3b544f6a25
- 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>
healthy-fit
Health and Fitness tracker
Initial prompt:
I need you to help me develop an application using Python and React, the main goal for the app is to track health metrics: nutrition (macros, calories, minerals), exercise (walking, weight lifting, sports like tennis) and everything else related to living a healthy lifestyle.
We can introduce an AI component to the application and it'll be ideal to leverage DSPy to enhance the engineering of prompts. Advanced features could include RAG and a Knowledge graph, I still don't have an use case for these, so, help me think how these approaches could be used in the app. Vector/semantic search or GraphRAG could add some value so also consider those.
The user will be able to easily track the macros, nutrient and calories they consume by just uploading a picture from their phone, and then refine the details manually. This information would be saved to a DB of some sort (help me define which would be best) and then be used across the different app modules. The user can track their blood indicators such as cholesterol, vitamin D3, testosterone and more. Also the weight, height and set goals to improve health. The app can help the user create a diet and exercise to gain musle and or lose weight/fat depending on their preference.
The architecture of the app must support initially a web version, but in the future the idea is to launch it to the Apple Store and Google Play Store. We are exclusively focusing on open source technologies that can be deployed to any cloud such as AWS, GCP or Azure or even on-premise or private VPS running Linux. Docker and Kubernetes are the preferred platform to run the app and services.