hnswlib

HNSWlib is a header-only C++/Python library for fast, scalable Approximate Nearest Neighbor (ANN) search.

HNSWlib implements the Hierarchical Navigable Small Worlds (HNSW) algorithm, delivering highly efficient vector similarity search for high-dimensional data. This library achieves sublinear time complexity by organizing data points into a multi-layered graph structure, enabling quick jumps between layers for coarse-to-fine-grained exploration. It is a header-only C++ library with robust Python bindings, making it ideal for prototyping and production use cases involving millions of data points, such as Retrieval-Augmented Generation (RAG) and recommendation systems. Key parameters like 'M' (connections per element) and 'efConstruction' (search scope during index building) allow fine-tuning the speed-accuracy trade-off.

https://github.com/nmslib/hnswlib