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.dockerignore

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+# Python build
+.eggs/
+gradio.egg-info/*
+!gradio.egg-info/requires.txt
+!gradio.egg-info/PKG-INFO
+dist/
+*.pyc
+__pycache__/
+*.py[cod]
+*$py.class
+build/
+
+# JS build
+gradio/templates/frontend/static
+gradio/templates/frontend/cdn
+
+# Secrets
+.env
+
+# Gradio run artifacts
+*.db
+*.sqlite3
+gradio/launches.json
+
+# Tests
+.coverage
+coverage.xml
+test.txt
+
+# Demos
+demo/tmp.zip
+demo/flagged
+demo/files/*.avi
+demo/files/*.mp4
+
+# Etc
+.idea/*
+.DS_Store
+*.bak
+workspace.code-workspace

.gitignore

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+# Python build
+.eggs/
+gradio.egg-info
+dist/
+*.pyc
+__pycache__/
+*.py[cod]
+*$py.class
+build/
+
+# JS build
+gradio/templates/cdn
+gradio/templates/frontend
+
+# Secrets
+.env
+
+# Gradio run artifacts
+*.db
+*.sqlite3
+gradio/launches.json
+flagged/
+gradio_cached_examples/
+
+# Tests
+.coverage
+coverage.xml
+test.txt
+**/snapshots/**/*.png
+
+# Demos
+demo/tmp.zip
+demo/files/*.avi
+demo/files/*.mp4
+demo/all_demos/demos/*
+demo/all_demos/requirements.txt
+demo/*/config.json
+
+# Etc
+.idea/*
+.DS_Store
+*.bak
+workspace.code-workspace
+*.h5
+
+# log files
+.pnpm-debug.log
+
+# Local virtualenv for devs
+.venv*
+
+# FRP
+gradio/frpc_*

CITATION.cff

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+cff-version: 1.2.0
+message: Please cite this project using these metadata.
+title: "Gradio: Hassle-free sharing and testing of ML models in the wild"
+abstract: >-
+  Accessibility is a major challenge of machine learning (ML).
+  Typical ML models are built by specialists and require
+  specialized hardware/software as well as ML experience to
+  validate. This makes it challenging for non-technical
+  collaborators and endpoint users (e.g. physicians) to easily
+  provide feedback on model development and to gain trust in
+  ML. The accessibility challenge also makes collaboration
+  more difficult and limits the ML researcher's exposure to
+  realistic data and scenarios that occur in the wild. To
+  improve accessibility and facilitate collaboration, we
+  developed an open-source Python package, Gradio, which
+  allows researchers to rapidly generate a visual interface
+  for their ML models. Gradio makes accessing any ML model as
+  easy as sharing a URL. Our development of Gradio is informed
+  by interviews with a number of machine learning researchers
+  who participate in interdisciplinary collaborations. Their
+  feedback identified that Gradio should support a variety of
+  interfaces and frameworks, allow for easy sharing of the
+  interface, allow for input manipulation and interactive
+  inference by the domain expert, as well as allow embedding
+  the interface in iPython notebooks. We developed these
+  features and carried out a case study to understand Gradio's
+  usefulness and usability in the setting of a machine
+  learning collaboration between a researcher and a
+  cardiologist.
+authors:
+  - family-names: Abid
+    given-names: Abubakar
+  - family-names: Abdalla
+    given-names: Ali
+  - family-names: Abid
+    given-names: Ali
+  - family-names: Khan
+    given-names: Dawood
+  - family-names: Alfozan
+    given-names: Abdulrahman
+  - family-names: Zou
+    given-names: James
+doi: 10.48550/arXiv.1906.02569
+date-released: 2019-06-06
+url: https://arxiv.org/abs/1906.02569

