# LangChat/langchat

LangChat: Java LLMs/AI Project, Supports Multi AI Providers( Gitee AI/ 智谱清言 / 阿里通义 / 百度千帆 / DeepSeek / 抖音豆包 / 零一万物 / 讯飞星火 / OpenAI / Gemini / Ollama / Azure / Claude 等大模型), Java生态下AI大模型产品解决方案，快速构建企业级AI知识库、AI机器人应用

Repository: https://github.com/LangChat/langchat
Canonical: https://ross.abutalabs.com/products/langchat
Homepage: http://langchat.cn
Language: Java
License: NOASSERTION
License Family: other
Last push: 2025-11-05T10:33:58+00:00

## Health v2 (maintenance only)
Score: 46/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 50, release rhythm 28, longevity 66
- inputs: {"age_days": 937, "days_push": 301, "days_rel": 567, "gap_med": 43.5, "n_releases_24m": 5}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1276, forks 254 (observed 2026-08-28T04:04:13.150610+00:00)

## What it is
LangChat is a Java-based enterprise AIGC platform for building AI knowledge bases, chatbots, and agent applications with multi-provider LLM support (OpenAI, DeepSeek, Gemini, Ollama, Claude, and Chinese providers). It integrates RBAC, RAG retrieval, MCP/plugin extensions, and offers a commercial Pro edition with visual workflow orchestration and sandboxed Skills execution.

## Use cases
- build an enterprise AI knowledge base in Java
- create a company chatbot with RAG over internal documents
- self-host an AI assistant behind our firewall
- switch between multiple LLM providers like DeepSeek and OpenAI
- build AI agents with MCP and plugin tool calling
- deploy a private ChatGPT alternative for my team
- add vector search and document Q&A to a Java app

## When to choose
- you need a Java/JVM-stack LLM application platform
- you want a self-hosted, RBAC-protected enterprise AI knowledge base
- you need multi-provider LLM support including Chinese models
- you want RAG, agents, and MCP integration out of the box

## When to avoid
- you need visual workflow orchestration, sandboxed Skills, or Text2SQL, which are commercial-Pro-only
- you want a Python/Node ecosystem rather than Java
- you need a lightweight library to embed rather than a full application platform
- strict open-source licensing matters, since the license is marked NOASSERTION despite Apache 2.0 claims

## Facets
- artifact type: application
- maturity: active
- function: rag, chatbot, agent-framework, llm-inference, mcp, chat-interface, web-framework
- domain: large-language-models, artificial-intelligence, chatbots, self-hosted, web-development
- platform: jvm, self-hosted, cross-platform
- tags: java, llm-ops, knowledge-base, multi-provider, enterprise-ai, aigc, langchain4j, rbac, workflow-orchestration, commercial-open-source, retrieval-augmented-generation, ai-agents, web-server, docker

## Member repositories
- LangChat/langchat (main) score 46

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:13.150610+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 2026-08-30T05:02:53.668398+00:00, confidence not recorded.
  - readme: https://github.com/LangChat/langchat (fetched 2026-08-28T04:04:13.150610+00:00, sha fd08151bfbc3)
  - homepage: http://langchat.cn (fetched 2026-08-29T12:13:59.612634+00:00, sha 47ed5cbbe201)
  - site_page: https://langchat.cn/about (fetched 2026-08-29T12:13:59.623860+00:00, sha 8353e4e723d9)
  - site_page: https://langchat.cn/pricing (fetched 2026-08-29T12:13:59.621422+00:00, sha ebd8753d528e)
- Data as of 2026-08-30T08:39:29.467469+00:00.