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package storage
import (
"encoding/binary"
"fmt"
"gf-lt/models"
"sort"
"unsafe"
"github.com/jmoiron/sqlx"
)
type VectorRepo interface {
WriteVector(*models.VectorRow) error
SearchClosest(q []float32, limit int) ([]models.VectorRow, error)
ListFiles() ([]string, error)
RemoveEmbByFileName(filename string) error
DB() *sqlx.DB
}
// SerializeVector converts []float32 to binary blob
func SerializeVector(vec []float32) []byte {
buf := make([]byte, len(vec)*4) // 4 bytes per float32
for i, v := range vec {
binary.LittleEndian.PutUint32(buf[i*4:], mathFloat32bits(v))
}
return buf
}
// DeserializeVector converts binary blob back to []float32
func DeserializeVector(data []byte) []float32 {
count := len(data) / 4
vec := make([]float32, count)
for i := 0; i < count; i++ {
vec[i] = mathBitsToFloat32(binary.LittleEndian.Uint32(data[i*4:]))
}
return vec
}
// mathFloat32bits and mathBitsToFloat32 are helpers to convert between float32 and uint32
func mathFloat32bits(f float32) uint32 {
return binary.LittleEndian.Uint32((*(*[4]byte)(unsafe.Pointer(&f)))[:4])
}
func mathBitsToFloat32(b uint32) float32 {
return *(*float32)(unsafe.Pointer(&b))
}
func fetchTableName(emb []float32) (string, error) {
switch len(emb) {
case 768:
return "embeddings_768", nil
default:
return "", fmt.Errorf("no table for the size of %d", len(emb))
}
}
func (p ProviderSQL) WriteVector(row *models.VectorRow) error {
tableName, err := fetchTableName(row.Embeddings)
if err != nil {
return err
}
serializedEmbeddings := SerializeVector(row.Embeddings)
query := fmt.Sprintf("INSERT INTO %s(embeddings, slug, raw_text, filename) VALUES (?, ?, ?, ?)", tableName)
_, err = p.db.Exec(query, serializedEmbeddings, row.Slug, row.RawText, row.FileName)
return err
}
func (p ProviderSQL) SearchClosest(q []float32, limit int) ([]models.VectorRow, error) {
tableName, err := fetchTableName(q)
if err != nil {
return nil, err
}
querySQL := "SELECT embeddings, slug, raw_text, filename FROM " + tableName
rows, err := p.db.Query(querySQL)
if err != nil {
return nil, err
}
defer rows.Close()
type SearchResult struct {
vector models.VectorRow
distance float32
}
var allResults []SearchResult
for rows.Next() {
var (
embeddingsBlob []byte
slug, rawText, fileName string
)
if err := rows.Scan(&embeddingsBlob, &slug, &rawText, &fileName); err != nil {
continue
}
storedEmbeddings := DeserializeVector(embeddingsBlob)
// Calculate cosine similarity (returns value between -1 and 1, where 1 is most similar)
similarity := cosineSimilarity(q, storedEmbeddings)
distance := 1 - similarity // Convert to distance where 0 is most similar
result := SearchResult{
vector: models.VectorRow{
Embeddings: storedEmbeddings,
Slug: slug,
RawText: rawText,
FileName: fileName,
},
distance: distance,
}
allResults = append(allResults, result)
}
// Sort by distance
sort.Slice(allResults, func(i, j int) bool {
return allResults[i].distance < allResults[j].distance
})
// Truncate to limit
if len(allResults) > limit {
allResults = allResults[:limit]
}
// Convert back to VectorRow slice
results := make([]models.VectorRow, len(allResults))
for i, result := range allResults {
result.vector.Distance = result.distance
results[i] = result.vector
}
return results, nil
}
// cosineSimilarity calculates the cosine similarity between two vectors
func cosineSimilarity(a, b []float32) float32 {
if len(a) != len(b) {
return 0.0
}
var dotProduct, normA, normB float32
for i := 0; i < len(a); i++ {
dotProduct += a[i] * b[i]
normA += a[i] * a[i]
normB += b[i] * b[i]
}
if normA == 0 || normB == 0 {
return 0.0
}
return dotProduct / (sqrt(normA) * sqrt(normB))
}
// sqrt returns the square root of a float32
func sqrt(f float32) float32 {
// A simple implementation of square root using Newton's method
if f == 0 {
return 0
}
guess := f / 2
for i := 0; i < 10; i++ { // 10 iterations should be enough for good precision
guess = (guess + f/guess) / 2
}
return guess
}
func (p ProviderSQL) ListFiles() ([]string, error) {
query := "SELECT DISTINCT filename FROM embeddings_768"
rows, err := p.db.Query(query)
if err != nil {
return nil, err
}
defer rows.Close()
var allFiles []string
for rows.Next() {
var filename string
if err := rows.Scan(&filename); err != nil {
continue
}
allFiles = append(allFiles, filename)
}
return allFiles, nil
}
func (p ProviderSQL) RemoveEmbByFileName(filename string) error {
query := "DELETE FROM embeddings_768 WHERE filename = ?"
_, err := p.db.Exec(query, filename)
return err
}
|
