JaneaSystems/jecq
Faiss-based library for efficient similarity search
This is a library for developers to efficiently search through large collections of high-dimensional vectors. It takes dense vectors as input and outputs a list of the most similar vectors, but with a significantly reduced memory footprint. Developers building applications like recommendation engines, semantic search, or RAG systems would use this to manage large vector databases more cost-effectively.
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Use this if you are a developer working with large collections of dense vectors and need to reduce memory usage while maintaining high search accuracy for your application.
Not ideal if your application requires GPU-based search acceleration or needs distance metrics other than inner product.
Stars
57
Forks
1
Language
C++
License
MIT
Category
Last pushed
Jul 31, 2025
Commits (30d)
0
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