- Update Dockerfile to use backend.main:app instead of main:app
- Change exposed port from 8000 to 8001
- Fix docker-compose.yml port mapping to 8001:8001
- Update healthcheck to use correct port and /health endpoint
- Remove old main.py from root directory
Docker now correctly runs the new frontend + backend structure.
- Created complete frontend structure with Jinja2 templates
- Implemented three main pages: Dashboard, Fleet Roster, and Unit Detail
- Added HTMX auto-refresh for real-time updates (10s interval)
- Integrated dark/light mode toggle with localStorage persistence
- Built responsive card-based UI with sidebar navigation
- Created API endpoints for status snapshot, roster, unit details, and photos
- Added mock data service for development (emit_status_snapshot)
- Implemented tabbed interface on unit detail page (Photos, Map, History)
- Integrated Leaflet maps for unit location visualization
- Configured static file serving and photo management
- Updated requirements.txt with Jinja2 and aiofiles
- Reorganized backend structure into routers and services
- Added comprehensive FRONTEND_README.md documentation
Frontend features:
- Auto-refreshing dashboard with fleet summary and alerts
- Sortable fleet roster table (prioritizes Missing > Pending > OK)
- Unit detail view with status, deployment info, and notes
- Photo gallery with thumbnail navigation
- Interactive maps showing unit coordinates
- Consistent styling with brand colors (orange, navy, burgundy)
Ready for integration with real Series3 emitter data.
Added Docker support for easy deployment:
- Dockerfile: Python 3.11 slim image with FastAPI app
- docker-compose.yml: Service definition with volume mounting for data persistence
- .dockerignore: Exclude unnecessary files from Docker build
- database.py: Updated to store SQLite DB in ./data directory for volume persistence
- .gitignore: Added entries for database files and data directory
- README.md: Comprehensive documentation with Docker and local setup instructions
The application can now be run with: docker compose up -d
Database persists in ./data directory mounted as a volume
Implemented FastAPI backend with SQLite database for tracking seismograph fleet status:
- database.py: SQLAlchemy setup with SQLite
- models.py: Emitter model with id, unit_type, last_seen, last_file, status, notes
- routes.py: POST /emitters/report and GET /fleet/status endpoints
- main.py: FastAPI app initialization with CORS support
- requirements.txt: Dependencies (FastAPI, SQLAlchemy, uvicorn)
