TheHealthApp

Enterprise-Grade Multilingual Preventive Health Platform

TheHealthApp is a scalable, modular, multilingual preventive health platform designed to improve accessibility to health risk awareness across diverse populations. The system enables users to perform structured self-assessments and receive interpretable insights through a technology-driven interface.

The platform integrates a modern full-stack architecture combining FastAPI, React, and a modular machine learning layer to deliver real-time, accessible health insights.

---

Vision

To build a globally accessible preventive healthcare platform that delivers clear, actionable, and language-inclusive health insights, empowering users to make informed lifestyle decisions regardless of geography or language barriers.

---

Current Product Scope (Milestone 2 – Deployable MVP)

The current release focuses on delivering a fully functional Minimum Viable Product (MVP) with:

• End-to-end user flow (consent → input → result)
• Stable local deployment environment
• Core health risk workflow (initial version)
• Basic CI validation for code reliability

This milestone prioritizes system stability, usability, and integration over feature breadth.

---

Key Capabilities

Authentication and Security

• JWT-based authentication (access and refresh tokens)
• Secure login, signup, and logout workflows
• Token lifecycle management

Multilingual Interface

• Language support: English, Hindi, Arabic
• Real-time UI translation using i18next
• Designed for future localization scalability

Health Risk Assessment (MVP)

• Structured questionnaire-based input
• Backend-driven risk evaluation logic (initial version)
• Expandable architecture for machine learning-based predictions

Modular System Architecture

• Decoupled frontend, backend, and ML services
• API-driven communication
• Scalable for future microservice expansion

Local Deployment (Docker-enabled)

• MongoDB containerized using Docker
• Reproducible development environment
• Simplified onboarding for contributors

CI/CD (Current Implementation)

• GitHub Actions-based CI workflow
• Automated linting, testing, and build validation
• Foundation for future deployment pipelines

---

System Architecture Overview

Frontend (React)  ->  Backend (FastAPI)  ->  Database (MongoDB)
↓
ML Service (Planned)

---

Technology Stack

Frontend

Tool	Purpose
React (Vite)	SPA framework
Tailwind + ShadCN/UI	Styling and components
i18next	Internationalization
Axios	API communication
React Router DOM	Navigation
Context API	Global state management

Backend

Tool	Purpose
FastAPI (Python 3.11)	Backend API
MongoDB 7	Database
Beanie ODM	Data modeling
Pydantic v2	Validation
SlowAPI	Rate limiting
JWT	Authentication
Uvicorn	Server runtime

Machine Learning Layer (Planned)

• Risk prediction models (Framingham-based and extended)
• Modular service architecture for ML integration
• API-driven inference system

---

Getting Started

1. Clone Repository

git clone https://github.com/oss-slu/TheHealthApp.git
cd TheHealthApp

2. Start Database (Docker)

docker run --name tha-mongo -p 27017:27017 -d mongo:7

3. Backend Setup

cd backend
cp .env.example .env

Configure environment variables:

Variable	Description	Example
MONGO_URL	MongoDB connection string	mongodb://localhost:27017
MONGO_DB_NAME	Database name	healthapp
JWT_ACCESS_SECRET	Access token secret	(set a strong random value)
JWT_REFRESH_SECRET	Refresh token secret	(set a different strong random value)
ACCESS_TOKEN_EXPIRE_MINUTES	Access token TTL	15
REFRESH_TOKEN_EXPIRE_DAYS	Refresh token TTL	7
ALLOWED_ORIGINS	CORS allowed origins	http://localhost:5173

Run backend:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
PYTHONPATH=$(pwd) uvicorn src.main:app --reload --port 8000

API docs: http://127.0.0.1:8000/docs

4. Frontend Setup

cd frontend
cp .env.example .env

Set:

Variable	Example
VITE_API_BASE_URL	http://localhost:8000/api/v1
VITE_ML_API_URL	http://localhost:8001/predict

Run:

npm install
npm run dev

Open: http://localhost:5173

---

Quick Functional Validation

Action	Expected Result
Signup/Login	JWT tokens generated
Token Refresh	Access token refreshed
Language Switch	UI updates dynamically
Questionnaire	Input accepted
Result Display	Risk output generated
Logout	Tokens cleared

---

Development Workflow

Branch Strategy

main        → Stable release
develop     → Integration branch
feature/*   → Feature development
fix/*       → Bug fixes
ci/*        → CI/CD updates

Commit Convention

feat: add risk calculation
fix: resolve API issue
ci: add GitHub Actions workflow
docs: update README

---

CI/CD Strategy (Current State)

CI is implemented using GitHub Actions and runs on:

• Pull requests
• Push to main and develop branches

Current Checks

• Lint validation
• Test execution
• Build verification

Planned Enhancements

• Docker image builds
• Deployment pipelines
• Environment-based releases

---

Roadmap

Completed

• Frontend–backend integration
• Authentication system
• Multilingual UI
• MVP health risk workflow

In Progress

• ML model integration
• CI/CD expansion
• Error handling improvements

Planned

• Advanced health analytics
• Accessibility improvements
• RTL language support
• Cloud deployment
• Contributor onboarding enhancements

---

Contribution Guidelines

Workflow

git checkout -b feat/your-feature
git commit -m "feat: description"
git push origin feat/your-feature

• All changes must go through pull requests
• CI must pass before merging
• Code review is required

---

Issue Labels

Label	Meaning
feature	New functionality
bug	Defect or issue
enhancement	Improvement
documentation	Documentation updates
devops	CI/CD or infrastructure
help wanted	Open for contribution

---

License

• TBD

---

Contact

Project Lead: Munazzah Rakhangi Email: munazzahrizwan.rakhangi@slu.edu