Users now see the extracted photo during item editing and can choose to:
- 'Use Photo': Auto-save the image with the item
- 'Skip Photo': Create item without saving the photo
Changes:
1. frontend/components/AIOnboarding.tsx: Added image preview panel in edit form
- Shows extracted image to user
- Buttons to accept/reject photo
- Visual feedback when photo is skipped
2. frontend/hooks/useAIExtraction.ts: Updated confirmSingleItem and confirmAllItems
- Respect user's photo decision (_skipPhoto flag)
- Only pass extractedImageBlob if user approved it
- Prevents unwanted auto-photo-save
This gives users full control over which extracted photos are auto-saved.
Documented the complete image pipeline bugfix:
- Part 1 (v1.14.1): Type system mismatch for photo_path fields
- Part 2 (v1.14.2): Blob serialization issue - image not reaching backend
The extracted image blob is now converted to base64 before sending to the API,
ensuring it's JSON-safe and matches the backend's ItemCreate schema.
The extracted image blob from AI extraction was not being sent to the backend
because Blob objects cannot be JSON serialized. Fixed by:
1. Converting Blob to base64 before sending to API
2. Renaming fields: extractedImageBlob → extracted_image_bytes, imageProcessing → image_processing
3. Removing Blob from local DB (keep original data structure for IndexedDB)
4. Applying same fix to both single item and batch update flows
This ensures the auto-photo-save feature receives the image data it needs.
Documented the image display issue, root cause (type system mismatch),
and the fix applied in v1.14.1. Images now correctly display from
the auto-photo-save feature in both ItemDetailModal and InventoryTable.
toast.warning is not a valid method in react-hot-toast API. Changed to
toast.success since the item was successfully created even if photo upload failed.
The backend returns photo_path, photo_thumbnail_path, and photo_upload_date
from the AI auto-save feature, but the frontend Item interface was missing
these fields, causing images not to display in ItemDetailModal and InventoryTable.
Updated:
- frontend/lib/db.ts: Added missing photo fields to Item interface
- frontend/components/ItemDetailModal.tsx: Use photo_path first, fallback to image_url
- frontend/components/InventoryTable.tsx: Use photo_path first, fallback to image_url
This ensures the UI can now display photos saved by the auto-photo-save feature.
- Updated confirmSingleItem() to include extractedImageBlob and imageProcessing
- Updated confirmAllItems() to pass image data for bulk item creation
- Each extracted item now carries its own image_processing metadata
- All items in bulk creation share the same extracted image blob
- Added 12 comprehensive tests verifying data is passed correctly
- All 465 frontend tests passing, zero regressions
- Extend ItemCreate schema with optional extracted_image_bytes (base64) and image_processing (dict)
- Update create_item endpoint to call _auto_save_photo_from_extraction after item creation
- Decode base64 image bytes and pass crop_bounds, rotation_degrees to helper
- Don't block item creation if photo save fails (log warning instead)
- Item returned with photo_path, photo_thumbnail_path populated if save succeeded
- Full backward compatibility: old clients without image fields work unchanged
- Add 5 integration tests covering all scenarios:
- Create item WITH image_processing → photo auto-saved
- Create item WITHOUT image_processing → no photo (backward compatible)
- Create item WITH invalid image_processing → item created, photo skipped
- Create item WITH crop_bounds=None → item created, photo skipped
- Create item WITH bytes but NO processing metadata → item created, photo skipped
- All 158 backend tests passing, zero regressions
- Added 11 comprehensive tests for image_processing parsing
- Tests validate crop_bounds structure: {x, y, width, height} all ints >= 0
- Tests validate rotation_degrees: int/float, -360 to +360
- Tests validate confidence: float, 0.0 to 1.0
- Tests graceful handling when image_processing field is missing
- Tests multiple items with image_processing data
- Tests partial data handling (optional fields)
- Tests with both Gemini and Claude providers
- Updated extract_label_info() to preserve and validate image_processing field
- All tests passing, no regressions
The username input was conditionally hidden when it had a value, causing
the field to disappear and focus to jump to password when typing. Fixed by:
1. Always rendering the username input (removed conditional)
2. Using controlled input with value prop
3. Only auto-focus password when username is already entered
This fixes the focus-jumping bug that made it impossible to enter usernames.
Temporarily using allow_origins=['*'] to debug whether CORS is blocking
LDAP login requests from VPN client. This is insecure for production.
TODO: Fix subnet pattern matching in ALLOWED_ORIGINS configuration.
local-ssl-proxy was binding to 0.0.0.0 which doesn't work reliably for
cross-network access (VPN, remote clients). Now binds to SERVER_IP from
inventory.env, ensuring the proxy is reachable from all networks that can
reach the server's main IP address.
When accessing from VPN/Tailscale (e.g., 100.78.182.28), frontend was trying
to reach backend on that same IP, but backend listens on SERVER_IP instead.
Now uses SERVER_IP from network.json config, ensuring remote clients connect
to the correct server address regardless of their access network.
- Next.js allowedDevOrigins now loaded from ALLOWED_DEV_ORIGINS env var
- start_server.sh generates ALLOWED_DEV_ORIGINS from EXTRA_ALLOWED_ORIGINS
- Subnet notation (10.0.0.0/24) auto-converts to wildcard patterns (10.0.0.*)
- Individual IPs convert to subnet patterns (192.168.1.100 -> 192.168.1.*)
- Zero hardcoded IPs in source code - all from inventory.env
- Simplify backend CORS middleware to use standard FastAPI implementation
- Keep subnet validation function for future use in route-level checks
- Add Tailscale subnet pattern to Next.js allowedDevOrigins config
- Both individual IPs and subnet configurations now work correctly
- Add ipaddress module for subnet parsing (10.0.0.0/24 format)
- Implement subnet validation in CORS middleware
- Separate individual IPs from subnet definitions in EXTRA_ALLOWED_ORIGINS
- Custom SubnetAwareCORSMiddleware for dynamic origin validation
- Support both exact IP matches and subnet ranges
- Backward compatible with existing ALLOWED_ORIGINS list
- Add ItemDetailModal component for viewing item details and replacing photos
- Add photo replacement/deletion endpoints to API layer (PUT/DELETE /items/{id}/photo)
- Update InventoryTable to open detail modal on item click
- Show current photo thumbnail with Replace/Delete buttons
- Support uploading new photo with ItemPhotoUpload component
- Delete old photo on backend when replacing (no orphaned files)
- Full test coverage: 18 tests for ItemDetailModal component
- All 393 tests passing, zero TypeScript errors
- Build verified successfully
- Create frontend/app/items/create.tsx with multi-step item creation workflow (Details → Photo Upload → Preview → Confirm)
- Create frontend/hooks/useItemCreate.ts custom hook managing form state, step navigation, and photo upload
- Add integration tests for item creation workflow with photo upload support
- Photo upload step supports manual crop UI with crop bounds submission
- ManualCropUI visible by default with toggle to use full photo
- Photo uploaded before item confirmation, ensuring photo is attached
- Works with mobile camera capture via ItemPhotoUpload component
- All 374 tests passing
