RuoYi AI is a full-stack AI development platform designed to help developers rapidly build and deploy personalized AI applications. It offers a comprehensive suite of tools for creating AI assistants, integrating local RAG capabilities, and extending functionality with plugins, targeting developers seeking a robust and extensible AI application framework.

How It Works

The platform provides a complete system including user-facing applications, a backend management system, and a mini-program, all under the MIT license. It features a local RAG solution leveraging Milvus/Weaviate, local vectorization models, and Ollama for privacy-focused data processing. Functionality is extended through plugins for internet access, SQL querying, and Text2API, alongside support for various LLMs via SSE and WebSocket, and integrated AI image generation with MidJourney and DALL-E.

Quick Start & Requirements

• Backend: Java 17, MySQL 5.7/8.0, Redis >= 5.X, Maven 3.8+
• Frontend: Node.js 20+, pnpm
• Deployment: Docker is available.
• Documentation: https://doc.pandarobot.chat/
• Demo: User: https://web.pandarobot.chat/, Admin: https://admin.pandarobot.chat/ (admin/admin123)

Highlighted Details

• Full-stack AI assistant platform with user, admin, and mini-program frontends.
• Local RAG implementation using Milvus/Weaviate, local models, and Ollama.
• Extensible plugin system for web search, SQL, and Text2API.
• Integrated AI image generation (MidJourney, DALL-E), translation, PPT generation, and voice cloning.

Maintenance & Community

• Active development with community contributions encouraged.
• QQ groups and WeChat for technical discussions.
• Roadmap includes frontend simplification, Agent2Agent support, and visual flow orchestration.

Licensing & Compatibility

• MIT License for the core system, allowing commercial use and closed-source linking.
• Note: The README mentions the vben template is a paid component and not included by default.

Limitations & Caveats

The project is described as being in its early stages, with development speed limited by individual effort. The vben frontend template is a paid component and not included in the open-source release.