Zenness is a full-stack mental health assessment web application designed to promote mental health awareness and self-reflection. The application allows users to complete a short engaging assessment, sends the responses to a backend service, and provides personalized feedback based on machine learning predictions.
This project is developed as a college-level mini project and is intended for educational and awareness purposes only. It is not a medical or diagnostic tool.
- Mental health self-assessment questionnaire
- Backend-powered prediction using a trained machine learning model
- Classification of mental health levels (Normal, Moderate, Severe)
- Personalized recommendations based on assessment results
- Clean, minimal, and responsive user interface
- Next.js (React framework)
- TypeScript
- CSS / Tailwind CSS
- Framer Motion (animations)
- FastAPI (Python)
- Machine Learning model stored as a
.pklfile
- The user accesses the home page of the application.
- The user starts the mental health assessment.
- The user answers a set of predefined questions.
- The frontend sends the responses to the FastAPI backend through a REST API.
- The backend processes the input using a trained machine learning model.
- The prediction result is returned to the frontend.
- The application displays the mental health level along with relevant recommendations.
root/
├── app/ # Next.js App Router pages
├── components/ # Reusable UI components
├── backend/ # FastAPI backend
│ ├── app.py # API endpoints
│ └── model.pkl # Trained ML model
├── public/ # Static assets
├── .gitignore
├── next.config.mjs
├── package.json
└── README.md
npm install
npm run devThe frontend will run at http://localhost:3000.
cd backend
pip install -r requirements.txt
uvicorn app:app --reloadThe backend will run at http://localhost:8000.
This project demonstrates:
- Full-stack web application development
- Integration of machine learning models into web applications
- REST API communication between frontend and backend
- Practical application of mental health awareness systems
- User authentication and profiles
- Database integration for storing assessment history
- Improved machine learning model accuracy
- Advanced analytics and dashboards
This application is intended solely for educational and self-awareness purposes. It does not replace professional mental health diagnosis or treatment.
Developed by Ark Gupta IIIT NAGPUR