🔍 WRAP - Web-based Resource for Analyzing Papers

Legal Document Analysis & Management System

📋 Table of Contents

• Overview
• System Architecture
• Key Features
• Technology Stack
• Getting Started
  • Prerequisites
  • Installation
• Components
  • Chrome Extension
  • Web Application
  • NLP Backend
• Usage
• Contributing
• License

🎯 Overview

WRAP is a comprehensive legal document analysis system developed as a capstone project at the University of Utah. It combines a Chrome extension, web application, and NLP backend to automatically detect, analyze, and manage legal documents such as Terms and Conditions, Privacy Policies, and Contract Agreements.

🏗️ System Architecture

The system consists of three main components:

1. Chrome Extension: Detects and captures legal documents from websites
2. Web Application: Manages user interactions and document viewing
3. NLP Backend: Processes and analyzes legal documents using advanced NLP techniques

✨ Key Features

Chrome Extension

• 🔄 Automatic legal document detection
• 📊 Immediate document analysis and reporting
• 💾 Automatic saving to database
• 📤 Manual document upload option
• ⚙️ Customizable detection settings

Web Application

• 📱 Responsive Material-UI design
• 📊 Interactive data visualization
• 🔄 Real-time updates using Socket.IO
• 📄 PDF generation and handling
• 🔍 Advanced search functionality

NLP Backend

• 🤖 CUDA-accelerated document processing
• 📝 Automatic report generation
• 🎯 Legal document classification
• 📊 Key information extraction
• 🔄 Real-time processing capabilities

💻 Technology Stack

Frontend

• React.js with Material-UI
• Chart.js & Recharts
• Socket.IO Client
• Axios

Backend

• Node.js & Express
• MongoDB with Mongoose
• Socket.IO
• JWT Authentication
• PDF Processing Tools

NLP Stack

• Python with CUDA support
• PyTorch
• Flask API
• NVIDIA GPU Requirements

🚀 Getting Started

Prerequisites

• Node.js (Latest LTS version)
• Python 3.8+
• NVIDIA GPU with CUDA support
• MongoDB
• Chrome browser (for extension)

Installation

1. Clone the repository

git clone https://github.com/LianruiBruce/wrap.git
cd wrap

2. Set up the main backend

npm install
cp .env.example .env  # Configure your environment variables
npm start

3. Set up the frontend

cd website_frontend
npm install
npm start

4. Set up the NLP environment

cd NLP
python -m venv nlp-env
source nlp-env/bin/activate  # On Windows: nlp-env\Scripts\activate
pip install -r requirements.txt

5. Start the Flask server

export FLASK_APP=src/app.py  # On Windows: $env:FLASK_APP = "src/app.py"
flask run --host=0.0.0.0 --port=5000

🎮 Usage

Chrome Extension

1. Open the extension before visiting a webpage
2. Navigate to a page with legal documents
3. The extension will automatically detect and analyze the document
4. View generated reports directly in the extension

Web Application

1. Access the web interface at wrapcapstone.com
2. Log in to your account
3. View detected documents and generated reports
4. Use the search functionality to find specific documents
5. Generate and download PDF reports

🤝 Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

👥 Contributors

• Lianrui Geng
• Xinyang Wang
• Daniel Coimbra
• Joey Cai

📄 License

Distributed under the MIT License. See LICENSE for more information.

📞 Contact

• Project Website: wrapcapstone.com
• Project Link: GitHub Repository

🙏 Acknowledgments

• University of Utah
• Our project advisors and mentors
• All contributors who helped with the project