semvec/pypi-packages huggingface dataset:
leann 0.3.6
LEANN - The smallest vector index in the world. RAG Everything with LEANN!
License: MIT
Requires Python: >=3.10
Keywords: vector-database, rag, embeddings, search, ai

# 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

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

## Quick Start

```python
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