In this article, explore how to develop an AI-powered logo generator using DALL-E, Azure OpenAI and Azure Kubernetes Service (AKS).
What We'll Cover:​
- Generating images with DALL-E
- Building a web interface
Building an AI-Powered Logo Variation Generator with Azure OpenAI and AKS (1)​
Have you ever wondered how to create unique and eye-catching logos for your brand or project? Do you want to unleash your creativity and experiment with AI? If so, you might be interested in Azure OpenAI, a new Azure service granting access to some of the most advanced AI models globally, including DALL-E 2.
With the ability to interpret detailed text prompts, DALL-E 2 can generate images ranging from realistic to imaginative. It can merge elements, characteristics, and artistic influences to generate unique illustrations, emblems, or images with a true-to-life appearance.
In this article, we’ll explore how to build an Intelligent App that uses DALL-E to create logos. Intelligent Apps harness artificial intelligence (AI), machine learning (ML), and data analytics to deliver personalized and data-driven user experiences. They can understand the user’s intent, make predictions, automate tasks, generate content, or provide recommendations based on data and analytics.
After completing this tutorial, you’ll know how to:
- Set up Azure OpenAI.
- Create a Python back end using FastAPI that uses DALL-E to create logo variations.
- Build a web interface that lets you upload a logo, enter a text prompt, and view logos generated by DALL-E.
- Deploy your app using Azure Kubernetes Service (AKS).
Let’s get started!
Creating an AI-Powered Logo Variation Generator​
Before diving into the details of how to build and deploy the app, let’s look at its basic architecture. The app consists of three main parts:
- A Python back end that uses the OpenAI Python Library to communicate with Azure OpenAI and FastAPI to serve logo generation requests.
- A web UI built with HTML, CSS, and JavaScript. This setup lets us select a logo, enter instructions, submit them to the back end, and view the logos provided by DALL-E.
- An AKS cluster that hosts the app. This is AKS Azure’s managed Kubernetes service, which we’ll use to deploy the app as a containerized application.
For a preview of the final product, review the complete project code.
Prerequisites​
To follow along, you need:
- An Azure subscription with access to Azure OpenAI. Note that you’ll have to apply for approval to access Azure OpenAI.
- A DALL-E model deployed to Azure. See the resource deployment guide for further instructions on deploying a model. You can currently only deploy DALL-E models to resource groups in the
eastus
region using thedalle2
model. - The deployment name, endpoint, and API key for your DALL-E model. See the “Retrieve key and endpoint” section in the Azure OpenAI docs for instructions on how to find your model’s endpoint URL and API key.
- The Azure CLI installed and signed in to the Azure subscription containing your DALL-E model deployment
- Docker to package and deploy your application
- kubectl to manage your AKS cluster
If you don’t yet have Docker or kubectl
installed, Docker Desktop includes both and is the quickest way to get up and running.