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Andy Lee
2025-07-21 20:13:12 -07:00
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The smallest vector index in the world. RAG Everything with LEANN!
</h2>
LEANN is a revolutionary vector database that makes personal AI accessible to everyone. Transform your laptop into a powerful RAG system that can index and search through millions of documents while using **97% less storage** than traditional solutions **without accuracy loss**.
LEANN is a revolutionary vector database that democratizes personal AI. Transform your laptop into a powerful RAG system that can index and search through millions of documents while using **[97% less storage]** than traditional solutions **without accuracy loss**.
LEANN achieves this through *graph-based selective recomputation* with *high-degree preserving pruning*, computing embeddings on-demand instead of storing them all. [Illustration →](#️-architecture--how-it-works) | [Paper →](https://arxiv.org/abs/2506.08276)
**Ready to RAG Everything?** Transform your laptop into a personal AI assistant that can search your **[file system](#process-any-documents-pdf-txt-md)**, **[emails](#search-your-entire-life)**, **[browser history](#time-machine-for-the-web)**, **[chat history](#wechat-detective)**, or external knowledge bases (i.e., 60M documents) - all on your laptop, with zero cloud costs and complete privacy.
RAG your **[emails](#-search-your-entire-life)**, **[browser history](#-time-machine-for-the-web)**, **[WeChat](#-wechat-detective)**, or 60M documents on your laptop, in nearly zero cost. No cloud, no API keys, completely private.
LEANN achieves this through *graph-based selective recomputation* with *high-degree preserving pruning*, computing embeddings on-demand instead of storing them all. [Read more →](#️-architecture--how-it-works) | [Paper →](https://arxiv.org/abs/2506.08276)
## Why LEANN?
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🔒 **Privacy:** Your data never leaves your laptop. No OpenAI, no cloud, no "terms of service".
🪶 **Lightweight:** Smart graph pruning means less storage, less memory usage, better performance on your existing hardware.
🪶 **Lightweight:** Graph-based recomputation eliminates heavy embedding storage, while smart graph pruning and CSR format minimize graph storage overhead. Always less storage, less memory usage!
📈 **Scalability:** Organize our messy personal data that would crash traditional vector DBs, with performance that gets better as your data grows more personalized.
📈 **Scalability:** Handle messy personal data that would crash traditional vector DBs, easily managing your growing personalized data and agent generated memory!
✨ **No Accuracy Loss:** Maintain the same search quality as heavyweight solutions while using 97% less storage.
## Quick Start in 1 minute
```bash
git clone git@github.com:yichuan520030910320/LEANN-RAG.git leann
git clone git@github.com:yichuan-w/LEANN.git leann
cd leann
git submodule update --init --recursive
```
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LEANN supports RAGing a lot of data sources, like .pdf, .txt, .md, and also supports RAGing your WeChat, Google Search History, and more.
### 📚 Process Any Documents (.pdf, .txt, .md)
### Process Any Documents (.pdf, .txt, .md)
Above we showed the Python API, while this CLI script demonstrates the same concepts while directly processing PDFs and documents.
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**Works with any text format** - research papers, personal notes, presentations. Built with LlamaIndex for document parsing.
### 🕵️ Search Your Entire Life
### Search Your Entire Life
```bash
python examples/mail_reader_leann.py
# "What did my boss say about the Christmas party last year?"
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- "Show me emails about travel expenses"
</details>
### 🌐 Time Machine for the Web
### Time Machine for the Web
```bash
python examples/google_history_reader_leann.py
# "What was that AI paper I read last month?"
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</details>
### 💬 WeChat Detective
### WeChat Detective
```bash
python examples/wechat_history_reader_leann.py