readme_template.md

<div align="center">

  [<img src="readme_files/gradio.svg" alt="gradio" width=300>](https://gradio.app)<br>
  <em>Build & share delightful machine learning apps easily</em>

  [<img src="https://circleci.com/gh/gradio-app/gradio.svg?style=svg" alt="circleci">](https://circleci.com/gh/gradio-app/gradio)
  [<img src="https://codecov.io/gh/gradio-app/gradio/branch/master/graph/badge.svg" alt="codecov">](https://app.codecov.io/gh/gradio-app/gradio)
  [![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-3.7+-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/)
</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 manipulation and interpretation 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)

## 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},
}
```