ejaasaari/lorann
Approximate Nearest Neighbor search using reduced-rank regression, with extremely fast queries, tiny memory usage, and rapid indexing on modern vector embeddings.
This tool helps machine learning engineers and data scientists quickly find the most similar items within large datasets. You input a collection of high-dimensional numerical data, like image or text embeddings, and it rapidly returns the items most closely matching a specific query. It's designed for users working with modern AI models and large-scale data.
Available on PyPI.
Use this if you need extremely fast nearest neighbor searches on large, high-dimensional embedding datasets, while also minimizing memory usage.
Not ideal if your data is not numerical, low-dimensional, or if your primary concern is perfectly exact matches rather than speed and efficiency.
Stars
51
Forks
3
Language
C++
License
MIT
Category
Last pushed
Dec 11, 2025
Commits (30d)
0
Dependencies
1
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