CONTRIBUTING.md

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+# Contributing to Gradio
+
+Prequisites:
+
+* [Python 3.7+](https://www.python.org/downloads/)
+* [pnpm version 7.x](https://pnpm.io/7.x/installation) (optional for backend-only changes, but needed for any frontend changes)
+
+More than 80 awesome developers have contributed to the `gradio` library, and we'd be thrilled if you would like be the next `gradio` contributor! Start by cloning this repo and installing Gradio locally:
+
+### Install Gradio locally from the `main` branch
+
+* Clone this repo
+* Navigate to the repo folder and run
+
+```bash
+bash scripts/install_gradio.sh
+```
+
+* Build the front end
+
+```
+bash scripts/build_frontend.sh
+```
+
+
+### Install testing requirements
+
+In order to be able to run the Python unit tests, do the following:
+
+* Navigate to the repo folder and install test requirements (note that it is highly recommended to use a virtual environment running **Python 3.9** since the versions are pinned)
+
+```
+bash scripts/install_test_requirements.sh
+```
+* If you have a different Python version and conflicting packages during the installation, please first run:
+
+```
+bash scripts/create_test_requirements.sh
+```
+
+### Extra tidbits
+
+* You can run gradio scripts in reload mode which will watch for changes in the `gradio` folder and reload the app if changes are made.
+```
+gradio app.py
+```
+
+* You can also start a local frontend development server (on port 3000 by default) that responds to any changes in the frontend.
+
+```
+bash scripts/run_frontend.sh
+```
+* To run all of the tests, do:
+
+```
+bash scripts/run_all_tests.sh
+```
+
+
+### Structure of the Repository
+
+It's helpful to know the overall structure of the repository so that you can focus on the part of the source code you'd like to contribute to
+
+* `/gradio`: contains the Python source code for the library
+    * `/gradio/interface.py`: contains the Python source code for the core `Interface` class
+    * `/gradio/blocks.py`: contains the Python source code for the core `Blocks` class
+    * `/gradio/components.py`: contains the Python source code for the `components`, you can add your custom components here.
+* `/ui`: contains the HTML/JS/CSS source code for the library ([start here for frontend changes](/ui/README.md))
+* `/test`: contains Python unit tests for the library
+* `/demo`: contains demos that are used in the documentation, you can find `Gradio` examples over here.
+* `/website`: contains the code for the Gradio website (www.gradio.app). See the README in the `/website` folder for more details
+
+### Continuous Integration and Testing
+
+All PRs must pass the continuous integration tests before merging. To test locally, you can run `python -m unittest` from the repo directory.
+
+## Submitting PRs
+
+All PRs should be against `main`. Direct commits to main are blocked, and PRs require an approving review to merge into main. By convention, the Gradio maintainers will review PRs when:
+
+* An initial review has been requested, and
+* A description of the change (with a link to the GitHub PR) has been added to CHANGELOG.md, and
+* A maintainer (@abidlabs, @aliabid94, @aliabd, @AK391, @dawoodkhan82, @pngwn, @freddyaboulton) is tagged in the PR comments and asked to complete a review
+
+We ask that you make sure initial CI checks are passing before requesting a review. One of the Gradio maintainers will merge the PR when all the checks are passing.
+
+Do not forget the format the backend before pushing.
+```
+bash scripts/format_backend.sh
+```
+```
+bash scripts/format_frontend.sh
+```
+You can run the circleci checks locally as well. 
+```
+bash scripts/run_circleci.sh
+```
+
+*Could these guidelines be clearer? Feel free to open a PR to help us faciltiate open-source contributions!*

