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ExploreGradio is a popular Python library for creating interactive machine learning apps. Traditionally, Gradio applications have relied on server-side infrastructure to run, which can be a hurdle for developers who need to host their applications.
Enter Gradio-lite (@gradio/lite
): a library that leverages Pyodide to bring Gradio directly to your browser. In this blog post, we’ll explore what @gradio/lite
is, go over example code, and discuss the benefits it offers for running Gradio applications.
@gradio/lite
?@gradio/lite
is a JavaScript library that enables you to run Gradio applications directly within your web browser. It achieves this by utilizing Pyodide, a Python runtime for WebAssembly, which allows Python code to be executed in the browser environment. With @gradio/lite
, you can write regular Python code for your Gradio applications, and they will run seamlessly in the browser without the need for server-side infrastructure.
Let’s build a “Hello World” Gradio app in @gradio/lite
Start by creating a new HTML file, if you don’t have one already. Importing the JavaScript and CSS corresponding to the @gradio/lite
package by using the following code:
<html>
<head>
<script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
</head>
</html>
Note that you should generally use the latest version of @gradio/lite
that is available. You can see the versions available here.
<gradio-lite>
tagsSomewhere in the body of your HTML page (wherever you’d like the Gradio app to be rendered), create opening and closing <gradio-lite>
tags.
<html>
<head>
<script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
</head>
<body>
<gradio-lite>
</gradio-lite>
</body>
</html>
Note: you can add the theme
attribute to the <gradio-lite>
tag to force the theme to be dark or light (by default, it respects the system theme). E.g.
<gradio-lite theme="dark">
...
</gradio-lite>
Now, write your Gradio app as you would normally, in Python! Keep in mind that since this is Python, whitespace and indentations matter.
<html>
<head>
<script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
</head>
<body>
<gradio-lite>
import gradio as gr
def greet(name):
return "Hello, " + name + "!"
gr.Interface(greet, "textbox", "textbox").launch()
</gradio-lite>
</body>
</html>
And that’s it! You should now be able to open your HTML page in the browser and see the Gradio app rendered! Note that it may take a little while for the Gradio app to load initially since Pyodide can take a while to install in your browser.
Note on debugging: to see any errors in your Gradio-lite application, open the inspector in your web browser. All errors (including Python errors) will be printed there.
What if you want to create a Gradio app that spans multiple files? Or that has custom Python requirements? Both are possible with @gradio/lite
!
Adding multiple files within a @gradio/lite
app is very straightrward: use the <gradio-file>
tag. You can have as many <gradio-file>
tags as you want, but each one needs to have a name
attribute and the entry point to your Gradio app should have the entrypoint
attribute.
Here’s an example:
<gradio-lite>
<gradio-file name="app.py" entrypoint>
import gradio as gr
from utils import add
demo = gr.Interface(fn=add, inputs=["number", "number"], outputs="number")
demo.launch()
</gradio-file>
<gradio-file name="utils.py" >
def add(a, b):
return a + b
</gradio-file>
</gradio-lite>
If your Gradio app has additional requirements, it is usually possible to install them in the browser using micropip. We’ve created a wrapper to make this paticularly convenient: simply list your requirements in the same syntax as a requirements.txt
and enclose them with <gradio-requirements>
tags.
Here, we install transformers_js_py
to run a text classification model directly in the browser!
<gradio-lite>
<gradio-requirements>
transformers_js_py
</gradio-requirements>
<gradio-file name="app.py" entrypoint>
from transformers_js import import_transformers_js
import gradio as gr
transformers = await import_transformers_js()
pipeline = transformers.pipeline
pipe = await pipeline('sentiment-analysis')
async def classify(text):
return await pipe(text)
demo = gr.Interface(classify, "textbox", "json")
demo.launch()
</gradio-file>
</gradio-lite>
Try it out: You can see this example running in this Hugging Face Static Space, which lets you host static (serverless) web applications for free. Visit the page and you’ll be able to run a machine learning model without internet access!
By default, Gradio-Lite executes Python code in a Web Worker with Pyodide runtime, and each Gradio-Lite app has its own worker. It has some benefits such as environment isolation.
However, when there are many Gradio-Lite apps in the same page, it may cause performance issues such as high memory usage because each app has its own worker and Pyodide runtime.
In such cases, you can use the SharedWorker mode to share a single Pyodide runtime in a SharedWorker among multiple Gradio-Lite apps. To enable the SharedWorker mode, set the shared-worker
attribute to the <gradio-lite>
tag.
<!-- These two Gradio-Lite apps share a single worker -->
<gradio-lite shared-worker>
import gradio as gr
# ...
</gradio-lite>
<gradio-lite shared-worker>
import gradio as gr
# ...
</gradio-lite>
When using the SharedWorker mode, you should be aware of the following points:
If you’d like to see the code side-by-side with the demo just pass in the playground
attribute to the gradio-lite element. This will create an interactive playground that allows you to change the code and update the demo! If you’re using playground, you can also set layout to either ‘vertical’ or ‘horizontal’ which will determine if the code editor and preview are side-by-side or on top of each other (by default it’s reposnsive with the width of the page).
<gradio-lite playground layout="horizontal">
import gradio as gr
gr.Interface(fn=lambda x: x,
inputs=gr.Textbox(),
outputs=gr.Textbox()
).launch()
</gradio-lite>
@gradio/lite
The primary advantage of @gradio/lite is that it eliminates the need for server infrastructure. This simplifies deployment, reduces server-related costs, and makes it easier to share your Gradio applications with others.
By running in the browser, @gradio/lite offers low-latency interactions for users. There’s no need for data to travel to and from a server, resulting in faster responses and a smoother user experience.
Since all processing occurs within the user’s browser, @gradio/lite
enhances privacy and security. User data remains on their device, providing peace of mind regarding data handling.
Currently, the biggest limitation in using @gradio/lite
is that your Gradio apps will generally take more time (usually 5-15 seconds) to load initially in the browser. This is because the browser needs to load the Pyodide runtime before it can render Python code.
Not every Python package is supported by Pyodide. While gradio
and many other popular packages (including numpy
, scikit-learn
, and transformers-js
) can be installed in Pyodide, if your app has many dependencies, its worth checking whether whether the dependencies are included in Pyodide, or can be installed with micropip
.
You can immediately try out @gradio/lite
by copying and pasting this code in a local index.html
file and opening it with your browser:
<html>
<head>
<script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
</head>
<body>
<gradio-lite>
import gradio as gr
def greet(name):
return "Hello, " + name + "!"
gr.Interface(greet, "textbox", "textbox").launch()
</gradio-lite>
</body>
</html>
We’ve also created a playground on the Gradio website that allows you to interactively edit code and see the results immediately!
Playground: https://www.gradio.app/playground