Ross ROSS = Recommend OSS · open-source software intelligence for agents

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) observed · 2026-08-28

github.com/moyangzhan/langchain4j-aideepin · homepage · Java · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

91/100

  • Activity 97
  • Release rhythm 90
  • Longevity 80
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 12.5
  • age_days: 1121
  • days_rel: 68
  • days_push: 19
  • n_releases_24m: 37

Full methodology

Adoption not part of the score

1361 stars · 332 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LangChain4j-AIDeepin is an open-source, self-hostable AI application platform built on Spring Boot, LangChain4j, and LangGraph4j with Vue 3 frontends. It bundles AI chat, image generation, RAG knowledge bases (vector and knowledge-graph retrieval), a visual workflow editor, an MCP service marketplace, ASR/TTS, and short/long-term memory for building intelligent business assistants.

Use cases

  • build a self-hosted ai chat assistant with a knowledge base
  • create a rag chatbot over company documents
  • design ai workflows with a visual editor
  • connect mcp tools to an ai assistant
  • add voice input and output to an ai chat app
  • generate images from text prompts with multiple model providers
  • give an ai assistant long-term memory of past conversations
  • expose characters, knowledge bases, and workflows via a rest api

When to choose

  • you want an all-in-one, self-hosted AI assistant platform with chat, RAG, and workflows
  • your stack is Java/JVM and you want to build on LangChain4j
  • you need both vector search and knowledge-graph (GraphRAG) retrieval
  • you want MCP tool integration and a marketplace out of the box
  • you need multi-provider LLM support (OpenAI, Qwen, Ollama, SiliconFlow) with streaming

When to avoid

  • you need a lightweight library to embed in an existing app rather than a full platform
  • your stack is Python-centric (LangChain, LlamaIndex ecosystems may fit better)
  • you only need a simple chatbot UI without knowledge bases or workflows
  • you require enterprise-grade scalability guarantees or commercial support

Facets

application · maturity active

rag chatbot agent-framework workflow-automation llm-inference speech-recognition tts mcp web-framework api-framework artificial-intelligence large-language-models chatbots self-hosted web-development self-hosted jvm langchain4j langgraph4j knowledge-base graphrag mcp-marketplace spring-boot ai-workflow long-term-memory image-generation asr tts retrieval-augmented-generation ai-agents web-server docker vue

2 sources

Member repositories

RepositoryRoleHealth v2
moyangzhan/langchain4j-aideepinmain91

For agents

markdown · JSON · MCP: product_card(name="moyangzhan/langchain4j-aideepin")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem