0
stars
49
commits
Python
primary language
Feb 16, 2026
updated
An AI-powered fashion technology application that enables users to virtually try on clothing using advanced machine learning models.
cd frontend
npm install
cp .env.local.example .env.local # Configure environment variables
npm run dev # Start dev server at http://localhost:3000
cd backend
pip install -r requirements.txt
cp .env.example .env # Configure environment variables
# Clone Leffa repository at project root
cd ..
git clone https://github.com/franciszzj/Leffa
# Start backend
cd backend
python main.py # Start dev server at http://localhost:8000
Frontend (.env.local):
NEXT_PUBLIC_API_URL=http://localhost:8000
NEXT_PUBLIC_SUPABASE_URL=your-supabase-url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your-supabase-anon-key
Backend (.env):
SUPABASE_URL=your-supabase-url
SUPABASE_KEY=your-supabase-service-key
GEMINI_API_KEY=your-gemini-api-key
USE_GPU=true
LOG_LEVEL=INFO
ALLOWED_ORIGINS=http://localhost:3000
/
├── frontend/ # Next.js application
├── backend/ # FastAPI ML service
├── Leffa/ # Leffa repository (clone here)
├── data/ # Runtime data storage
├── docs/ # Documentation
├── .kiro/ # Kiro configuration & specs
└── README.md # This file
Once the backend is running, visit:
CPU fallback available but 10-20x slower.
For 3D reconstruction features, see detailed setup guide:
Includes:
# Windows PowerShell
.\dev_start.ps1
cd backend
pytest tests/
cd backend
python scripts/verify_environment.py
[Add your license here]
For issues and questions:
.kiro/steering/backend/app/core/ERROR_HANDLING_GUIDE.mdbackend/3d/SETUP.mdLast Updated: February 15, 2026
Python
37.8%
C
27.5%
TypeScript
15.8%
C++
14.0%
PLpgSQL
2.3%
Shell
1.9%
0
stars
49
commits
Python
primary language
Feb 16, 2026
updated
An AI-powered fashion technology application that enables users to virtually try on clothing using advanced machine learning models.
cd frontend
npm install
cp .env.local.example .env.local # Configure environment variables
npm run dev # Start dev server at http://localhost:3000
cd backend
pip install -r requirements.txt
cp .env.example .env # Configure environment variables
# Clone Leffa repository at project root
cd ..
git clone https://github.com/franciszzj/Leffa
# Start backend
cd backend
python main.py # Start dev server at http://localhost:8000
Frontend (.env.local):
NEXT_PUBLIC_API_URL=http://localhost:8000
NEXT_PUBLIC_SUPABASE_URL=your-supabase-url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your-supabase-anon-key
Backend (.env):
SUPABASE_URL=your-supabase-url
SUPABASE_KEY=your-supabase-service-key
GEMINI_API_KEY=your-gemini-api-key
USE_GPU=true
LOG_LEVEL=INFO
ALLOWED_ORIGINS=http://localhost:3000
/
├── frontend/ # Next.js application
├── backend/ # FastAPI ML service
├── Leffa/ # Leffa repository (clone here)
├── data/ # Runtime data storage
├── docs/ # Documentation
├── .kiro/ # Kiro configuration & specs
└── README.md # This file
Once the backend is running, visit:
CPU fallback available but 10-20x slower.
For 3D reconstruction features, see detailed setup guide:
Includes:
# Windows PowerShell
.\dev_start.ps1
cd backend
pytest tests/
cd backend
python scripts/verify_environment.py
[Add your license here]
For issues and questions:
.kiro/steering/backend/app/core/ERROR_HANDLING_GUIDE.mdbackend/3d/SETUP.mdLast Updated: February 15, 2026
Python
37.8%
C
27.5%
TypeScript
15.8%
C++
14.0%
PLpgSQL
2.3%
Shell
1.9%