LEANN - The smallest vector index in the world

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.

Installation

# Default installation (includes both HNSW and DiskANN backends)
uv pip install leann

# CPU-only install (Linux)
uv pip install \
  --default-index https://download.pytorch.org/whl/cpu \
  --index https://pypi.org/simple \
  --index-strategy first-index \
  "leann[cpu]"

Quick Start

from leann import LeannBuilder, LeannSearcher, LeannChat
from pathlib import Path
INDEX_PATH = str(Path("./").resolve() / "demo.leann")

# Build an index (choose backend: "hnsw" or "diskann")
builder = LeannBuilder(backend_name="hnsw")  # or "diskann" for large-scale deployments
builder.add_text("LEANN saves 97% storage compared to traditional vector databases.")
builder.add_text("Tung Tung Tung Sahur called—they need their banana‑crocodile hybrid back")
builder.build_index(INDEX_PATH)

# Search
searcher = LeannSearcher(INDEX_PATH)
results = searcher.search("fantastical AI-generated creatures", top_k=1)

# Chat with your data
chat = LeannChat(INDEX_PATH, llm_config={"type": "hf", "model": "Qwen/Qwen3-0.6B"})
response = chat.ask("How much storage does LEANN save?", top_k=1)

License

MIT License