Gradio is an open-source Python library that is used to build machine learning and data science demos and web applications.

With Gradio, you can quickly create a beautiful user interface around your machine learning models or data science workflow and let people "try it out" by dragging-and-dropping in their own images, pasting text, recording their own voice, and interacting with your demo, all through the browser.

Gradio is useful for:

  • Demoing your machine learning models for clients / collaborators / users / students
  • Deploying your models quickly with automatic shareable links and getting feedback on model performance
  • Debugging your model interactively during development using built-in manipulation and interpretation tools


Features

  1. A Dozen of built-in UI elements
  2. Supports images
  3. Real-time live interface
  4. Supports multiple inputs and outputs
  5. Built-in DataFrames and Graphs support
  6. Flagging option
  7. Supports CSV, Excel, TSV, JSON formats
  8. Control everything thru blocks
  9. Easy to share demos through Gardio.org
  10. Share and host your code on Hugging Face Spaces

Requirements

  • Python 3.7+

Tech Stack

Gradio is built using:

  1. Python
  2. Sevlte
  3. Vite.js
  4. Tailwind CSS
  5. Python FastAPI

License

Gradio is released under the Apache-2.0 license.

Resources

  1. GitHub
  2. Website