This project has been made for a hackathon

📚 Virtual Study Environment 🧠

Welcome to the Virtual Study Environment! This innovative platform allows users to upload PDF files, analyzes the content, scans the user's mood, and provides personalized study tips based on that mood.

This project leverages React, Node.js, and Flask to create an intuitive and responsive study companion.

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✨ Features

• PDF Analysis: Upload your PDF and receive a summarized version of the content.
• Mood Detection: The system scans your mood using a webcam or manual input.
• Personalized Study Tips: Based on your mood, receive customized study recommendations.
• Interactive UI: Smooth and responsive user interface built with React.

🛠 Tech Stack

• Frontend: React.js
• Backend: Node.js (for handling file uploads, user interaction)
• API: Flask (for PDF analysis and mood detection)

🚀 Getting Started

Prerequisites

Ensure you have the following installed:

• Node.js
• Python 3.x
• Flask

Installation

1. Clone the repository

   git clone https://github.com/yourusername/virtual-study-environment.git
   cd virtual-study-environment

Install dependencies for the frontend

bash Copy code cd client npm install Install dependencies for the backend

bash Copy code cd server npm install Install dependencies for Flask

bash Copy code cd flask-api pip install -r requirements.txt Running the Application Start the Flask server

bash Copy code cd flask-api flask run Start the Node.js server

bash Copy code cd server npm start Start the React client

bash Copy code cd client npm start Environment Variables Create a .env file in the root of each service and add the necessary environment variables:

Flask API: FLASK_ENV, MOOD_DETECTION_API_KEY Node.js: PORT, DATABASE_URL React: REACT_APP_API_URL 📈 How it Works PDF Upload: Users can upload a PDF document to the system. Content Summarization: The Flask API analyzes the content of the PDF and returns a concise summary. Mood Detection: Using a webcam (or manually entering their mood), the system analyzes the user’s mood. Study Tips: Based on the detected mood, the system provides personalized study recommendations to enhance productivity. 🤝 Contributing Contributions are welcome! Feel free to submit a pull request or open an issue.