gradio/readme_template.md

<div align="center">

[<img src="readme_files/gradio.svg" alt="gradio" width=400>](https://gradio.app)<br>
<em>Build & share delightful machine learning apps easily</em>

[![gradio-backend](https://github.com/gradio-app/gradio/actions/workflows/backend.yml/badge.svg)](https://github.com/gradio-app/gradio/actions/workflows/backend.yml)
[![gradio-ui](https://github.com/gradio-app/gradio/actions/workflows/ui.yml/badge.svg)](https://github.com/gradio-app/gradio/actions/workflows/ui.yml)  
 [![PyPI](https://img.shields.io/pypi/v/gradio)](https://pypi.org/project/gradio/)
[![PyPI downloads](https://img.shields.io/pypi/dm/gradio)](https://pypi.org/project/gradio/)
![Python version](https://img.shields.io/badge/python-3.8+-important)
[![Twitter follow](https://img.shields.io/twitter/follow/gradio?style=social&label=follow)](https://twitter.com/gradio)

[Website](https://gradio.app)
| [Documentation](https://gradio.app/docs/)
| [Guides](https://gradio.app/guides/)
| [Getting Started](https://gradio.app/getting_started/)
| [Examples](demo/)
| [中文](readme_files/zh-cn#readme)

</div>

# Gradio: Build Machine Learning Web Apps — in Python

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.

![Interface montage](readme_files/header-image.jpg)

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 input manipulation tools.

$getting_started

## Open Source Stack

Gradio is built with many wonderful open-source libraries, please support them as well!

[<img src="readme_files/huggingface_mini.svg" alt="huggingface" height=40>](https://huggingface.co)
[<img src="readme_files/python.svg" alt="python" height=40>](https://www.python.org)
[<img src="readme_files/fastapi.svg" alt="fastapi" height=40>](https://fastapi.tiangolo.com)
[<img src="readme_files/encode.svg" alt="encode" height=40>](https://www.encode.io)
[<img src="readme_files/svelte.svg" alt="svelte" height=40>](https://svelte.dev)
[<img src="readme_files/vite.svg" alt="vite" height=40>](https://vitejs.dev)
[<img src="readme_files/pnpm.svg" alt="pnpm" height=40>](https://pnpm.io)
[<img src="readme_files/tailwind.svg" alt="tailwind" height=40>](https://tailwindcss.com)
[<img src="readme_files/storybook.svg" alt="storybook" height=40>](https://storybook.js.org/)
[<img src="readme_files/chromatic.svg" alt="chromatic" height=40>](https://www.chromatic.com/)

## License

Gradio is licensed under the Apache License 2.0 found in the [LICENSE](LICENSE) file in the root directory of this repository.

## Citation

Also check out the paper _[Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild](https://arxiv.org/abs/1906.02569), ICML HILL 2019_, and please cite it if you use Gradio in your work.

```
@article{abid2019gradio,
  title = {Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild},
  author = {Abid, Abubakar and Abdalla, Ali and Abid, Ali and Khan, Dawood and Alfozan, Abdulrahman and Zou, James},
  journal = {arXiv preprint arXiv:1906.02569},
  year = {2019},
}
```