stephantul/reach
Load embeddings and featurize your sentences.
Provides a lightweight, numpy-backed vector store optimized for RAG systems with sub-millisecond similarity search on 100K+ vectors. Integrates seamlessly with embedding models like model2vec, enabling quick disk serialization for ephemeral retrieval tasks without requiring persistent database infrastructure. Designed for scalability up to ~1M vectors before requiring heavier alternatives.
31 stars and 3,631 monthly downloads. No commits in the last 6 months. Available on PyPI.
Stars
31
Forks
7
Language
Python
License
MIT
Category
Last pushed
Oct 23, 2024
Monthly downloads
3,631
Commits (30d)
0
Dependencies
2
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curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/stephantul/reach"
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