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README.md
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The smallest vector index in the world. RAG Everything with LEANN!
</h2>
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 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)
@@ -125,15 +125,15 @@ response = chat.ask(
)
```
## Wild Things You Can Do
## RAG on Everything!
LEANN supports RAGing a lot of data sources, like .pdf, .txt, .md, and also supports RAGing your WeChat, Google Search History, and more.
LEANN supports RAG on various data sources including documents (.pdf, .txt, .md), Apple Mail, Google Search History, WeChat, and more.
### 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, and even any directory that stores your personal files!
Ask questions directly about your personal PDFs, documents, and any directory containing your files!
The following scripts use Ollama `qwen3:8b` by default, so you need `ollama pull qwen3:8b` first. For other models: `--llm openai --model gpt-4o` (requires `OPENAI_API_KEY` environment variable) or `--llm hf --model Qwen/Qwen3-4B`.
The example below asks a question about summarizing two papers (uses default data in `examples/data`):
```bash
# Drop your PDFs, .txt, .md files into examples/data/
@@ -148,8 +148,6 @@ python ./examples/main_cli_example.py
**Works with any text format** - research papers, personal notes, presentations. Built with LlamaIndex for document parsing.
### Search Your Entire Life
**Note:** You need to grant full disk access to your terminal/VS Code in System Preferences → Privacy & Security → Full Disk Access.
@@ -259,9 +257,9 @@ First, you need to install the WeChat exporter:
sudo packages/wechat-exporter/wechattweak-cli install
```
**Troubleshooting**:
- If you encounter installation issues, check the [WeChatTweak-CLI issues page](https://github.com/sunnyyoung/WeChatTweak-CLI/issues/41).
- If you encounter the error below, try restart your wechat
**Troubleshooting:**
- **Installation issues**: Check the [WeChatTweak-CLI issues page](https://github.com/sunnyyoung/WeChatTweak-CLI/issues/41)
- **Export errors**: If you encounter the error below, try restarting WeChat
```
Failed to export WeChat data. Please ensure WeChat is running and WeChatTweak is installed.
Failed to find or export WeChat data. Exiting.