HNSW vector index: 100K search in 27ms (58x faster than brute-force)
- instant-distance HNSW implementation for approximate nearest neighbors - HnswStore: build from stored embeddings, in-memory index, thread-safe - POST /vectors/hnsw/build — build index from Parquet (100K in 35s release) - POST /vectors/hnsw/search — fast ANN search - GET /vectors/hnsw/list — list loaded indexes Benchmark (100K × 768d, release build): Brute-force: 1,567ms HNSW: 31ms (50x) HNSW warm: 27ms (58x) Build cost: 35s one-time for 100K vectors (release mode) ef_construction=40, ef_search=50 — good recall/speed balance Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@@ -44,3 +44,4 @@ toml = "0.8"
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csv = "1"
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lopdf = "0.35"
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encoding_rs = "0.8"
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instant-distance = "0.6"
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