Vector search

The vec/ sub-package is a typed Table API over sqlite-vec (bundled by modernc.org/sqlite/vec). Blank-importing vec auto-registers the extension on every connection.

import (
  _ "gosqlite.org"
  "gosqlite.org/vec"
)

tbl, _ := vec.Create(ctx, db, "docs", 8, vec.Options{Metric: vec.Cosine})
tbl.BatchInsert(ctx, items)
for m, err := range tbl.KNN(ctx, query, 5) { // streaming iter.Seq2
  if err != nil { return err }
  fmt.Println(m.Rowid, m.Distance)
}

KNNSlice is the non-streaming form. Runnable: examples/features/search/vec-search/.

• Metrics: L2, Cosine, Dot (an alias for L1), Hamming.
• Encodings: JSON, binary, and quantized int8 / bit for compact storage.
• Columns: metadata, partition-key, and auxiliary columns, plus chunk_size tuning.
• Filtering: WithFilter(predicate, args...) pushes a non-vector constraint into the KNN query (evaluated alongside MATCH).
• Keyed tables: KeyedTable[K] keys the search on a string / UUID instead of an int rowid — see examples/features/search/vec-keyed/.
• Escape hatch: KNNSQL returns the generated SQL if you need to compose it by hand.

• INSERT OR REPLACE is not honored by vec0 — use (*Table).Update for in-place replacement.
• Metadata / partition columns reject NULL (only auxiliary columns allow it).
• bit[N] needs N % 8 == 0; chunk_size must be a multiple of 8.
• The LIMIT/k is inlined as a literal because sqlite-vec’s planner needs it visible.

The full matrix of column options, metrics, encodings, and KNN forms is in dev/coverage/vec.md. For combining vector + lexical results, see Hybrid search. For the gorm sidecar, see gorm.