Legalizer - LLM Based Legal Document Summarizer and Doubt Solver

Legalizer is a web application that helps users summarize legal documents and get answers to legal queries using advanced language models. Users can upload PDF or image files, and interact with an AI assistant through a user-friendly chat interface. The backend is built with Flask and leverages the Groq LLM model for summarization and question answering.

Features

• Document Summarization: Upload PDF or image files to extract and summarize legal content using the Groq LLM model.
• Legal Query Assistance: Chat with the AI to receive answers to legal questions.
• User-Friendly Interface: Clean, modern UI for easy interaction.

Project Structure

legalizer
├── src
│   ├── app.py                # Main application file
│   ├── static
│   │   ├── css
│   │   │   └── styles.css    # CSS styles for the application
│   ├── templates
│   │   ├── index.html        # Landing page template
│   │   └── chat.html         # Chat interface template
├── requirements.txt          # Python dependencies
├── Dockerfile                # Docker build instructions
├── docker-compose.yml        # Docker Compose configuration
└── README.md                 # Project documentation

Installation

1. Clone the repository:

   git clone <repository-url>
   cd legalizer
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Set up environment variables:

   • Create a .env file and add your GROQ_API_KEY.

4. (Optional) Run with Docker:

   docker-compose up --build
   

Usage

• Start the Flask application:

  python src/app.py
  

  Or use Docker as above.

• Access the app: Open your browser and go to http://127.0.0.1:5000.

• Interact:

  • Use the landing page to navigate to the chat interface.
  • Upload documents or type legal questions to get AI-powered responses.

Contributors

• Satwik M badiger
• Mohit R
• M Rahul Sagayaraj
• Mahesh Sharma

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.