One of the hottest🔥 models as of June 2022 is DALL-E mini. There are a number of projects and examples utilizing this model as seen here, here and here. There have even been mainstream news articles covering this model.

This article presents a workflow to build a summary of a webpage and then generate an image of this summary. While there are a number of potential use cases for text to image models, this example is focused on showing the power of workflows and also provides interesting insights into how DALL-E mini "sees" the world.

Install dependencies

Install txtai and all dependencies.

All credit for the DALL-E mini models and code goes to https://github.com/borisdayma/dalle-mini and https://github.com/kuprel/min-dalle.

pip install txtai tika min-dalle ipyplot 

Build a DALL-E pipeline

Let's first construct a txtai pipeline that generates images using DALL-E mini.

from min_dalle import MinDalle from txtai.pipeline import Pipeline class Dalle(Pipeline): def __init__(self): self.model = MinDalle(is_mega=False, is_verbose=False) def __call__(self, texts, seed, prefix): results = [] for text in texts: text = prefix + text results.append(self.model.generate_image(text, seed)) return results 

Build DALL-E workflow

Next we'll define a txtai workflow as YAML. This workflow extracts text at a specified URL, builds a summary and then generates an image for the summary text.

This workflow can be run from Python as shown below or as a API service.

from txtai.app import Application app = Application(""" __main__.Dalle: summary: path: sshleifer/distilbart-cnn-12-6 textractor: join: true lines: false minlength: 100 paragraphs: true sentences: false workflow: draw: tasks: - action: textractor task: url - action: summary args: [0, 60, 0] - action: __main__.Dalle args: [1024, "Illustration of "] """) 

Generate webpage summary images

Now that the workflow is up, let's generate some images! The following example generates images for a set of Wikipedia articles. Give this a try for articles, recipes or any other descriptive web page.

It's also fun to generate images for random Wikipedia pages using this url: https://en.wikipedia.org/wiki/Special:Random

import ipyplot # Build list of Wikipedia article URLs captions = ["Catholic Church", "Magic Kingdom", "Epcot", "Mountain", "Tundra", "War of 1812", "Chinese Cuisine", "Indian Cuisine", "Italian Cuisine", "Romanian cuisine", "Football", "Artificial Intelligence", "Galaxy", "Fjord", "Island"] urls = [f"https://en.wikipedia.org/wiki/{url.replace(' ', '_')}" for url in captions] # Run workflow to generate images with DALL-E mini images = list(app.workflow("draw", urls)) # Plot images ipyplot.plot_images(images, captions, img_width=256) 

Wrapping up

This article walked through an example on how to build a txtai workflow to generate webpage summary images. DALL-E mini is a fascinating model and it's a lot of fun to "see" how the model works. Give it a try yourself!