scalable mental health platform to support users dealing with depression, anxiety, and PTSD through interactive therapeutic games & a hospital Management website
- Real-time Communication: WebSocket support for live updates and smooth Flow of Data.
- Cloud Storage: Integration with Cloudinary for secure media uploads.
- Modern Frontend: Built with React and styled using Tailwind CSS.
- Robust Backend: Python (Flask) API with MongoDB for data storage and Redis for caching/session management.
- Admin Dashboard: Manage doctors, medicines, appointments, users and RESTAPI being used for connecting the user panel and admin panel .
- Mental Health Games: Interactive games to support mental well-being.
- Frontend: React, Tailwind CSS, Vite
- Backend: Python (Flask)
- Database: MongoDB
- Cache/Session: Redis for storing the Realtime scores of the games and leaderboard data of the therapeutic games
- WebSockets: For real-time features
- Cloud Storage: Cloudinary
- Node.js (for frontend)
- Python 3.8+
- MongoDB
- Redis
- Cloudinary account (for media uploads)
- Clone the repository.
- Navigate to the
backend/directory. - Install dependencies:
pip install -r requirements.txt
- Copy
.env.exampleto.envand fill in required environment variables (MongoDB URI, Redis URL, Cloudinary credentials, etc). - Seed the database:
- To add initial doctors and medicines, run:
python seed.py
- To add initial doctors and medicines, run:
- Start the backend server:
python run.py
- Navigate to the
Healthcare/directory. - Install dependencies:
npm install
- Start the frontend:
npm run dev
- . WebSocket support for live updates and smooth Flow of Data
- Media uploads (e.g., doctor profile images, reports) are stored securely in Cloudinary. Configure your Cloudinary credentials in the backend
.envfile.
backend/— Python Flask API, models, controllers, routes, and database seeders.Healthcare/— React frontend, components, assets, and styles.
- MongoDB URI
- Redis URL
- Cloudinary API Key, Secret, and Cloud Name
- (See
.env.exampleinbackend/for all required variables)
- Use
backend/seed.pyto populate the database with initial doctor and medicine data.
MIT
Contributions are welcome!