# 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)

Repository: https://github.com/moyangzhan/langchain4j-aideepin
Canonical: https://ross.abutalabs.com/products/langchain4j-aideepin
Homepage: http://www.aideepin.com
Language: Java
License: MIT
License Family: permissive
Topics: knowlege-base, langchain4j, rag, graphrag, ai-agent, ai-workflow, mcp
Last push: 2026-08-14T11:57:02+00:00

## Health v2 (maintenance only)
Score: 91/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 97, release rhythm 90, longevity 80
- inputs: {"age_days": 1121, "days_push": 19, "days_rel": 68, "gap_med": 12.5, "n_releases_24m": 37}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1361, forks 332 (observed 2026-08-28T04:04:30.079376+00:00)

## What it is
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
- artifact type: application
- maturity: active
- function: rag, chatbot, agent-framework, workflow-automation, llm-inference, speech-recognition, tts, mcp, web-framework, api-framework
- domain: artificial-intelligence, large-language-models, chatbots, self-hosted, web-development
- platform: self-hosted, jvm
- tags: 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

## Member repositories
- moyangzhan/langchain4j-aideepin (main) score 91

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:30.079376+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:41:35.824797+00:00, confidence not recorded.
  - readme: https://github.com/moyangzhan/langchain4j-aideepin (fetched 2026-08-28T04:04:30.079376+00:00, sha 6af4020dd61f)
  - homepage: http://www.aideepin.com (fetched 2026-08-29T11:59:16.670195+00:00, sha 73a3e99906fd)
- Data as of 2026-08-30T08:39:29.467469+00:00.