LEANN is an innovative 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 Fig → | Paper →
Ready to RAG Everything? Transform your laptop into a personal AI assistant that can semantic search your file system, emails, browser history, chat history (WeChat, iMessage), agent memory (ChatGPT, Claude), live data (Slack, Twitter), codebase*, or external knowledge bases (i.e., 60M documents) - all on your laptop, with zero cloud costs and complete privacy.
* Claude Code only supports basic grep-style keyword search. LEANN is a drop-in semantic search MCP service fully compatible with Claude Code, unlocking intelligent retrieval without changing your workflow. 🔥 Check out the easy setup →
Why LEANN?
The numbers speak for themselves: Index 60 million text chunks in just 6GB instead of 201GB. From emails to browser history, everything fits on your laptop. See detailed benchmarks for different applications below ↓
🔒 Privacy: Your data never leaves your laptop. No OpenAI, no cloud, no "terms of service".
🪶 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!
📦 Portable: Transfer your entire knowledge base between devices (even with others) with minimal cost - your personal AI memory travels with you.
📈 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.
Making Your Coding Agent Smarter
We plugged LEANN into Claude Code and compared it with BM25 on 30 SWE-Bench Pro tasks from ContextBench, keeping the model, agent, tools, and 8,192-token retrieval budget fixed.
With LEANN, the agent achieved 2.1× the initial relevant-code recall (24.2% vs. 11.4%), reached 12.6 percentage points higher relevant-code coverage after exploration (38.4% vs. 25.8%), and used 8.4% fewer tokens (3.22M vs. 3.51M).
LEANN surfaces relevant code earlier, so coding agents can spend more of their context window reasoning about the right files instead of repeatedly scanning the repository. Reproduce the benchmark →
Note: Results are macro-averaged annotated gold-line metrics over 30 SWE-Bench Pro tasks. Better context access does not guarantee issue resolution.
Installation
📦 Prerequisites: Install uv
Install uv first if you don't have it. Typically, you can install it with:
curl -LsSf https://astral.sh/uv/install.sh | sh
🚀 Quick Install
Clone the repository to access all examples and try amazing applications,
git clone https://github.com/StarTrail-org/LEANN.git leann
cd leann
and install LEANN from PyPI to run them immediately:
uv venv
source .venv/bin/activate
uv pip install leann
# CPU-only (Linux): use the `cpu` extra (e.g. `leann[cpu]`)
Linux note: if a later leann build fails with Security Violation [pathsec.open]: refusing multiply-linked file, reinstall with UV_LINK_MODE=copy uv pip install --reinstall ... (or UV_LINK_MODE=copy uv tool install --reinstall ...) - uv's default hardlink installs trip nltk's hardened file loader bundled with llama-index. Details in the FAQ.
git clone https://github.com/StarTrail-org/LEANN.git leann
cd leann
git submodule update --init --recursive
macOS:
Note: DiskANN requires MacOS 13.3 or later.
brew install libomp boost protobuf zeromq pkgconf
uv sync --extra diskann
Linux (Ubuntu/Debian):
Note: On Ubuntu 20.04, you may need to build a newer Abseil and pin Protobuf (e.g., v3.20.x) for building DiskANN. See Issue #30 for a step-by-step note.
You can manually install Intel oneAPI MKL instead of libmkl-full-dev for DiskANN. You can also use libopenblas-dev for building HNSW only, by removing --extra diskann in the command below.
sudo apt-get update && sudo apt-get install -y \
libomp-dev libboost-all-dev protobuf-compiler libzmq3-dev \
pkg-config libabsl-dev libaio-dev libprotobuf-dev \
libmkl-full-dev
uv sync --extra diskann
Linux (Arch Linux):
以上為 README 的開頭部分。其餘內容請閱讀原文。 檢視完整 README ↗
