MinishLab/vicinity

Lightweight Nearest Neighbors with Flexible Backends

49
/ 100
Emerging

This tool helps data practitioners efficiently find the most similar items within a large collection of data. You input a list of items and their numerical representations (vectors), along with a query item, and it outputs the top matching items. This is ideal for anyone working with embeddings to find similar text, images, products, or recommendations.

334 stars. Available on PyPI.

Use this if you need a consistent way to experiment with and evaluate different nearest neighbor search methods for your vector data.

Not ideal if your primary need is to frequently delete items from your collection, as many underlying methods require re-indexing for deletions.

similarity-search recommendation-systems information-retrieval data-matching vector-search
Maintenance 6 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 8 / 25

How are scores calculated?

Stars

334

Forks

10

Language

Python

License

MIT

Last pushed

Dec 30, 2025

Commits (30d)

0

Dependencies

3

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curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/MinishLab/vicinity"

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