ruoyi-ai and dive-into-spring-ai
One project is an enterprise-grade AI application development framework supporting various large language models and agent skills, while the other is an educational resource for learning Spring AI, making them ecosystem siblings, with the latter potentially teaching how to use technologies that could be integrated into solutions built with the former.
About ruoyi-ai
ageerle/ruoyi-ai
面向企业级市场的一站式AI应用开发框架，支持多厂商大模型统一接入与管理，具备安全可控的企业知识库与高精度检索优化能力，提供可视化流程编排、自主决策智能体与多智能体协同调度，兼容主流 Agent Skill 协议，同时支持微信生态扩展，帮助企业与开发者零门槛快速构建安全、高效、可落地的AI智能体应用与行业解决方案。
Built on Spring Boot 4.0, Spring AI 2.0, and Langchain4j, the platform integrates multiple vector databases (Milvus, Weaviate, Qdrant) for RAG-based knowledge retrieval and supports MCP protocol tools alongside custom Skills. Multi-agent coordination uses a Supervisor pattern with multiple decision models, while SSE streaming and WebSocket enable real-time workflow execution with document parsing (PDF, Word, Excel) and image analysis capabilities.
About dive-into-spring-ai
qifan777/dive-into-spring-ai
《动手学SpringAI》包含SSE流/Agent智能体/知识图谱RAG/FunctionCall/历史消息/图片生成/图片理解/Embedding/VectorDatabase/RAG
Implements a full-stack Spring AI application with Redis-Stack for vector storage and Neo4j for graph-based RAG, enabling semantic search across knowledge graphs. Covers advanced patterns including streaming responses via SSE, multi-turn conversation memory, tool/function calling for AI agents, and multimodal capabilities (image generation and understanding). Requires Java 17+ and includes a Node.js frontend for interactive demonstrations of embedding, retrieval, and knowledge graph query workflows.
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