EmoS Project

Welcome to the EmoS repository!

Description

EmoS is a modern, full-stack machine learning web app for mental health risk prediction and PHQ-9 depression screening. It features a beautiful Claude-inspired UI with glassmorphism, dark mode, and a responsive design. Built with Python and Flask, it uses a trained Random Forest model to provide personalized wellness recommendations.

Getting Started

Prerequisites

• Python 3.8+
• pip (Python package manager)

Installation

1. Clone the repository:

   git clone <your-repo-url>
   cd EmoS

2. Install dependencies:

   pip install -r requirements.txt

3. Ensure mental_health_model.pkl is present in the project root (already included if you cloned the repo).

Running the App

python app_flask.py

Then open your browser and go to http://localhost:5000

Features

• 🧠 Mental Health Risk Prediction: Enter lifestyle and health data to get a risk assessment and wellness score.
• 📋 PHQ-9 Depression Screening: Take the PHQ-9 quiz and receive severity and recommendations.
• 💬 Modern UI: Claude-inspired, glassy, and responsive interface.
• 🌙 Dark Mode: Toggle dark/light mode (persists across pages).
• ⚡ Personalized Recommendations: Actionable tips based on your data and model prediction.
• 🔗 Instant Navigation: Click the "EmoS" logo to return home from any page.

Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License.