RuoYi AI
ActiveDescription
An out-of-the-box enterprise full-stack AI assistant platform with Langchain4j-based Supervisor multi-agent orchestration, RAG knowledge bases, visual workflow design, and multi-model management.
Key Features
- Multi-agent orchestration — Supervisor mode on Langchain4j with multiple decision models that combine tools and skills flexibly
- RAG knowledge management — local RAG with Milvus/Weaviate/Qdrant vector stores, document parsing, and retrieval QA
- Visual workflow designer — drag-and-drop node orchestration with SSE streaming for model calls, email, and human-approval nodes
- Multi-model and platform integration — DeepSeek, Zhipu, OpenAI built in, plus Coze, Dify, FastGPT, and RAGFlow bridges
- Full-stack delivery — backend, user frontend, admin panel, and mini-app repos with one-command Docker Compose startup
Use Cases
💡 Stand up a private enterprise assistant for customers and staff with fully self-owned data and models
💡 Chain model calls, email notifications, and human approvals into automated workflows with the visual designer
💡 Load product docs and policies into the RAG knowledge base for accurate frontline Q&A
💡 Extend on the familiar RuoYi Java stack and integrate smoothly with existing enterprise systems
Strengths & Limitations
✅ Strengths
- • Actively maintained, recent updates
- • High community interest (5.7k stars)
- • Permissive open-source license (MIT)
- • Established track record (2 years in production)
Tags
Categories
Quick Start
# Clone and pin the image version
git clone --depth 1 --branch v3.1.0 https://github.com/ageerle/ruoyi-ai.git
cd ruoyi-ai && 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 up -d