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package rag
import (
"errors"
"math"
)
const isNormalizedPrecisionTolerance = 1e-6
// dotProduct calculates the dot product between two vectors.
// It's the same as cosine similarity for normalized vectors.
// The resulting value represents the similarity, so a higher value means the
// vectors are more similar.
func dotProduct(a, b []float32) (float32, error) {
// The vectors must have the same length
if len(a) != len(b) {
return 0, errors.New("vectors must have the same length")
}
var dotProduct float32
for i := range a {
dotProduct += a[i] * b[i]
}
return dotProduct, nil
}
func normalizeVector(v []float32) []float32 {
var norm float32
for _, val := range v {
norm += val * val
}
norm = float32(math.Sqrt(float64(norm)))
res := make([]float32, len(v))
for i, val := range v {
res[i] = val / norm
}
return res
}
// subtractVector subtracts vector b from vector a in place.
func subtractVector(a, b []float32) []float32 {
res := make([]float32, len(a))
for i := range a {
res[i] = a[i] - b[i]
}
return res
}
// isNormalized checks if the vector is normalized.
func isNormalized(v []float32) bool {
var sqSum float64
for _, val := range v {
sqSum += float64(val) * float64(val)
}
magnitude := math.Sqrt(sqSum)
return math.Abs(magnitude-1) < isNormalizedPrecisionTolerance
}
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