Skip to content

Latest commit

 

History

History
137 lines (100 loc) · 3.2 KB

README.md

File metadata and controls

137 lines (100 loc) · 3.2 KB

Litigation Simulator

A cutting-edge legal technology platform for data-driven trial preparation, judge analytics, outcome prediction, and interactive litigation simulation. Built for attorneys and legal teams, with a focus on Commercial Real Estate (CRE) litigation.

Features

  • Judge Analysis: Profiles, writing style, ruling patterns, questioning analysis
  • Case Outcome Prediction: ML-powered predictions, factor analysis, "what-if" scenarios
  • Interactive Simulation: AI-generated judicial questioning, opposing counsel, feedback
  • Strategy Recommendations: Citation and argument suggestions
  • Admin Tools: Data import, model retraining, background tasks

Technical Architecture

  • Backend: FastAPI (Python), async, modular microservices
  • Frontend: React.js (TypeScript), Tailwind CSS, Recharts
  • Database: PostgreSQL (relational), Redis (cache/queue), JSONB for analytics
  • ML/AI: Transformers, scikit-learn, topic modeling, clustering, simulation engine
  • Deployment: Docker Compose, Kubernetes, AWS-ready

Quick Start

1. Clone the Repository

git clone https://github.com/tony-42069/litigation-simulator.git
cd litigation-simulator

2. Environment Setup

  • Python 3.10+
  • Node.js 16+ and npm
  • Docker & Docker Compose
  • PostgreSQL 13+
  • Redis 6+ (can use WSL or Docker)

3. Configure Environment Variables

Copy .env.example to .env and fill in your credentials:

POSTGRES_USER=postgres
POSTGRES_PASSWORD=your_password
POSTGRES_DB=litigation_simulator
POSTGRES_HOST=localhost
POSTGRES_PORT=5432
REDIS_HOST=localhost
REDIS_PORT=6379
COURT_LISTENER_API_TOKEN=your_court_listener_api_token
SECRET_KEY=your_secret_key
DEBUG=True
MODEL_DIR=./models

4. Database Setup

  • Create the database: 
    psql -U postgres -c "CREATE DATABASE litigation_simulator;"
  • Initialize schema: 
    psql -U postgres -d litigation_simulator -f schema.sql

5. Data Import

  • Install dependencies: 
    pip install -r requirements.txt
  • Import initial data from Court Listener: 
    python import_courtlistener_data.py

6. Running the App

  • Backend: 
    uvicorn api-endpoints:app --reload
  • Frontend: 
    cd frontend
npm install
npm start

Deployment

  • Docker Compose: 
    docker compose -f docker-compose.dev.yml up -d
  • Kubernetes & AWS:
    See deployment-instructions.md for full production deployment steps.

Contributing

  1. Fork the repo and create your branch
  2. Commit your changes with clear messages
  3. Push to your fork and submit a pull request

Documentation

License

MIT License

Contact

For questions, support, or partnership inquiries, please open an issue or contact the maintainer.