LICENSE

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README.md

@@ -1,3 +1,274 @@
----
-license: afl-3.0
----
+<!-- DO NOT EDIT THIS FILE DIRECTLY. INSTEAD EDIT THE `readme_template.md` OR `guides/1)getting_started/1)quickstart.md` TEMPLATES AND THEN RUN `render_readme.py` SCRIPT. -->
+
+<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.
+
+## Quickstart
+
+**Prerequisite**: Gradio requires Python 3.7 or higher, that's all!
+
+### What Does Gradio Do?
+
+One of the *best ways to share* your machine learning model, API, or data science workflow with others is to create an **interactive app** that allows your users or colleagues to try out the demo in their browsers.
+
+Gradio allows you to **build demos and share them, all in Python.** And usually in just a few lines of code! So let's get started.
+
+### Hello, World
+
+To get Gradio running with a simple "Hello, World" example, follow these three steps:
+
+1\. Install Gradio using pip:
+
+```bash
+pip install gradio
+```
+
+2\. Run the code below as a Python script or in a Jupyter Notebook (or [Google Colab](https://colab.research.google.com/drive/18ODkJvyxHutTN0P5APWyGFO_xwNcgHDZ?usp=sharing)):
+
+```python
+import gradio as gr
+
+def greet(name):
+    return "Hello " + name + "!"
+
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo.launch()
+```
+
+
+3\. The demo below will appear automatically within the Jupyter Notebook, or pop in a browser on [http://localhost:7860](http://localhost:7860) if running from a script:
+
+![`hello_world` demo](demo/hello_world/screenshot.gif)
+
+### The `Interface` Class
+
+You'll notice that in order to make the demo, we created a `gradio.Interface`. This `Interface` class can wrap any Python function with a user interface. In the example above, we saw a simple text-based function, but the function could be anything from music generator to a tax calculator to the prediction function of a pretrained machine learning model.
+
+The core `Interface` class is initialized with three required parameters:
+
+- `fn`: the function to wrap a UI around
+- `inputs`: which component(s) to use for the input (e.g. `"text"`, `"image"` or `"audio"`)
+- `outputs`: which component(s) to use for the output (e.g. `"text"`, `"image"` or `"label"`)
+
+Let's take a closer look at these components used to provide input and output.
+
+### Components Attributes
+
+We saw some simple `Textbox` components in the previous examples, but what if you want to change how the UI components look or behave?
+
+Let's say you want to customize the input text field — for example, you wanted it to be larger and have a text placeholder. If we use the actual class for `Textbox` instead of using the string shortcut, you have access to much more customizability through component attributes.
+
+```python
+import gradio as gr
+
+def greet(name):
+    return "Hello " + name + "!"
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=gr.Textbox(lines=2, placeholder="Name Here..."),
+    outputs="text",
+)
+demo.launch()
+```
+
+![`hello_world_2` demo](demo/hello_world_2/screenshot.gif)
+
+### Multiple Input and Output Components
+
+Suppose you had a more complex function, with multiple inputs and outputs. In the example below, we define a function that takes a string, boolean, and number, and returns a string and number. Take a look how you pass a list of input and output components.
+
+```python
+import gradio as gr
+
+def greet(name, is_morning, temperature):
+    salutation = "Good morning" if is_morning else "Good evening"
+    greeting = f"{salutation} {name}. It is {temperature} degrees today"
+    celsius = (temperature - 32) * 5 / 9
+    return greeting, round(celsius, 2)
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=["text", "checkbox", gr.Slider(0, 100)],
+    outputs=["text", "number"],
+)
+demo.launch()
+```
+
+![`hello_world_3` demo](demo/hello_world_3/screenshot.gif)
+
+You simply wrap the components in a list. Each component in the `inputs` list corresponds to one of the parameters of the function, in order. Each component in the `outputs` list corresponds to one of the values returned by the function, again in order.
+
+### An Image Example
+
+Gradio supports many types of components, such as `Image`, `DataFrame`, `Video`, or `Label`. Let's try an image-to-image function to get a feel for these!
+
+```python
+import numpy as np
+import gradio as gr
+
+def sepia(input_img):
+    sepia_filter = np.array([
+        [0.393, 0.769, 0.189], 
+        [0.349, 0.686, 0.168], 
+        [0.272, 0.534, 0.131]
+    ])
+    sepia_img = input_img.dot(sepia_filter.T)
+    sepia_img /= sepia_img.max()
+    return sepia_img
+
+demo = gr.Interface(sepia, gr.Image(shape=(200, 200)), "image")
+demo.launch()
+```
+
+![`sepia_filter` demo](demo/sepia_filter/screenshot.gif)
+
+When using the `Image` component as input, your function will receive a NumPy array with the shape `(width, height, 3)`, where the last dimension represents the RGB values. We'll return an image as well in the form of a NumPy array.
+
+You can also set the datatype used by the component with the `type=` keyword argument. For example, if you wanted your function to take a file path to an image instead of a NumPy array, the input `Image` component could be written as:
+
+```python
+gr.Image(type="filepath", shape=...)
+```
+
+Also note that our input `Image` component comes with an edit button 🖉, which allows for cropping and zooming into images. Manipulating images in this way can help reveal biases or hidden flaws in a machine learning model!
+
+You can read more about the many components and how to use them in the [Gradio docs](https://gradio.app/docs).
+
+### Blocks: More Flexibility and Control
+
+Gradio offers two classes to build apps:
+
+1\. **Interface**, that provides a high-level abstraction for creating demos that we've been discussing so far.
+
+2\. **Blocks**, a low-level API for designing web apps with more flexible layouts and data flows. Blocks allows you to do things like feature multiple data flows and demos, control where components appear on the page, handle complex data flows (e.g. outputs can serve as inputs to other functions), and update properties/visibility of components based on user interaction — still all in Python. If this customizability is what you need, try `Blocks` instead!
+
+### Hello, Blocks
+
+Let's take a look at a simple example. Note how the API here differs from `Interface`.
+
+```python
+import gradio as gr
+
+def greet(name):
+    return "Hello " + name + "!"
+
+with gr.Blocks() as demo:
+    name = gr.Textbox(label="Name")
+    output = gr.Textbox(label="Output Box")
+    greet_btn = gr.Button("Greet")
+    greet_btn.click(fn=greet, inputs=name, outputs=output)
+
+demo.launch()
+```
+
+![`hello_blocks` demo](demo/hello_blocks/screenshot.gif)
+
+Things to note:
+
+- `Blocks` are made with a `with` clause, and any component created inside this clause is automatically added to the app.
+- Components appear vertically in the app in the order they are created. (Later we will cover customizing layouts!)
+- A `Button` was created, and then a `click` event-listener was added to this button. The API for this should look familiar! Like an `Interface`, the `click` method takes a Python function, input components, and output components.
+
+### More Complexity
+
+Here's an app to give you a taste of what's possible with `Blocks`:
+
+```python
+import numpy as np
+import gradio as gr
+
+def flip_text(x):
+    return x[::-1]
+
+def flip_image(x):
+    return np.fliplr(x)
+
+with gr.Blocks() as demo:
+    gr.Markdown("Flip text or image files using this demo.")
+    with gr.Tabs():
+        with gr.TabItem("Flip Text"):
+            text_input = gr.Textbox()
+            text_output = gr.Textbox()
+            text_button = gr.Button("Flip")
+        with gr.TabItem("Flip Image"):
+            with gr.Row():
+                image_input = gr.Image()
+                image_output = gr.Image()
+            image_button = gr.Button("Flip")
+    
+    text_button.click(flip_text, inputs=text_input, outputs=text_output)
+    image_button.click(flip_image, inputs=image_input, outputs=image_output)
+    
+demo.launch()
+```
+
+![`blocks_flipper` demo](demo/blocks_flipper/screenshot.gif)
+
+A lot more going on here! We'll cover how to create complex `Blocks` apps like this in the [building with blocks](https://github.com/gradio-app/gradio/tree/main/guides/3\)building_with_blocks) section for you.
+
+Congrats, you're now familiar with the basics of Gradio! 🥳 Go to our [next guide](https://gradio.app/key_features) to learn more about the key features of Gradio.
+
+
+## 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},
+}
+```

