dtoro
997e11db78
User-facing labels and code now use "discard" (verb) and "Discarded"
(state/view label) instead of "trash" / "Trashed". The DB column names
stay (is_trashed / trashed_at) so no migration is required — only the
SQLAlchemy attribute names are renamed via Column('old_name', ...).
Backend
- Photo model: is_discarded / discarded_at attributes (DB columns
unchanged).
- PhotoBase / PhotoResponse / PhotoUpdate schemas use the new field
names.
- Photos list endpoint: is_discarded query param, filter logic.
- DELETE /photos/{id} now sets is_discarded; success message updated.
- Bulk action 'trash' renamed to 'discard'.
- backend/app/routers/trash.py renamed to discard.py with renamed
functions and route prefix /api/v1/discard.
- main.py imports and mounts the discard router.
- tasks/scan.py marks missing files as is_discarded.
Frontend
- Photo TS type: is_discarded.
- PhotoThumbnail: shows the trash-can icon when is_discarded.
- RightSidebar: button label "Discard"; mutation field name; local
variable rename.
- TopBar: discardPhotosMutation and "Discard" button; toast text
"Discarded".
- LeftSidebar: virtual node id 'discarded' / label "Discarded".
- FilterBar / filterStore / useFilterUrlSync: FlagFilter enum value
'trashed' → 'discarded'; backend param key is_discarded.
- KeyboardHints: X label "Discard".
- useKeyboardShortcuts: PhotoUpdate field rename, X handler.
- api.ts: /trash routes → /discard, trash export → discard,
bulkUpdate trash field → discard.
Out of scope (intentional): the docker-compose trash_data volume,
backend/Dockerfile mkdir /data/trash, config.py TrashSettings, and
the spec doc — all unused since soft-discard, and renaming them is
churn for no benefit.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Mulita - Self-Hosted Photo Management Application
A self-hosted, Docker-deployed photo management application inspired by Lightroom's workflow. Mulita provides a fast, keyboard-driven interface to browse, organize, tag, and manage your photo library.
Features
- Photo Organization: Browse photos in a timeline view with virtual scrolling for performance
- Thumbnail Generation: Automatic thumbnail generation for all photo formats including RAW
- Metadata Extraction: Full EXIF/XMP metadata extraction and search
- Keyboard Shortcuts: Lightroom-style keyboard navigation and actions
- File Support: JPEG, PNG, RAW formats (CR2, CR3, NEF, ARW, etc.), HEIC/HEIF, and videos
- Heaps: Temporary collections for organizing photos
- Tags & Ratings: Organize with tags, star ratings, and color labels
- Dark Mode: Photography-optimized dark interface
Tech Stack
Backend
- Python 3.12 with FastAPI
- SQLite with SQLAlchemy (async)
- Celery + Redis for background tasks
- pyvips for fast thumbnail generation
- ExifTool for metadata extraction
Frontend
- React 18 with TypeScript
- Vite for fast development
- TanStack Query for data fetching
- TanStack Virtual for virtualized scrolling
- Tailwind CSS for styling
- Zustand for state management
Quick Start
Prerequisites
- Docker and Docker Compose
- Photo directories to mount
Setup
- Clone the repository:
git clone <repository-url>
cd muleimage
- Configure your photo directories in
.env:
# Edit .env file
PHOTO_DIRS=/path/to/your/photos
- Start the application:
docker-compose up -d
- Access the application at
http://localhost:3000
Architecture
The application consists of 5 Docker services:
- frontend: React SPA served by Nginx
- backend: FastAPI REST API
- worker: Celery workers for background tasks
- redis: Message broker for Celery
- db: SQLite database (file-based)
Keyboard Shortcuts
| Key | Action |
|---|---|
← → ↑ ↓ |
Navigate photos |
Space |
Quick preview |
Enter |
Open loupe view |
P |
Pick photo |
X |
Reject photo |
1-5 |
Set star rating |
Tab |
Toggle left sidebar |
I |
Toggle metadata panel |
G |
Grid view |
E |
Loupe view |
Delete |
Move to trash |
Development
Backend Development
cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload
Frontend Development
cd frontend
npm install
npm run dev
Configuration
Edit mulita.yml to configure:
- Source photo directories
- Thumbnail sizes and quality
- Scanner settings
- Performance tuning
Performance
- Handles 100,000+ photos efficiently
- Virtual scrolling for smooth timeline navigation
- Thumbnail generation at 10+ photos/second
- SQLite FTS5 for fast full-text search
Future Features (Phase 2)
- AI-powered scene classification
- Face detection and clustering
- Smart albums
- Duplicate detection
- Export presets
- Multi-user support
License
MIT