RuoYi AI

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

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✨ Core Features

🚀 Quick Start

Live Demo

Project Repositories

Partner Projects

🛠️ 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):

# Clone the repository
git clone https://github.com/ageerle/ruoyi-ai.git
cd ruoyi-ai

# Start all services (pull pre-built images from registry)
docker-compose -f docker-compose-all.yaml up -d

# Check service status
docker-compose -f docker-compose-all.yaml ps

# Access services
# Admin Panel: http://localhost:25666 (admin / admin123)
# User Frontend: http://localhost:25137
# Backend API: http://localhost:26039

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

Image Registry

All images are hosted on Alibaba Cloud Container Registry:

crpi-31mraxd99y2gqdgr.cn-beijing.personal.cr.aliyuncs.com/ruoyi_ai

Available images: - mysql:v3 - MySQL database (includes initialization SQL) - redis:6.2 - Redis cache - weaviate:1.30.0 - Vector database - minio:latest - Object storage - ruoyi-ai-backend:latest - Backend service - ruoyi-ai-admin:latest - Admin frontend - ruoyi-ai-web:latest - User frontend

Common Commands

# Stop all services
docker-compose -f docker-compose-all.yaml down

# View service logs
docker-compose -f docker-compose-all.yaml logs -f [service-name]

# Restart a service
docker-compose -f docker-compose-all.yaml restart [service-name]

📚 Documentation

Want to learn more about installation, deployment, configuration, and secondary development?

👉 Complete Documentation

🤝 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

1. Fork the project to your account
2. Create a branch (git checkout -b feature/new-feature-name)
3. Commit your changes (git commit -m 'Add new feature')
4. Push to the branch (git push origin feature/new-feature-name)
5. 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: - Spring AI Alibaba Copilot - Intelligent coding assistant based on spring-ai-alibaba - Langchain4j - Powerful Java LLM development framework - RuoYi-Vue-Plus - Mature enterprise-level rapid development framework - Vben Admin - Modern Vue admin template

🌐 Ecosystem Partners

• PPIO Cloud - Provides cost-effective GPU computing and model API services
• Youyun Intelligent Computing - Thousands of RTX40 series GPUs + mainstream models API services, second-level response, pay-per-use, free for new customers.

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