SECURITY.md

@@ -0,0 +1,5 @@
+# Security Policy
+
+## Reporting a Vulnerability
+
+If you discover a security vulnerability, we would be very grateful if you could email us at team@gradio.app. This is the preferred approach instead of opening a public issue. We take all vulnerability reports seriously, and will work to patch the vulnerability immediately. Whenever possible, we will credit the person or people who report the security vulnerabilities after it has been patched.

codecov.yml

@@ -0,0 +1,17 @@
+coverage:
+  range: 0..100
+  round: down
+  precision: 2
+  status:
+    project:
+      default: false  # disable the default status that measures entire project
+      source:
+        paths:
+          - "gradio/"
+        target: 70%
+        threshold: 0.1
+    patch: off
+  
+comment: false
+codecov:
+  require_ci_to_pass: yes

pyproject.toml

@@ -0,0 +1,60 @@
+[build-system]
+requires = ["hatchling", "hatch-requirements-txt", "hatch-fancy-pypi-readme>=22.5.0"]
+build-backend = "hatchling.build"
+
+[project]
+name = "gradio"
+dynamic = ["version", "dependencies", "readme"]
+description = "Python library for easily interacting with trained machine learning models"
+license = "Apache-2.0"
+requires-python = ">=3.7"
+authors = [
+  { name = "Abubakar Abid", email = "team@gradio.app" },
+  { name = "Ali Abid", email = "team@gradio.app" },
+  { name = "Ali Abdalla", email = "team@gradio.app" },
+  { name = "Dawood Khan", email = "team@gradio.app" },
+  { name = "Ahsen Khaliq", email = "team@gradio.app" },
+  { name = "Pete Allen", email = "team@gradio.app" },
+  { name = "Ömer Faruk Özdemir", email = "team@gradio.app" },
+]
+keywords = ["machine learning", "reproducibility", "visualization"]
+
+[project.scripts]
+gradio = "gradio.reload:run_in_reload_mode"
+
+[project.urls]
+Homepage = "https://github.com/gradio-app/gradio"
+
+[tool.hatch.version]
+path = "gradio/version.txt"
+pattern = "(?P<version>.+)"
+
+[tool.hatch.metadata.hooks.requirements_txt]
+filename = "requirements.txt"
+
+[tool.hatch.metadata.hooks.fancy-pypi-readme]
+content-type = "text/markdown"
+fragments = [
+  { path = "README.md" },
+]
+
+[[tool.hatch.metadata.hooks.fancy-pypi-readme.substitutions]]
+pattern = "(website/homepage|readme_files)/"
+replacement = 'https://raw.githubusercontent.com/gradio-app/gradio/main/\g<1>/'
+
+[[tool.hatch.metadata.hooks.fancy-pypi-readme.substitutions]]
+pattern = 'demo/([\S]*.gif)'
+replacement = 'https://raw.githubusercontent.com/gradio-app/gradio/main/demo/\g<1>'
+
+[tool.hatch.build]
+artifacts = [
+  "/gradio/templates",
+]
+
+[tool.hatch.build.targets.sdist]
+include = [
+  "/gradio",
+  "/test",
+  "/README.md",
+  "/requirements.txt",
+]

