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[<img src="readme_files/gradio.svg" alt="gradio" width=300> ](https://gradio.app )< br >
< em > Build & share delightful machine learning apps easily< / em >
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[](https://github.com/gradio-app/gradio/actions/workflows/backend.yml)
[](https://github.com/gradio-app/gradio/actions/workflows/ui.yml)
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[](https://pypi.org/project/gradio/)
[](https://pypi.org/project/gradio/)

[](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/ )
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| [中文 ](readme_files/zh-cn#readme )
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# 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.
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
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Gradio is useful for:
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- **Demoing** your machine learning models for clients/collaborators/users/students.
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- **Deploying** your models quickly with automatic shareable links and getting feedback on model performance.
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- **Debugging** your model interactively during development using built-in manipulation and interpretation tools.
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$getting_started
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## Open Source Stack
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Gradio is built with many wonderful open-source libraries, please support them as well!
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[<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 )
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## License
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Gradio is licensed under the Apache License 2.0 found in the [LICENSE ](LICENSE ) file in the root directory of this repository.
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## Citation
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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.
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```
@article {abid2019gradio,
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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},
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}
```