TBNilles/LEANN
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

[Readme]

Browse Source
This commit is contained in:
yichuan520030910320
2025-07-21 20:06:21 -07:00
parent 48ea5566e9
commit 5259ace111
1 changed files with 6 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
README.md
View File

@@ -12,11 +12,13 @@
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](#storage-usage-comparison)** 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 **[file system](#process-any-documents-pdf-txt-md)**, **[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?
@@ -32,7 +34,7 @@ LEANN achieves this through *graph-based selective recomputation* with *high-deg
🪶 **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:** Handle messy personal data that would crash traditional vector DBs, easily managing your growing personalized datasets.
📈 **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.