Case Compass: A Legal Precedent Search Engine

Case Compass is a cutting-edge legal precedent search engine designed to assist legal professionals and enthusiasts in quickly finding relevant case summaries. Leveraging state-of-the-art NLP models and a user-friendly Streamlit interface, it offers a seamless experience for navigating through a comprehensive database of legal cases.

Features

• Multiple Search Algorithms: Utilize TF-IDF, Doc2Vec, and BERT models for flexible and accurate search capabilities.
• Automatic Summary Generation: Generate concise summaries of legal cases using Google's Generative AI.
• Database Management: Store and retrieve case summaries efficiently with SQLite.
• User Interface: A clean and intuitive interface built with Streamlit for easy navigation and operation.

Installation

Before running the application, ensure you have Python 3.8+ installed. Clone this repository and navigate to the project directory. Install the required dependencies with:

pip install -r requirements.txt

This application requires access to Google Generative AI models, so make sure to set up your Google API key and store it in a .env file as GOOGLE_API_KEY=<your_api_key_here>.

Running the Application

To launch the application, run:

streamlit run your_script_name.py

Replace your_script_name.py with the path to the script you want to run.

Usage

Upon launching the application, select a search engine type (TF-IDF, Doc2Vec, or BERT) and enter your search query. The application will display matching cases along with options to generate summaries. Summaries are automatically saved to the database for future reference.

Contributing

We welcome contributions! If you have suggestions for improvements or bug fixes, please feel free to make a pull request or open an issue.

License

This project is open-sourced under the MIT License. See the LICENSE file for more details.

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