TechGnana

  Chapter-2 Introduction In Chapter-1, you saw how easy it is to build a basic Gradio app. But the real power of Gradio comes from its rich variety of input and output components . Whether you're working with images, text, audio, video, or files — Gradio provides ready-made UI elements to make your models interactive with just a few lines of code. In this article, we’ll explore: All major inputs and outputs Parameter tuning for customization How to chain multiple components/functions together Textbox Use When: You want the user to input plain text (sentences, prompts, numbers as strings, etc.) Key Parameters: label : Display name lines : Height of textbox (default = 1) placeholder : Hint inside the box value : Default value Example: import gradio as gr def reverse ( text ):     return text[:: -1 ] gr.Interface(fn=reverse, inputs=gr.Textbox(label= "Enter text" ), outputs= "text" ).launch() Image  Use When: You're building an i...

Chapter-1 Introduction In the fast-moving world of machine learning, showcasing your model with a working demo is just as important as building the model itself. Whether you're a researcher, student, or engineer, Gradio allows you to turn models into interactive web apps—without needing full-stack development skills. This article kicks off a comprehensive series exploring Gradio , from beginner-friendly tutorials to advanced case studies. In this first part, we’ll walk you through what Gradio is, why it’s useful, and how to build your very first app. What is Gradio? Gradio is an open-source Python library that lets you quickly create customizable UI components for machine learning models or any Python function. You can run the interface locally or host it online—making it ideal for collaboration, demonstrations, or teaching. Key Features: Easy-to-use Python API Supports image, text, audio, video, and file inputs Integrates with TensorFlow, PyTorch, Hugging Face, etc. ...