Use FLUX, PyTorch, and Streamlit to Build an AI Image Generation App

The need for AI-generated images has been growing rapidly in recent years. These images are not only used for artistic purposes, but also for practical applications in various industries. For example, in the fashion industry, AI-generated images can be used to create virtual models for showcasing clothing. In the automotive industry, AI-generated images can be used for designing and testing new car models. And the best part? You can now run your own AI image generation machine on Koyeb GPUs.

The FLUX.1 [dev] model (by BlackForestLabs) is an advanced AI image generation model that produces outstanding output quality. It is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. It features competitive prompt following, and is trained using guidance distillation. Additionally, the generated outputs can be utilized for personal, scientific, and non-commercial purposes as outlined in the FLUX.1 [dev] Non-Commercial License.

In this tutorial, we will learn how to set up a Streamlit application, integrate the FLUX model for real-time image generation, and deploy the application using Docker and Koyeb, ensuring a scalable image generation service.

You can deploy the FLUX application as built in this tutorial using the Deploy to Koyeb…