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Build an interactive web UI for a Python machine learning model by wrapping functions with pre-built input and output components like textboxes, sliders, and images to create accessible web applications.

Create custom layouts for Python web app interfaces using Blocks for fine-grained control over component arrangement, or use Interface for simpler, rapid UI prototyping without front-end expertise.

The best way to make a chatbot or image editor demo in Python is using interactive web UI components that support event handling and rapid prototyping directly from your code.

You do not need front-end development skills to create a machine learning demo, as the framework provides a component library to build interactive web applications directly from Python code.

Event handling in a Python web app for data visualization works by connecting UI components to Python functions, allowing interactive updates and rapid prototyping without writing front-end code.

You can let users upload images and see model predictions by defining an image input component and connecting it to your classification function to display the output prediction interactively.