OssamaLouati/Legal-AI_Project

The Automated Legal Document Analysis Platform is a powerful web application that automates the laborious process of analyzing legal documents. By leveraging cutting-edge technologies such as Next.js, NLP, and machine learning models, our platform extracts relevant information and identifies potential risks from legal documents.

TypeScript

79

46 commits

updated Mar 15, 2026

See the code

README

Legal AI — Automated Legal Document Analysis Platform

Full-stack application for contract Q&A and clause understanding.

  • client/: Next.js + NextAuth (Google OAuth) UI
  • server/: Flask API (Gunicorn) serving ML/NLP endpoints

Quickstart (Docker)

1) Prerequisites

  • Docker Desktop or Podman (this repo currently uses podman-compose on macOS)

2) Configure environment

Create a local env file (never commit secrets):

cp client/.env.local.example client/.env

Edit client/.env and set at least:

  • NEXTAUTH_URL=http://localhost:3000
  • NEXTAUTH_SECRET=... (generate with openssl rand -base64 32)
  • GOOGLE_ID=...
  • GOOGLE_SECRET=...

Also:

  • NEXT_PUBLIC_BACKEND_URL=http://127.0.0.1:5001

3) Build & run

docker compose up -d --build

Open:

Local dev (without Docker)

Backend

cd server
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
gunicorn -b 127.0.0.1:5001 app:app --reload

Frontend

cd client
npm install
npm run dev

Key Features

  • Contract upload + question selection
  • Reading comprehension model (SQuAD-style)
  • Paraphrasing (T5-based)
  • Sentiment analysis (TextBlob)

Disclaimer

This project is provided for research/education and is not a substitute for professional legal advice.

OssamaLouati/Legal-AI_Project

The Automated Legal Document Analysis Platform is a powerful web application that automates the laborious process of analyzing legal documents. By leveraging cutting-edge technologies such as Next.js, NLP, and machine learning models, our platform extracts relevant information and identifies potential risks from legal documents.

TypeScript

79

46 commits

updated Mar 15, 2026

See the code

README

Legal AI — Automated Legal Document Analysis Platform

Full-stack application for contract Q&A and clause understanding.

  • client/: Next.js + NextAuth (Google OAuth) UI
  • server/: Flask API (Gunicorn) serving ML/NLP endpoints

Quickstart (Docker)

1) Prerequisites

  • Docker Desktop or Podman (this repo currently uses podman-compose on macOS)

2) Configure environment

Create a local env file (never commit secrets):

cp client/.env.local.example client/.env

Edit client/.env and set at least:

  • NEXTAUTH_URL=http://localhost:3000
  • NEXTAUTH_SECRET=... (generate with openssl rand -base64 32)
  • GOOGLE_ID=...
  • GOOGLE_SECRET=...

Also:

  • NEXT_PUBLIC_BACKEND_URL=http://127.0.0.1:5001

3) Build & run

docker compose up -d --build

Open:

Local dev (without Docker)

Backend

cd server
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
gunicorn -b 127.0.0.1:5001 app:app --reload

Frontend

cd client
npm install
npm run dev

Key Features

  • Contract upload + question selection
  • Reading comprehension model (SQuAD-style)
  • Paraphrasing (T5-based)
  • Sentiment analysis (TextBlob)

Disclaimer

This project is provided for research/education and is not a substitute for professional legal advice.