feat: 🎉 Vectors na Vectors, the begining

Translate 1536 <-> 768 , 3072 <-> 2048

pkg/adapter/random.go

@@ -0,0 +1,45 @@
+package adapter
+
+import (
+	"fmt"
+	"math"
+	"math/rand"
+	"time"
+)
+
+type randomAdapter struct {
+	sourceDim int
+	targetDim int
+	matrix    [][]float32
+}
+
+func newRandomAdapter(sourceDim, targetDim int, seed int64) *randomAdapter {
+	if seed == 0 {
+		seed = time.Now().UnixNano()
+	}
+	//nolint:gosec // deterministic seeded RNG for projection matrix generation, not security use
+	rng := rand.New(rand.NewSource(seed))
+
+	// Gaussian N(0, 1/targetDim) — preserves expected squared norms (Johnson-Lindenstrauss)
+	stddev := 1.0 / math.Sqrt(float64(targetDim))
+	matrix := make([][]float32, targetDim)
+	for i := range matrix {
+		row := make([]float32, sourceDim)
+		for j := range row {
+			row[j] = float32(rng.NormFloat64() * stddev)
+		}
+		matrix[i] = row
+	}
+
+	return &randomAdapter{sourceDim: sourceDim, targetDim: targetDim, matrix: matrix}
+}
+
+func (a *randomAdapter) SourceDim() int { return a.sourceDim }
+func (a *randomAdapter) TargetDim() int { return a.targetDim }
+
+func (a *randomAdapter) Adapt(vec []float32) ([]float32, error) {
+	if len(vec) != a.sourceDim {
+		return nil, fmt.Errorf("random adapt: %w: got %d, want %d", ErrDimMismatch, len(vec), a.sourceDim)
+	}
+	return L2Norm(matVecMul(a.matrix, vec)), nil
+}