head to head · open source
Langchain-Chatchat vs DeepAnalyze
Langchain-Chatchat has 38,715 GitHub stars, 6,255 forks, 26 open issues and last shipped 12 months ago. DeepAnalyze has 4,781 stars, 750 forks, 27 open issues and last shipped 3 days ago. Langchain-Chatchat leads on adoption by 710% (38,715 vs 4,781 stars). Langchain-Chatchat is written in Python under Apache-2.0; DeepAnalyze is written in Python under MIT. Langchain-Chatchat has attracted 16% as many forks as stars, DeepAnalyze 16%. DeepAnalyze was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (chatbot), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
← all 20902 open source comparisons
Side by side
| Langchain-Chatchat | DeepAnalyze | |
|---|---|---|
| GitHub stars | ★ 39K | ★ 4.8K |
| License | Apache-2.0 | MIT |
| Written in | Python | Python |
| Last push | 2025-11-10 | 2026-11-02 |
| Forks | ⑂ 6.3K | ⑂ 750 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Langchain-Chatchat if
- You weight community size — 39K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick DeepAnalyze if
- You want the DeepAnalyze feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and DeepAnalyze fits your workflow better
About Langchain-Chatchat
🌍 READ THIS IN ENGLISH 📃 LangChain Chatchat (原 Langchain ChatGLM) 基于 ChatGLM 等大语言模型与 Langchain 等应用框架实现，开源、可离线部署的 RAG 与 Agent 应用项目。 目录 概述 功能介绍 0.3.x 功能一览 已支持的模型推理框架与模型 快速上手 pip 安装部署 源码安装部署/开发部署 Docker 部署 项目里程碑 联系我们 概述 🤖️ 一种利用 langchain 思想实现的基于本地知识库的问答应用，目标期望建立一套对中文场景与开源模型支持友好、可离线运行的知识库问答解决方案。 💡 受 GanymedeNil 的项目 document.ai 和 AlexZhangji 创建的 ChatGLM 6B Pull Request 启发，建立了全流程可使用开源模型实现的本地知识库问答应用。本项目的最新版本中可使用 Xinference、Ollama 等框架接入 GLM 4 Chat、 Qwen2 Instruct、 Llama3 等模型，依托于 langchain 框架支持通过基于 FastAPI 提供的 API 调用服务，或使用基于 Streamlit 的 WebUI 进行操作。 ✅ 本项目支持市面上主流的开源 LLM、 Embedding 模型与向量数据库，可实现全部使用 开源 模型 离线私有部署…
read the full Langchain-Chatchat overview →
About DeepAnalyze
DeepAnalyze: Agentic Large Language Models for Autonomous Data Science Authors : Shaolei Zhang, Ju Fan , Meihao Fan, Guoliang Li, Xiaoyong Du Renmin University of China, Tsinghua University DeepAnalyze is the first agentic LLM for autonomous data science. It can autonomously complete a wide range of data centric tasks without human intervention, supporting: 🛠 Entire data science pipeline : Automatically perform any data science tasks such as data preparation, analysis, modeling, visualization, and report generation. 🔍 Open ended data research : Conduct deep research on diverse data sources, including…
read the full DeepAnalyze overview →
More in AI & Machine Learning
Related comparisons
More AI Interaction & Interfaces projects
Compare either of these against the rest of the AI Interaction & Interfaces field.
Frequently asked questions
Is Langchain-Chatchat or DeepAnalyze more popular?
Langchain-Chatchat has 38,715 GitHub stars and DeepAnalyze has 4,781. Langchain-Chatchat has the larger community by that measure.
Are Langchain-Chatchat and DeepAnalyze free?
Both are open source. Langchain-Chatchat is licensed under Apache-2.0 and DeepAnalyze under MIT. Neither carries a licence fee.
What is the difference between Langchain-Chatchat and DeepAnalyze?
Langchain-Chatchat is written in Python and DeepAnalyze in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Langchain-Chatchat or DeepAnalyze?
Choose Langchain-Chatchat if you want the larger community (38,715 stars) or its Apache-2.0 licence terms. Choose DeepAnalyze if its feature set, stack or MIT licence fits better. Both are self-hostable.