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Basic Information

RuoYi AI is an enterprise-grade, full-stack AI assistant platform designed to help organizations build, deploy, and operate AI-powered applications. The repository provides a backend service with front-end integrations and ready modules to create chatbots, knowledge-driven assistants, and AI applications that combine multiple model providers and RAG (retrieval-augmented generation) capabilities. It targets developers and teams who need an out-of-the-box AI platform that integrates mainstream model providers and vector databases while supporting local deployment and data privacy. The project bundles production-ready components such as document processing, real-time streaming interfaces, and administrative UIs so teams can quickly prototype, extend, and operate AI solutions in enterprise environments.

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Features
The project includes multi-model support for providers like OpenAI GPT-4, Azure, ChatGLM, and other Chinese models. It deeply integrates third-party AI platforms such as FastGPT, Coze (扣子) and DIFY, and supports Spring AI MCP for an extensible tool ecosystem. RAG capabilities are built using Langchain4j and a Chinese vector model (BGE-large-zh-v1.5), with compatibility for Milvus, Weaviate and Qdrant vector stores. The stack offers local inference options compatible with Ollama and vLLM, real-time streaming via SSE/WebSocket, document parsing for PDF/Word/Excel, AI image generation integrations (DALL·E-3, MidJourney, Stable Diffusion), intelligent PPT generation, and an AI programming assistant for code analysis and scaffolding.
Use Cases
RuoYi AI helps organizations accelerate AI adoption by providing a consolidated platform for building conversational agents, private knowledge bases, and AI-enhanced workflows. It enables secure, controllable deployments with local RAG and vector DB options to protect sensitive data. Developers benefit from unified chat interfaces, multi-platform load balancing, and integrations that reduce connector and orchestration work. The included document processing and multimodal capabilities simplify ingestion of enterprise content, while real-time streaming and admin UIs support production usage. The project also offers demos, documentation and cooperation templates to shorten development cycles and support extension for business-specific AI services.

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