refboard-ayon/docs/plans/2026-03-10-team-feedback-tracker.md

Team Feedback Tracker — 2026-03-10

Priority Order

1. Auto-Select After Import (Small UX fix)

Problem: Imported items don't get selected after upload completes.

Root cause: image-drop.ts:handleUploadResult() never calls selectionManager.selectOnly(). setupDragDrop() doesn't receive a selectionManager reference.

Fix:

• Pass selectionManager to setupDragDrop() and setupPaste() in useCanvasSetup.ts
• After addImageFromUpload()/addVideoFromUpload() returns, call selectionManager.selectOnly(item.id)
• Multi-file drops: select all new items

Files: frontend/src/canvas/image-drop.ts, frontend/src/hooks/useCanvasSetup.ts

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2. Upload Manager (Big UX win)

Problem: Uploads are completely silent — no progress, no status, no error feedback. Errors only logged to console.

Design:

• States: uploading → queued → processing → ready → failed
• Reuse the existing media job pipeline and socket events (media:job:update), NOT a parallel status system
• Retry/cancel support
• Upload progress via axios.onUploadProgress or XHR

What exists to build on:

• Toast system in Editor.tsx
• media_jobs table + media:job:update socket events
• Placeholder rectangles on canvas during upload

Files: frontend/src/api.ts, frontend/src/canvas/image-drop.ts, frontend/src/pages/Editor.tsx, backend/services/media-worker.js

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3. Video Size Failure Handling (Validation + feedback)

Problem: Videos of certain sizes fail silently. "Certain size" is too vague — need exact failure reasons surfaced to UI.

Fixes (in order of priority):

1. Upload-time validation — client-side file size + resolution checks with clear error messages
2. Log exact failure reason back to UI via socket events (not just console.error on backend)
3. ffmpeg job queue/backpressure — reject or queue when at capacity
4. Explicit max supported file/resolution policy (document and enforce)
5. Preview/proxy strategy for very large videos
6. Container memory bump (2GB) is a last resort, not the primary fix

Current limits found:

• Container memory: 512MB (docker-compose.yml:519)
• ffmpeg/ffprobe timeout: 15s each (video-utils.js:37,94)
• File size: 200MB default (minio.js:119, configurable)
• No resolution limit, no GPU texture size check

Files: backend/video-utils.js, backend/services/media-worker.js, backend/routes/upload.js, frontend/src/canvas/image-drop.ts, docker-compose.yml

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4. Export as Image (Incremental)

Problem: No way to download board/selection as image file.

Design:

• Browser download (NOT filesystem path — not realistic in-browser)
• Options: filename, format (PNG/JPEG/WebP), dimensions (locked ratio), quality, scope
• Scope: selection first, then full board
• Filename default: board name + timestamp

What exists to build on:

• clipboard.ts — full renderer.extract.canvas() + generateTexture() pipeline
• getItemWorldBounds() — world-space bounds for any item/group
• Resolution scaling logic (native texture ratio, capped at 4x)
• preserveDrawingBuffer: true already set

Files: frontend/src/canvas/clipboard.ts, frontend/src/components/Toolbar.tsx, frontend/src/pages/Editor.tsx

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5. GIF Support (Product decision needed first)

Problem: GIFs upload fine but render as static first frame only.

Product decision required — three options:

1. Stay animated — use PixiJS GifSprite, but risk CPU/GPU explosion with many visible GIFs
2. Autoplay only in viewport — animate when visible, pause when culled (like video lifecycle)
3. Static poster by default, animate-on-click — safest, consistent with video behavior

Recommendation: Normalize GIFs to video-like lifecycle, not image lifecycle. Treat as lightweight video with similar culling, poster, and play/pause behavior.

Technical context:

• PixiJS v8.17 has built-in GifSprite (available but unused)
• GIFs currently classified as type: 'image', use ImageSprite
• No animation metadata stored (frame count, duration)
• GIFs excluded from LOD tiers (stored as-is like SVG)

Files: frontend/src/canvas/SceneManager.ts, frontend/src/canvas/sprites/ImageSprite.ts, backend/routes/upload.js