Learn how to build an API that trains and generate photos featuring... you! Using FastAPI, Upstash, Replicate, Jupyter, and more
Tech Stack
- Python 3.13
- Django (
pip install "Django>=5.1,<5.2"
) - Upstash - serverless redis, qstash for async endpoint scheduling, rate limiting, caching, and more.
- Replicate - train and run generative ai model featuring your face
- Python requests (
pip install requests
) - Jupyter (
pip install jupyter
) - Python Decouple to load environment variables (e.g.
.env
) with type casting and default values. - ostris/flux-dev-lora-trainer. Model made to allow you to fine-tune FLUX with your own images (pre-trained model designed for your training)
Download the following:
Open a command line (Terminal, VSCode Terminal, Cursor Terminal, Powershell, etc)
Clone this Repo
mkdir -p ~/dev/superme-api
cd ~/dev/superme-api
git clone https://github.com/codingforentrepreneurs/super-me-photo-ai-api .
Checkout the start branch
git checkout start
Make the code yours
rm -rf .git
git init
git add --all
git commit -m "I am the capitan now"
Create a Python vitual environment macOS/Linux/WSL
python3.12 -m venv venv
source venv/bin/activate
windows powershell
c:\Path\To\Python312\python.exe -m venv venv
.\venv\Scripts\activate
Install requirements
(venv) python -m pip install pip --upgrade
(venv) python -m pip install -r requirements.txt
To add support for .heic
images (e.g. iPhone images) install libheif
via homebrew:
brew install libheif
(venv) python -m pip install pillow-heif
If on linux or Docker, you can use sudo apt-get install libheif-dev