Initial commit: img-infinite-canvas AI design workbench MVP

Moteva-style AI design workbench replica. Home prompt creates a project;
the project page provides an infinite canvas with node drag, zoom/pan,
a design chat panel, history replay, image asset upload, and project
save/regenerate.

- Backend: go-zero, DDD layering, sqlc/pgx, optional PostgreSQL; memory
  or Redis cache; asynq job queue; MinIO/S3/R2/OSS object storage;
  sky-valley/pi agent runtime adapter.
- Frontend: Next.js App Router + Vite artifact build, TypeScript, i18n,
  shadcn/ui components, auth (OTP/Turnstile/Google/WeChat).
- Deploy: Docker Compose and k3s manifests.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

server/internal/application/image_asset_encoding.go

@@ -0,0 +1,43 @@
+package application
+
+import (
+	"bytes"
+	"image"
+	"strings"
+
+	webp "github.com/deepteams/webp"
+)
+
+const generatedWebPQuality float32 = 90
+
+func encodeRasterAssetAsWebP(data []byte, contentType string) ([]byte, string, error) {
+	if !shouldEncodeAssetAsWebP(contentType) {
+		return data, contentType, nil
+	}
+
+	source, _, err := image.Decode(bytes.NewReader(data))
+	if err != nil {
+		return nil, "", err
+	}
+
+	var output bytes.Buffer
+	if err := webp.Encode(&output, source, &webp.EncoderOptions{
+		Quality:      generatedWebPQuality,
+		Method:       4,
+		AlphaQuality: 100,
+		UseSharpYUV:  true,
+		Exact:        true,
+	}); err != nil {
+		return nil, "", err
+	}
+	return output.Bytes(), "image/webp", nil
+}
+
+func shouldEncodeAssetAsWebP(contentType string) bool {
+	switch strings.ToLower(strings.TrimSpace(contentType)) {
+	case "image/png", "image/jpeg", "image/jpg":
+		return true
+	default:
+		return false
+	}
+}