http://gothub.r4focoma7gu2zdwwcjjad47ysxt634lg73sxmdbkdozanwqslho5ohyd.onion/unum-cloud/usearch
For smaller collections, we offer a more direct approach with the search method. from usearch . index import search , MetricKind , Matches , BatchMatches import numpy as np # Generate 10'000 random vectors with 1024 dimensions vectors = np . random . rand ( 10_000 , 1024 ). astype ( np . float32 ) vector = np . random . rand ( 1024 ). astype ( np . float32 ) one_in_many : Matches = search ( vectors , vector , 50 , MetricKind .