54df6310c5
- Fix OpenMP library linking in DiskANN CMake configuration - Add timeout protection for HuggingFace model loading to prevent hangs - Improve embedding server process termination with better timeouts - Make DiskANN backend default enabled alongside HNSW - Update documentation to reflect both backends included by default
37 lines
1.2 KiB
Markdown
37 lines
1.2 KiB
Markdown
# LEANN - The smallest vector index in the world
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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**.
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## Installation
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```bash
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# Default installation (includes both HNSW and DiskANN backends)
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uv pip install leann
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```
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## Quick Start
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```python
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from leann import LeannBuilder, LeannSearcher, LeannChat
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from pathlib import Path
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INDEX_PATH = str(Path("./").resolve() / "demo.leann")
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# Build an index (choose backend: "hnsw" or "diskann")
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builder = LeannBuilder(backend_name="hnsw") # or "diskann" for large-scale deployments
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builder.add_text("LEANN saves 97% storage compared to traditional vector databases.")
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builder.add_text("Tung Tung Tung Sahur called—they need their banana‑crocodile hybrid back")
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builder.build_index(INDEX_PATH)
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# Search
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searcher = LeannSearcher(INDEX_PATH)
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results = searcher.search("fantastical AI-generated creatures", top_k=1)
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# Chat with your data
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chat = LeannChat(INDEX_PATH, llm_config={"type": "hf", "model": "Qwen/Qwen3-0.6B"})
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response = chat.ask("How much storage does LEANN save?", top_k=1)
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```
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## License
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MIT License
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