StarTrail-org/LEANN

Health v2 · maintenance only

Adoption not part of the score

12836 stars · 1152 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

LEANN is a low-storage vector index that enables retrieval-augmented generation (RAG) on personal devices by recomputing embeddings on the fly instead of storing them, achieving up to 97% (50x) storage savings with no accuracy loss. It ships as a Python library and CLI with integrations for Ollama, LangChain, LlamaIndex, and MCP, letting users semantically search files, emails, browser history, and documents fully offline and privately.

Use cases

• run a private RAG assistant on my laptop over my own documents
• semantic search across PDFs, emails, and files without uploading data to the cloud
• build a vector index that doesn't blow up my disk with embeddings
• chat with my local files using Ollama models offline
• index millions of documents on a personal device with minimal storage
• add retrieval-augmented generation to a LangChain or LlamaIndex app
• query my codebase or browser history locally with an MCP-connected agent

When to choose

• you need 100% private, offline RAG on a laptop or personal device
• storage overhead of traditional vector indices (FAISS, etc.) is a blocker
• you want local semantic search over heterogeneous personal data (files, email, browser history)
• you use Ollama, LangChain, LlamaIndex, or MCP and want drop-in RAG

When to avoid

• you need a distributed, multi-node vector database for server-scale deployments
• your workload demands the lowest possible query latency and can afford large storage
• you need GPU-accelerated or heavily optimized production serving today
• you require a managed service with built-in replication and sharding

Facets

library · maturity active

vector-database rag search-engine llm-inference mcp large-language-models databases privacy self-hosted windows python cli self-hosted local-rag vector-index storage-efficient semantic-search ollama personal-ai offline-first embeddings retrieval-augmented-generation search macos linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="StarTrail-org/LEANN")