What is Gradio?
Gradio is designed to simplify the frontend development of machine learning models, allowing developers to launch interactive web applications with just a few lines of Python code—no need to master JavaScript, CSS, or frontend development. It’s suitable for both local prototype validation and building production‑grade web apps, and it offers free hosting on Hugging Face Spaces, with automatic scaling and one‑click sharing.
Key features
Single-command installation (pip install gradio) and ultra-simplified launching (e.g., demo.launch()), all written in pure Python with zero frontend development expertise.
Supports over 40 input and output components, covering a wide range of data types including images, audio, video, 3D models, data tables, chat interfaces, annotated text, file browsers, and more.
Use cases and audience
Python developers, machine learning engineers, data scientists, AI researchers
- Quickly create interactive web interfaces for machine learning models
- Generate a shareable link on the fly during local development for colleagues or clients to test.
- Deploy to Hugging Face Spaces for a permanent, serverless online demo.
Supports multiple input types, including text, images, audio, video, 3D models, DataFrames, files, date and time, checkboxes, radio buttons, and more.
Supports multiple output types, including text, images, audio, video, 3D models, DataFrames, charts (Plot), highlighted text (HighlightedText), chat interfaces (Chatbot), annotated images (AnnotatedImage), and more.
How to use
- 01
Installation: pip install gradio
- 02
Define Python functions (e.g., to process text, images, and other inputs)
- 03
Build interfaces using gr.Interface or gr.Blocks, specifying inputs and outputs.
- 04
Call demo.launch() to start the local service; add share=True to generate a temporary sharing link.
Official website & sources
Sources
Updated on 2026-10-26
