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package storage
import (
"elefant/models"
"fmt"
"log"
"unsafe"
sqlite_vec "github.com/asg017/sqlite-vec-go-bindings/ncruces"
)
type VectorRepo interface {
WriteVector(*models.VectorRow) error
SearchClosest(q [5120]float32) (*models.VectorRow, error)
}
var vecTableName = "embeddings"
func (p ProviderSQL) WriteVector(row *models.VectorRow) error {
stmt, _, err := p.s3Conn.Prepare(
fmt.Sprintf("INSERT INTO %s(embedding, slug, raw_text) VALUES (?, ?, ?)", vecTableName))
defer stmt.Close()
if err != nil {
p.logger.Error("failed to prep a stmt", "error", err)
return err
}
v, err := sqlite_vec.SerializeFloat32(row.Embeddings)
if err != nil {
p.logger.Error("failed to serialize vector",
"emb-len", len(row.Embeddings), "error", err)
return err
}
stmt.BindInt(1, int(row.ID))
stmt.BindBlob(2, v)
stmt.BindText(3, row.Slug)
stmt.BindText(4, row.RawText)
err = stmt.Exec()
if err != nil {
p.logger.Error("failed exec a stmt", "error", err)
return err
}
return nil
}
func decodeUnsafe(bs []byte) []float32 {
return unsafe.Slice((*float32)(unsafe.Pointer(&bs[0])), len(bs)/4)
}
func (p ProviderSQL) SearchClosest(q [5120]float32) (*models.VectorRow, error) {
stmt, _, err := p.s3Conn.Prepare(`
SELECT
id,
distance,
embedding,
slug,
raw_text
FROM vec_items
WHERE embedding MATCH ?
ORDER BY distance
LIMIT 4
`)
if err != nil {
log.Fatal(err)
}
query, err := sqlite_vec.SerializeFloat32(q[:])
if err != nil {
log.Fatal(err)
}
stmt.BindBlob(1, query)
resp := make([]models.VectorRow, 4)
i := 0
for stmt.Step() {
resp[i].ID = uint32(stmt.ColumnInt64(0))
resp[i].Distance = float32(stmt.ColumnFloat(1))
emb := stmt.ColumnRawText(2)
resp[i].Embeddings = decodeUnsafe(emb)
resp[i].Slug = stmt.ColumnText(3)
resp[i].RawText = stmt.ColumnText(4)
i++
}
if err := stmt.Err(); err != nil {
log.Fatal(err)
}
err = stmt.Close()
if err != nil {
log.Fatal(err)
}
return nil, nil
}
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