SuperMe - Generative Photo AI

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)

Tutorial

• Let's build a AI Photo Generator with Python and FastAPI

Getting Started

Download the following:

• git
• VSCode (or Cursor)
• Python

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