129 lines
2.9 KiB
Go
129 lines
2.9 KiB
Go
package storage
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import (
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"elefant/models"
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"errors"
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"fmt"
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"unsafe"
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sqlite_vec "github.com/asg017/sqlite-vec-go-bindings/ncruces"
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)
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type VectorRepo interface {
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WriteVector(*models.VectorRow) error
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SearchClosest(q []float32) ([]models.VectorRow, error)
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}
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var (
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vecTableName = "embeddings"
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vecTableName384 = "embeddings_384"
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)
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func fetchTableName(emb []float32) (string, error) {
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switch len(emb) {
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case 5120:
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return vecTableName, nil
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case 384:
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return vecTableName384, nil
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default:
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return "", fmt.Errorf("no table for the size of %d", len(emb))
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}
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}
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func (p ProviderSQL) WriteVector(row *models.VectorRow) error {
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tableName, err := fetchTableName(row.Embeddings)
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if err != nil {
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return err
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}
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stmt, _, err := p.s3Conn.Prepare(
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fmt.Sprintf("INSERT INTO %s(embedding, slug, raw_text) VALUES (?, ?, ?)", tableName))
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if err != nil {
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p.logger.Error("failed to prep a stmt", "error", err)
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return err
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}
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defer stmt.Close()
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v, err := sqlite_vec.SerializeFloat32(row.Embeddings)
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if err != nil {
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p.logger.Error("failed to serialize vector",
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"emb-len", len(row.Embeddings), "error", err)
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return err
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}
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if v == nil {
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err = errors.New("empty vector after serialization")
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p.logger.Error("empty vector after serialization",
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"emb-len", len(row.Embeddings), "text", row.RawText, "error", err)
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return err
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}
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if err := stmt.BindBlob(1, v); err != nil {
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p.logger.Error("failed to bind", "error", err)
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return err
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}
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if err := stmt.BindText(2, row.Slug); err != nil {
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p.logger.Error("failed to bind", "error", err)
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return err
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}
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if err := stmt.BindText(3, row.RawText); err != nil {
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p.logger.Error("failed to bind", "error", err)
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return err
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}
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err = stmt.Exec()
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if err != nil {
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p.logger.Error("failed exec a stmt", "error", err)
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return err
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}
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return nil
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}
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func decodeUnsafe(bs []byte) []float32 {
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return unsafe.Slice((*float32)(unsafe.Pointer(&bs[0])), len(bs)/4)
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}
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func (p ProviderSQL) SearchClosest(q []float32) ([]models.VectorRow, error) {
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tableName, err := fetchTableName(q)
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if err != nil {
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return nil, err
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}
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stmt, _, err := p.s3Conn.Prepare(
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fmt.Sprintf(`SELECT
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id,
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distance,
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embedding,
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slug,
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raw_text
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FROM %s
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WHERE embedding MATCH ?
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ORDER BY distance
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LIMIT 4
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`, tableName))
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if err != nil {
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return nil, err
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}
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query, err := sqlite_vec.SerializeFloat32(q[:])
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if err != nil {
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return nil, err
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}
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if err := stmt.BindBlob(1, query); err != nil {
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p.logger.Error("failed to bind", "error", err)
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return nil, err
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}
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resp := []models.VectorRow{}
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for stmt.Step() {
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res := models.VectorRow{}
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res.ID = uint32(stmt.ColumnInt64(0))
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res.Distance = float32(stmt.ColumnFloat(1))
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emb := stmt.ColumnRawText(2)
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res.Embeddings = decodeUnsafe(emb)
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res.Slug = stmt.ColumnText(3)
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res.RawText = stmt.ColumnText(4)
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resp = append(resp, res)
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}
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if err := stmt.Err(); err != nil {
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return nil, err
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}
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err = stmt.Close()
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if err != nil {
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return nil, err
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}
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return resp, nil
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}
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