FurEverAI

Full-stack ML application with Next.js frontend and Flask backend.

Project Structure

FurEverAI/
├── client/          # Next.js frontend (Port 3000)
│   ├── app/         # App Router pages
│   ├── lib/         # API helpers and utilities
│   └── .env.local   # Environment variables
└── server/          # Flask backend (Port 5000)
    ├── server.py    # Main Flask app
    └── requirements.txt

Quick Start

Backend Setup (Flask)

cd server
python -m venv .venv
Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope Process
. .venv\Scripts\Activate.ps1
pip install -r requirements.txt
python server.py

Backend runs at: http://localhost:5000

Frontend Setup (Next.js)

cd client
npm install
npm run dev

Frontend runs at: http://localhost:3000

Team Workflow

Frontend Developer

• Work in client/app/ for pages and UI
• Use client/lib/api.ts to call backend endpoints
• All styling in client/app/globals.css or component-level
• Backend connection is already configured

ML Team

• Work in server/server.py - implement model in /api/predict endpoint
• Add ML dependencies to server/requirements.txt
• Backend is configured with CORS for frontend communication

API Endpoints

• GET /api/health - Check server status
• GET /api/home - Home endpoint
• POST /api/predict - Model prediction (accepts JSON or file upload)

Environment Variables

Create client/.env.local:

NEXT_PUBLIC_API_URL=http://localhost:5000

Notes

• Backend uses Flask with CORS enabled
• Frontend uses Next.js 14+ App Router
• API layer abstracted in lib/api.ts for clean separation