feat: production Docker, Playwright tests, settings API, and bug fixes

- Add user management endpoints (register, list, delete, change password)
- Add API key management (create, list, delete)
- Add settings persistence endpoints (get, put)
- Wire settings dialog to real backend (People, API Keys, System, Security)
- Fix login auth flow (window.location.href for full reload)
- Fix download URLs returning 401 (make public since UUIDs are unguessable)
- Fix border tool shadowColor validation (accept 6-8 hex digits)
- Fix remove-bg alpha matting fallback (retry without on failure)
- Fix AI tool silent fallbacks (report errors instead of no-ops)
- Add checkerboard background to before/after slider for transparency
- Add progress bars to all AI tool components
- Add Playwright E2E test suite (131 tests across 9 test files)
- Rewrite Dockerfile for production (tsx runtime, pre-baked AI models)
- Add .dockerignore for faster builds
- Add proper accessible labels to login form

packages/ai/python/detect_faces.py

@@ -63,18 +63,16 @@ def main():
                 )
 
         except ImportError:
-            # Fallback: no face detection available, save original
-            img.save(output_path)
+            # MediaPipe not available — report error clearly
             print(
                 json.dumps(
                     {
-                        "success": True,
-                        "facesDetected": 0,
-                        "faces": [],
-                        "note": "mediapipe not available - no faces detected",
+                        "success": False,
+                        "error": "Face detection requires the mediapipe package. Install with: pip install mediapipe",
                     }
                 )
             )
+            sys.exit(1)
 
     except ImportError:
         print(

packages/ai/python/inpaint.py

@@ -41,12 +41,21 @@ def main():
             Image.fromarray(result).save(output_path)
             method = "lama"
 
-        except (ImportError, Exception):
-            # Fallback: simple inpainting using PIL
-            # Just copy the image (mask areas won't be processed without ML model)
-            img = Image.open(input_path)
-            img.save(output_path)
-            method = "copy"
+        except ImportError:
+            # LaMa not available — report error instead of silently copying
+            print(
+                json.dumps(
+                    {
+                        "success": False,
+                        "error": "Object eraser requires the lama-cleaner package. Install with: pip install lama-cleaner",
+                    }
+                )
+            )
+            sys.exit(1)
+        except Exception as e:
+            # LaMa installed but processing failed — still report error
+            print(json.dumps({"success": False, "error": f"Inpainting failed: {str(e)}"}))
+            sys.exit(1)
 
         print(json.dumps({"success": True, "method": method}))
 

packages/ai/python/remove_bg.py

@@ -16,12 +16,17 @@ def main():
         with open(input_path, "rb") as f:
             input_data = f.read()
 
-        output_data = remove(
-            input_data,
-            alpha_matting=True,
-            alpha_matting_foreground_threshold=240,
-            alpha_matting_background_threshold=10,
-        )
+        # Try with alpha matting first for better edges, but fall back
+        # without it if the image triggers the known rembg matting error
+        try:
+            output_data = remove(
+                input_data,
+                alpha_matting=True,
+                alpha_matting_foreground_threshold=240,
+                alpha_matting_background_threshold=10,
+            )
+        except Exception:
+            output_data = remove(input_data)
 
         with open(output_path, "wb") as f:
             f.write(output_data)