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Often times, you may want to bind multiple triggers to the same function. For example, you may want to allow a user to click a submit button, or press enter to submit a form. You can do this using the `gr.on` method and passing a list of triggers to the `trigger`.
$code_on_listener_basic
$demo_on_listener_basic
You can use decorator syntax as well:
$code_on_listener_decorator
You can use `gr.on` to create "live" events by binding to the `change` event of components that implement it. If you do not specify any triggers, the function will automatically bind to all `change` event of all input components that include a `change` event (for example `gr.Textbox` has a `change` event whereas `gr.Button` does not).
$code_on_listener_live
$demo_on_listener_live
You can follow `gr.on` with `.then`, just like any regular event listener. This handy method should save you from having to write a lot of repetitive code!
|
Binding Multiple Triggers to a Function
|
https://gradio.app/guides/blocks-and-event-listeners
|
Building With Blocks - Blocks And Event Listeners Guide
|
If you want to set a Component's value to always be a function of the value of other Components, you can use the following shorthand:
```python
with gr.Blocks() as demo:
num1 = gr.Number()
num2 = gr.Number()
product = gr.Number(lambda a, b: a * b, inputs=[num1, num2])
```
This functionally the same as:
```python
with gr.Blocks() as demo:
num1 = gr.Number()
num2 = gr.Number()
product = gr.Number()
gr.on(
[num1.change, num2.change, demo.load],
lambda a, b: a * b,
inputs=[num1, num2],
outputs=product
)
```
|
Binding a Component Value Directly to a Function of Other Components
|
https://gradio.app/guides/blocks-and-event-listeners
|
Building With Blocks - Blocks And Event Listeners Guide
|
Gradio themes are the easiest way to customize the look and feel of your app. You can choose from a variety of themes, or create your own. To do so, pass the `theme=` kwarg to the `Blocks` constructor. For example:
```python
with gr.Blocks(theme=gr.themes.Glass()):
...
```
Gradio comes with a set of prebuilt themes which you can load from `gr.themes.*`. You can extend these themes or create your own themes from scratch - see the [Theming guide](/guides/theming-guide) for more details.
For additional styling ability, you can pass any CSS to your app as a string using the `css=` kwarg. You can also pass a pathlib.Path to a css file or a list of such paths to the `css_paths=` kwarg.
**Warning**: The use of query selectors in custom JS and CSS is _not_ guaranteed to work across Gradio versions that bind to Gradio's own HTML elements as the Gradio HTML DOM may change. We recommend using query selectors sparingly.
The base class for the Gradio app is `gradio-container`, so here's an example that changes the background color of the Gradio app:
```python
with gr.Blocks(css=".gradio-container {background-color: red}") as demo:
...
```
If you'd like to reference external files in your css, preface the file path (which can be a relative or absolute path) with `"/gradio_api/file="`, for example:
```python
with gr.Blocks(css=".gradio-container {background: url('/gradio_api/file=clouds.jpg')}") as demo:
...
```
Note: By default, most files in the host machine are not accessible to users running the Gradio app. As a result, you should make sure that any referenced files (such as `clouds.jpg` here) are either URLs or [allowed paths, as described here](/main/guides/file-access).
|
Adding custom CSS to your demo
|
https://gradio.app/guides/custom-CSS-and-JS
|
Building With Blocks - Custom Css And Js Guide
|
You can `elem_id` to add an HTML element `id` to any component, and `elem_classes` to add a class or list of classes. This will allow you to select elements more easily with CSS. This approach is also more likely to be stable across Gradio versions as built-in class names or ids may change (however, as mentioned in the warning above, we cannot guarantee complete compatibility between Gradio versions if you use custom CSS as the DOM elements may themselves change).
```python
css = """
warning {background-color: FFCCCB}
.feedback textarea {font-size: 24px !important}
"""
with gr.Blocks(css=css) as demo:
box1 = gr.Textbox(value="Good Job", elem_classes="feedback")
box2 = gr.Textbox(value="Failure", elem_id="warning", elem_classes="feedback")
```
The CSS `warning` ruleset will only target the second Textbox, while the `.feedback` ruleset will target both. Note that when targeting classes, you might need to put the `!important` selector to override the default Gradio styles.
|
The `elem_id` and `elem_classes` Arguments
|
https://gradio.app/guides/custom-CSS-and-JS
|
Building With Blocks - Custom Css And Js Guide
|
There are 3 ways to add javascript code to your Gradio demo:
1. You can add JavaScript code as a string to the `js` parameter of the `Blocks` or `Interface` initializer. This will run the JavaScript code when the demo is first loaded.
