D-Vector Search

FlatIndex keeps dense vectors in memory and ranks them with cosine similarity. save / load use the HYBRIDVS binary format (float32 or sq8).

import vector_store;
auto index = FlatIndex(384);
index.add(embedding);
auto hits = index.searchTopK(query, 5);