readme_template.md

@@ -0,0 +1,67 @@
+<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},
+}
+```

render_readme.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python
+
+import re
+from pathlib import Path
+
+README_TEMPLATE_FILEPATH = "readme_template.md"
+GETTING_STARTED_TEMPLATE_FILEPATH = "guides/1)getting_started/1)quickstart.md"
+
+readme_template = Path(README_TEMPLATE_FILEPATH).read_text()
+getting_started_template = Path(GETTING_STARTED_TEMPLATE_FILEPATH).read_text()
+
+# Extract all the code and demo tags from the getting started template
+code_tags = re.findall(r"\$code_([^\s]+)", getting_started_template)
+demo_tags = re.findall(r"\$demo_([^\s]+)", getting_started_template)
+codes = {}
+demos = {}
+
+for src in code_tags:
+    context = Path(f"demo/{src}/run.py").read_text()
+    # Replace the condition to run the demo directly with actual launch code
+    context = re.sub(r"if __name__(.*[\n$]*)*", "demo.launch()", context)
+    codes[src] = f"```python\n{context}\n```\n"  # Convert to Markdown code block
+
+for src in demo_tags:
+    demos[src] = f"![`{src}` demo](demo/{src}/screenshot.gif)"
+
+# Replace the headers in the getting started template with a smaller header (e.g. H3 instead of H2) to
+# make the README more readable and less cluttered.
+getting_started_template = re.sub(r"^(#+)", r"#\1", getting_started_template, flags=re.MULTILINE)
+readme_template = readme_template.replace("$getting_started", getting_started_template)
+
+# Now put the codes and the screenshots in the README template
+readme_template = re.sub(r"\$code_([^\s]+)", lambda x: codes[x.group(1)], readme_template)
+readme_template = re.sub(r"\$demo_([^\s]+)", lambda x: demos[x.group(1)], readme_template)
+
+# Save the README template to the actual README.md file (with a note about the editing)
+EDITING_NOTE = ("<!-- DO NOT EDIT THIS FILE DIRECTLY. INSTEAD EDIT THE `readme_template.md` OR "
+                "`guides/1)getting_started/1)quickstart.md` TEMPLATES AND THEN RUN `render_readme.py` SCRIPT. -->")
+Path("README.md").write_text(f"{EDITING_NOTE}\n\n{readme_template}")

requirements.txt

@@ -0,0 +1,22 @@
+aiohttp
+altair
+fastapi
+ffmpy
+markdown-it-py[linkify,plugins]
+markupsafe
+matplotlib
+numpy
+orjson
+pandas
+pillow
+pycryptodome
+python-multipart
+pydub
+pyyaml
+requests
+uvicorn
+Jinja2
+fsspec
+httpx
+pydantic
+websockets>=10.0