Below is an example of adding custom js to show an animated welcome message when the demo first loads.
$code_blocks_js_load
$demo_blocks_js_load
2. When using `Blocks` and event listeners, events have a `js` argument that can take a JavaScript function as a string and treat it just like a Python event listener function. You can pass both a JavaScript function and a Python function (in which case the JavaScript function is run first) or only Javascript (and set the Python `fn` to `None`). Take a look at the code below:
$code_blocks_js_methods
$demo_blocks_js_methods
3. Lastly, you can add JavaScript code to the `head` param of the `Blocks` initializer. This will add the code to the head of the HTML document. For example, you can add Google Analytics to your demo like so:
```python
head = f"""
<script async src="https://www.googletagmanager.com/gtag/js?id={google_analytics_tracking_id}"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){{dataLayer.push(arguments);}}
gtag('js', new Date());
gtag('config', '{google_analytics_tracking_id}');
</script>
"""
with gr.Blocks(head=head) as demo:
gr.HTML("<h1>My App</h1>")
demo.launch()
```
The `head` parameter accepts any HTML tags you would normally insert into the `<head>` of a page. For example, you can also include `<meta>` tags to `head` in order to update the social sharing preview for your Gradio app like this:
```py
import gradio as gr
custom_head = """
<!-- HTML Meta Tags -->
<title>Sample App</title>
<meta name="description" content="An open-source web application showcasing various features and capabilities.">
<!-- Facebook Meta Tags -->
<meta property="og:url" content="https://example.com">
<meta property="og:type" content="webs
|
Adding custom JavaScript to your demo
|
https://gradio.app/guides/custom-CSS-and-JS
|
Building With Blocks - Custom Css And Js Guide
|
n open-source web application showcasing various features and capabilities.">
<!-- Facebook Meta Tags -->
<meta property="og:url" content="https://example.com">
<meta property="og:type" content="website">
<meta property="og:title" content="Sample App">
<meta property="og:description" content="An open-source web application showcasing various features and capabilities.">
<meta property="og:image" content="https://cdn.britannica.com/98/152298-050-8E45510A/Cheetah.jpg">
<!-- Twitter Meta Tags -->
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:creator" content="@example_user">
<meta name="twitter:title" content="Sample App">
<meta name="twitter:description" content="An open-source web application showcasing various features and capabilities.">
<meta name="twitter:image" content="https://cdn.britannica.com/98/152298-050-8E45510A/Cheetah.jpg">
<meta property="twitter:domain" content="example.com">
<meta property="twitter:url" content="https://example.com">
"""
with gr.Blocks(title="My App", head=custom_head) as demo:
gr.HTML("<h1>My App</h1>")
demo.launch()
```
Note that injecting custom JS can affect browser behavior and accessibility (e.g. keyboard shortcuts may be lead to unexpected behavior if your Gradio app is embedded in another webpage). You should test your interface across different browsers and be mindful of how scripts may interact with browser defaults. Here's an example where pressing `Shift + s` triggers the `click` event of a specific `Button` component if the browser focus is _not_ on an input component (e.g. `Textbox` component):
```python
import gradio as gr
shortcut_js = """
<script>
function shortcuts(e) {
var event = document.all ? window.event : e;
switch (e.target.tagName.toLowerCase()) {
case "input":
case "textarea":
break;
default:
if (e.key.toLowerCase() == "s" && e.shiftKey) {
document.getElementById("my_btn").click();
}
}
}
doc
|
Adding custom JavaScript to your demo
|
https://gradio.app/guides/custom-CSS-and-JS
|
Building With Blocks - Custom Css And Js Guide
|
e "input":
case "textarea":
break;
default:
if (e.key.toLowerCase() == "s" && e.shiftKey) {
document.getElementById("my_btn").click();
}
}
}
document.addEventListener('keypress', shortcuts, false);
</script>
"""
with gr.Blocks(head=shortcut_js) as demo:
action_button = gr.Button(value="Name", elem_id="my_btn")
textbox = gr.Textbox()
action_button.click(lambda : "button pressed", None, textbox)
demo.launch()
```
|
Adding custom JavaScript to your demo
|
https://gradio.app/guides/custom-CSS-and-JS
|
Building With Blocks - Custom Css And Js Guide
|
In the example below, we will create a variable number of Textboxes. When the user edits the input Textbox, we create a Textbox for each letter in the input. Try it out below:
$code_render_split_simple
$demo_render_split_simple
See how we can now create a variable number of Textboxes using our custom logic - in this case, a simple `for` loop. The `@gr.render` decorator enables this with the following steps:
