M62 - Generative AI Analytics Dashboard

ITIS 5166 - Backend Application Development - Final Project

A full-stack web application showcasing recent innovations in Generative AI with interactive data visualizations, user authentication, and a production-ready deployment pipeline.

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Quick Start

Prerequisites

• Docker & Docker Compose installed
• Ports 80, 443, and 3000 available

Run Locally

# 1. Copy environment variables
cp .env.example .env

# 2. Start all services
docker compose up -d --build

# 3. Open in browser
# http://localhost (or https://localhost)

# 4. Log in
# Username: matthew
# Password: matthew

That's it! All three services (MongoDB, Backend, Frontend) start automatically.

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What's Running

Service	Purpose	Port
MongoDB	Data storage for AI models and releases	27017 (internal)
Backend (FastAPI)	REST API serving authentication & data endpoints	3000 (internal)
Frontend (React + Nginx)	Web UI with charts and dashboards	80/443 (public)

Data note: All data is seeded from static JSON files on startup (mongo-init/seed.sh, model_performance.json, model_releases.json (genai_adoption.json is unused)). The database resets on every container restart.

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Development

Local Setup (without Docker)

# Concurrently allows both backend and frontend services to run through one terminal
# MongoDB database should already be connected and seeded with JSON data
cd frontend
npm run dev
# Runs API at http://localhost:3000
# Runs frontend at http://localhost:5173

Quality Checks

# Frontend lint/format/typecheck
npm run lint
npm run format
npm run typecheck

# Backend lint/format/testing
ruff check backend
ruff format --check backend
pytest backend

Deployment

One-Time Server Setup

# SSH into your (I use DigitalOcean) server
ssh deploy@your-server

# Clone repo
git clone https://github.com/mbachel/M62.git
cd M62

# Copy environment file
cp .env.example .env
# Edit .env with your JWT_SECRET and MongoDB URL
# Keep the MongoDB URL default if you plan to let it seed itself

# Test startup
docker compose up -d --build

Deploy Updates

After pushing changes to main:

ssh deploy@your-server 'cd /home/deploy/M62 && git pull && docker compose up -d --build'

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Deployment Sanity Check

After deploying, verify everything is running:

# SSH into server
ssh deploy@your-server

#Check all services running
cd home/deploy/M62
docker compose ps

#Expected output: all services UP (not Exit)

View Logs

# Real-time logs from all services
docker compose logs -f

# Tail last 50 lines
docker compose logs -n 50 -f

# Specific service
docker compose logs -f backend

Restart / Rebuild

# Restart without rebuild
docker compose restart

# Full restart with code rebuild
docker compose up -d --build

# Stop all services
docker compose down

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Project Status

What's Maintained

• ✅ Bug fixes and security updates via Dependabot
• ✅ CI/CD pipeline runs on all PRs and pushes
• ✅ Automated deployment on push to main

What's NOT Maintained

• ❌ New features (this is the final project - it's complete)
• ❌ Data updates (static JSON files; no backend admin panel)
• ❌ Active development (archive expected upon graduation)

This is a project snapshot, not an actively developed product.

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Architecture

.
├── frontend/                 # React + Vite + Tailwind
│   ├── Dockerfile            # Nginx reverse proxy
│   ├── nginx.conf            # SSL + API routing
│   └── app/                  # React components & pages
├── backend/                  # Python FastAPI
│   ├── Dockerfile            # FastAPI application
│   ├── main.py               # Routes & business logic
│   ├── auth.py               # JWT authentication
│   └── tests/                # Pytest suite
├── docker-compose.yml        # Service orchestration
├── .github/workflows/        # GitHub Actions CI/CD
│   └── ci-deploy.yml         # Lint, test, deploy pipeline
└── .env.example              # Environment template

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Tech Stack

• Frontend: React 19, React Router, Tailwind CSS, D3.js charts, Vite
• Backend: Python 3.13, FastAPI, OAuth2/JWT, Pytest
• Database: MongoDB 8.2
• Infrastructure: Docker, Docker Compose, Nginx (SSL/reverse proxy)
• CI/CD: GitHub Actions (lint, test, deploy via SSH)
• Tooling: ESLint, Prettier, Ruff, Pytest, Dependabot

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Features

• Model Performance Dashboard: Compare top-tier LLMs across benchmarks
• Release Timeline: Track AI model releases and innovations
• User Authentication: Secure login with JWT tokens
• Responsive UI: Mobile-friendly design with theme toggle
• Data Visualizations: Interactive charts powered by D3.js

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Support & Issues

This project is no longer in active development. For questions during handoff:

1. Check the Architecture section above
2. Review docker-compose.yml for service configuration
3. Check .env.example for required environment variables
4. Review GitHub Actions workflow (.github/workflows/ci-deploy.yml) for deployment process

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Created: Fall 2025
Status: Complete (Final Project)