ruoyi-ai and langchain4j-aideepin
Both are AI application development frameworks, with project A providing an enterprise-grade, multi-vendor LLM management and agent skill orchestration platform, while project B focuses on AI-based productivity tools encompassing chat, drawing, RAG, and workflow functionalities.
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 langchain4j-aideepin
moyangzhan/langchain4j-aideepin
基于AI的工作效率提升工具（聊天、绘画、知识库、工作流、 MCP服务市场、语音输入输出、长期记忆） | Ai-based productivity tools (Chat,Draw,RAG,Workflow,MCP marketplace, ASR,TTS, Long-term memory etc)
Built on LangChain4j and LangGraph4j, it provides a modular backend architecture supporting multiple AI model platforms (OpenAI, DeepSeek, Qwen, Ollama) with pluggable vector storage (PostgreSQL with pgvector or Neo4j) and graph databases for knowledge representation. The system enables hybrid RAG through both semantic vector search and knowledge graph traversal, with configurable multi-modal I/O including ASR/TTS voice interactions and flexible storage backends (local or Alibaba OSS).
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