- Production Dockerfiles: backend (gunicorn + uvicorn workers),
frontend (multi-stage Node build + nginx with API proxy)
- docker-compose.prod.yml: integrates with VPS nginx-proxy via
VIRTUAL_HOST for auto-TLS at fit.cescalante.dev
- GitHub Actions workflow (Gitea Actions-compatible): builds images
and deploys on push to main via self-hosted runner
- Make CORS origins configurable via CORS_ORIGINS env var
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Introduces DSPy-based nutrition and plan generation modules, including image analysis for nutritional info and personalized diet/exercise plans. Adds new API endpoints for health metrics/goals, nutrition image analysis, and plan management. Updates models, schemas, and backend structure to support these features, and includes initial training data and configuration for prompt optimization.
Set up backend and frontend structure for a health and fitness tracker using Python (FastAPI, SQLModel, DSPy) and React. Includes Docker and Compose configs, authentication, nutrition AI module, health/nutrition/user endpoints, database models, and basic frontend with routing and context. Enables tracking nutrition, health metrics, and user management, with architecture ready for future mobile and cloud deployment.