style.md

@@ -0,0 +1,160 @@
+# component-styles
+
+## Textbox
+
+| name        | type                                 | description                    |
+| ----------- | ------------------------------------ | ------------------------------ |
+| `rounded`   | `bool` or `(bool, bool, bool, bool)` | corners of text input          |
+| `border`    | `bool` or `(bool, bool, bool, bool)` | borders of text input          |
+| `container` | `bool`                               | show or hide the container box |
+
+## Number
+
+| name        | type                                 | description                    |
+| ----------- | ------------------------------------ | ------------------------------ |
+| `rounded`   | `bool` or `(bool, bool, bool, bool)` | corners of text input          |
+| `border`    | `bool` or `(bool, bool, bool, bool)` | borders of text input          |
+| `container` | `bool`                               | show or hide the container box |
+
+## Slider
+
+| name        | type   | description                    |
+| ----------- | ------ | ------------------------------ |
+| `container` | `bool` | show or hide the container box |
+
+## Checkbox
+
+| name        | type                                 | description                    |
+| ----------- | ------------------------------------ | ------------------------------ |
+| `rounded`   | `bool` or `(bool, bool, bool, bool)` | corners of checkbox            |
+| `border`    | `bool` or `(bool, bool, bool, bool)` | borders of checkbox            |
+| `container` | `bool`                               | show or hide the container box |
+
+## Checkbox Group
+
+| name             | type                                 | description                               |
+| ---------------- | ------------------------------------ | ----------------------------------------- |
+| `rounded`        | `bool` or `(bool, bool, bool, bool)` | corners of checkboxes                     |
+| `container`      | `bool`                               | show or hide the container box            |
+| `item_container` | `bool`                               | show or hide the checkbox container boxes |
+
+## Radio
+
+| name             | type   | description                            |
+| ---------------- | ------ | -------------------------------------- |
+| `container`      | `bool` | show or hide the container box         |
+| `item_container` | `bool` | show or hide the radio container boxes |
+
+## Dropdown
+
+| name        | type                                 | description                    |
+| ----------- | ------------------------------------ | ------------------------------ |
+| `rounded`   | `bool` or `(bool, bool, bool, bool)` | corners of input               |
+| `border`    | `bool` or `(bool, bool, bool, bool)` | borders of input               |
+| `container` | `bool`                               | show or hide the container box |
+
+## Image
+
+| name      | type                                 | description         |
+| --------- | ------------------------------------ | ------------------- |
+| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of main box |
+
+## Video
+
+| name      | type                                 | description         |
+| --------- | ------------------------------------ | ------------------- |
+| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of main box |
+
+## Audio
+
+| name      | type                                 | description         |
+| --------- | ------------------------------------ | ------------------- |
+| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of main box |
+
+## File
+
+| name      | type                                 | description         |
+| --------- | ------------------------------------ | ------------------- |
+| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of main box |
+
+## Dataframe
+
+| name      | type                                 | description         |
+| --------- | ------------------------------------ | ------------------- |
+| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of main box |
+
+## Timeseries
+
+| name      | type                                 | description         |
+| --------- | ------------------------------------ | ------------------- |
+| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of main box |
+
+## Label
+
+| name        | type   | description                    |
+| ----------- | ------ | ------------------------------ |
+| `container` | `bool` | show or hide the container box |
+
+## HighlightedText
+
+| name        | type                                 | description                    |
+| ----------- | ------------------------------------ | ------------------------------ |
+| `rounded`   | `bool` or `(bool, bool, bool, bool)` | corners of labels              |
+| `color_map` | `Dict[str, str]`                     | color map of labels and colors |
+| `container` | `bool`                               | show or hide the container box |
+
+## JSON
+
+| name        | type   | description                    |
+| ----------- | ------ | ------------------------------ |
+| `container` | `bool` | show or hide the container box |
+
+## HTML
+
+Nothing
+
+## Gallery
+
+| name        | type                                      | description                         |
+| ----------- | ----------------------------------------- | ----------------------------------- |
+| `rounded`   | `bool` or `(bool, bool, bool, bool)`      | corners of images                   |
+| `grid`      | `int` or `(int, int, int, int, int, int)` | grid for images                     |
+| `height`    | `"auto"`                                  | height of gallery (auto or default) |
+| `container` | `bool`                                    | show or hide the container box      |
+
+## Chatbot
+
+| name        | type                                 | description                                      |
+| ----------- | ------------------------------------ | ------------------------------------------------ |
+| `rounded`   | `bool` or `(bool, bool, bool, bool)` | corners of chat bubbles                          |
+| `color_map` | `Dict[str, str]`                     | color map of user and bot color for chat bubbles |
+
+## Model3D
+
+| name      | type                                 | description         |
+| --------- | ------------------------------------ | ------------------- |
+| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of main box |
+
+## Plot
+
+Nothing (yet)
+
+## Markdown
+
+Nothing
+
+## Button
+
+| name         | type                                 | description                             |
+| ------------ | ------------------------------------ | --------------------------------------- |
+| `rounded`    | `bool` or `(bool, bool, bool, bool)` | corners of button                       |
+| `border`     | `bool` or `(bool, bool, bool, bool)` | borders of button                       |
+| `full_width` | `bool`                               | whether button expand to fill container |
+
+## Dataset
+
+Nothing
+
+## Variable
+
+Nothing