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Gradio

Gradio is an open-source Python library for rapidly building interactive web interfaces and demonstrations for machine-learning models and applications.

How 3 Manning books explain it

Hugging Face in Action

A Gradio application is a machine-learning web application created with the Gradio library.

How it is used
Builds interactive web interfaces around machine-learning models, data-science workflows, query engines, and chatbot functions.
How deep it goes
Explains Interface parameters, component data flow, installation, sharing, authentication, deployment, and chatbot state without descending into web-development internals.
Examples
Demonstrates grayscale conversion, image segmentation, receipt queries, simple chatbots, and stateful GPT4All conversations.
What you can do after
Build it from scratch, bind a callable to typed inputs and outputs, launch it locally, share it temporarily, or deploy it on Hugging Face Spaces.

Read how Hugging Face in Action explains Gradio →

LLMs in Production

Gradio is an open-source Python library for building interactive web interfaces around machine-learning functions and models.

How it is used
Builds interactive web interfaces for machine-learning models, especially rapid chatbot demos and feedback-enabled applications.
How deep it goes
Explains the library’s interface model and demonstrates chatbot wiring, history handling, streaming, and automatic interaction controls.
Examples
Uses a local LLM chat app with streamed responses, conversation history, Stop, Retry, Undo, and a feedback form.
What you can do after
Builds a customizable chatbot interface around an API-backed model without writing HTML, CSS, or JavaScript.

Read how LLMs in Production explains Gradio →

Deep Learning with PyTorch, Second Edition

A Python library for quickly building interactive web demos and prototypes around machine learning models.

How it is used
Deploys machine learning functions as quickly testable, interactive web demos and shareable prototypes.
How deep it goes
Explains interface construction and launching through short examples, but stops short of production-scale serving and performance.
Examples
Demonstrates a greeting interface and a Stable Diffusion text-to-image application.
What you can do after
Build interactive model demos, test them in a browser, and share them through a public link.

Read how Deep Learning with PyTorch, Second Edition explains Gradio →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.