Legal AI Query & Referral System - COMP30022

A unified platform for University of Melbourne researchers to submit grants-related queries and receive AI-powered assistance or escalation to the legal team.

🚀 Getting Started

New to the project? Follow our documentation in order:

👉 📚 Start Here - Documentation Guide

Or jump directly to:

1. ⚙️ Setup Guide - Get your environment running
2. 🌿 Git Workflow - Learn our development process
3. 💻 Development Guide - Daily development practices

Tech Stack

• Frontend: Next.js/React with TypeScript
• Backend API: Python Flask
• Database: MongoDB
• AI Service: Python microservice with RAG capabilities
• Containerization: Docker & Docker Compose

Project Structure

COMP30022/
├── frontend/                # Next.js application
├── backend/                 # Flask API server
├── ai-service/             # AI/LLM microservice
├── docker/                 # Docker configurations
├── docs/                   # Documentation
├── scripts/                # Utility scripts
└── docker-compose.yml      # Orchestration

Quick Start

Prerequisites

• Docker & Docker Compose
• Make (optional)

No local Python/Node.js required - fully containerized!

# Clone the repository
git clone https://github.com/yourusername/COMP30022.git
cd COMP30022

# Start development environment
make dev-up
# or manually:
docker-compose -f docker-compose.yml -f docker-compose.dev.yml up

# Access the application
# Frontend: http://localhost:3000
# Backend API: http://localhost:5000
# AI Service: http://localhost:8000

🚢 Deploying to Railway

🎯 DEPLOYING NOW? → START HERE ← Complete step-by-step guide!

🚨 Already deployed and having issues? See RAILWAY-QUICK-FIX.md for troubleshooting.

📋 Complete deployment guide: See .railway-env-template.md for detailed setup instructions.

Quick Setup:

1. Add MongoDB database to your Railway project
2. Configure environment variables for each service (see template)
3. Set Docker build variables for each service:
   • RAILWAY_DOCKERFILE_PATH: Path to production Dockerfile (e.g., backend/Dockerfile.prod)
   • RAILWAY_DOCKER_BUILD_CONTEXT: . (monorepo root)
4. Deploy services in order: MongoDB → AI Service → Backend → Frontend

Critical Environment Variables:

Frontend (must be set before deployment - required at build time):

NEXT_PUBLIC_API_URL=https://${{backend.RAILWAY_PUBLIC_DOMAIN}}/api
NEXT_PUBLIC_AI_SERVICE_URL=https://${{ai-service.RAILWAY_PUBLIC_DOMAIN}}
RAILWAY_DOCKERFILE_PATH=frontend/Dockerfile.prod
RAILWAY_DOCKER_BUILD_CONTEXT=.

Backend:

MONGODB_URI=${{MongoDB.MONGO_URL}}
AI_SERVICE_URL=https://${{ai-service.RAILWAY_PRIVATE_DOMAIN}}
CORS_ORIGINS=https://${{frontend.RAILWAY_PUBLIC_DOMAIN}}
FLASK_SECRET_KEY=<generate-secure-random-string>
JWT_SECRET_KEY=<generate-secure-random-string>
RAILWAY_DOCKERFILE_PATH=backend/Dockerfile.prod
RAILWAY_DOCKER_BUILD_CONTEXT=.

AI Service:

CORS_ALLOW_ORIGINS=https://${{frontend.RAILWAY_PUBLIC_DOMAIN}},https://${{backend.RAILWAY_PUBLIC_DOMAIN}}
RAILWAY_DOCKERFILE_PATH=ai-service/Dockerfile.prod
RAILWAY_DOCKER_BUILD_CONTEXT=.

⚠️ Important:

• Use PUBLIC domains for frontend (users access it externally)
• Use PRIVATE domains for backend-to-ai-service communication (internal)
• Frontend NEXT_PUBLIC_* vars must be set BEFORE deployment
• If you change NEXT_PUBLIC_* vars, you MUST redeploy the frontend

📖 Troubleshooting: See .railway-env-template.md for common issues and solutions.

Development Workflow

GitFlow Strategy

We use GitFlow with main and develop branches:

# Start development
git checkout develop && git pull origin develop
git checkout -b feature/SPRNT2-XX-description

# Daily workflow
make test    # Run tests (containers must be running)
make format  # Format code
make lint    # Lint code

# Create PR to develop branch
# Code review → Squash merge

Commit Format

feat(SPRNT2-XX): add chat interface

Implement real-time messaging with validation

Closes SPRNT2-XX

Team

• Product Owner: Adam
• Frontend Lead: Farah
• Backend Lead: Himank
• AI Lead: Yusuf
• Scrum Master: Bryan

Features

• Fully containerized: Zero local dependencies
• CI/CD pipeline: Automated testing, linting, formatting
• Microservices: Frontend, Backend, AI Service, Database
• Hot reload: Development with live code changes

📚 Documentation

📋 Quick Access:

• 📚 Documentation Index - Start here for complete guide
• ⚙️ Setup Guide - Environment setup
• 🌿 Git Workflow - Branching and commits
• 💻 Development Guide - Daily workflow
• 🏗️ Project Structure - Codebase organization
• 🤖 Technical Context - Detailed technical info

🎯 For Your Role:

• New Developer? → Documentation Index
• Code Review? → Git Workflow
• Need Architecture? → Project Structure