange Group</strong><br> <em>Technical discussion</em> </td> </tr> </table> </div><div align="center">
⭐ Star to Support • Fork to Contribute • 📚 中文 • 📖 Complete Documentation
Built with ❤️, maintained by the RuoYi AI open-source community
</div> <!-- Badge Links -->Truncated for display — read the full file on GitHub.
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