1. Create a function and attach the @gr.render decorator to it.
2. Add the input components to the `inputs=` argument of @gr.render, and create a corresponding argument in your function for each component. This function will automatically re-run on any change to a component.
3. Add all components inside the function that you want to render based on the inputs.
Now whenever the inputs change, the function re-runs, and replaces the components created from the previous function run with the latest run. Pretty straightforward! Let's add a little more complexity to this app:
$code_render_split
$demo_render_split
By default, `@gr.render` re-runs are triggered by the `.load` listener to the app and the `.change` listener to any input component provided. We can override this by explicitly setting the triggers in the decorator, as we have in this app to only trigger on `input_text.submit` instead.
If you are setting custom triggers, and you also want an automatic render at the start of the app, make sure to add `demo.load` to your list of triggers.
|
Dynamic Number of Components
|
https://gradio.app/guides/dynamic-apps-with-render-decorator
|
Building With Blocks - Dynamic Apps With Render Decorator Guide
|
If you're creating components, you probably want to attach event listeners to them as well. Let's take a look at an example that takes in a variable number of Textbox as input, and merges all the text into a single box.
$code_render_merge_simple
$demo_render_merge_simple
Let's take a look at what's happening here:
1. The state variable `text_count` is keeping track of the number of Textboxes to create. By clicking on the Add button, we increase `text_count` which triggers the render decorator.
2. Note that in every single Textbox we create in the render function, we explicitly set a `key=` argument. This key allows us to preserve the value of this Component between re-renders. If you type in a value in a textbox, and then click the Add button, all the Textboxes re-render, but their values aren't cleared because the `key=` maintains the the value of a Component across a render.
3. We've stored the Textboxes created in a list, and provide this list as input to the merge button event listener. Note that **all event listeners that use Components created inside a render function must also be defined inside that render function**. The event listener can still reference Components outside the render function, as we do here by referencing `merge_btn` and `output` which are both defined outside the render function.
Just as with Components, whenever a function re-renders, the event listeners created from the previous render are cleared and the new event listeners from the latest run are attached.
This allows us to create highly customizable and complex interactions!
|
Dynamic Event Listeners
|
https://gradio.app/guides/dynamic-apps-with-render-decorator
|
Building With Blocks - Dynamic Apps With Render Decorator Guide
|
The `key=` argument is used to let Gradio know that the same component is being generated when your render function re-runs. This does two things:
1. The same element in the browser is re-used from the previous render for this Component. This gives browser performance gains - as there's no need to destroy and rebuild a component on a render - and preserves any browser attributes that the Component may have had. If your Component is nested within layout items like `gr.Row`, make sure they are keyed as well because the keys of the parents must also match.
2. Properties that may be changed by the user or by other event listeners are preserved. By default, only the "value" of Component is preserved, but you can specify any list of properties to preserve using the `preserved_by_key=` kwarg.
See the example below:
$code_render_preserve_key
$demo_render_preserve_key
You'll see in this example, when you change the `number_of_boxes` slider, there's a new re-render to update the number of box rows. If you click the "Change Label" buttons, they change the `label` and `info` properties of the corresponding textbox. You can also enter text in any textbox to change its value. If you change number of boxes after this, the re-renders "reset" the `info`, but the `label` and any entered `value` is still preserved.
Note you can also key any event listener, e.g. `button.click(key=...)` if the same listener is being recreated with the same inputs and outputs across renders. This gives performance benefits, and also prevents errors from occurring if an event was triggered in a previous render, then a re-render occurs, and then the previous event finishes processing. By keying your listener, Gradio knows where to send the data properly.
|
Closer Look at `keys=` parameter
|
https://gradio.app/guides/dynamic-apps-with-render-decorator
|
Building With Blocks - Dynamic Apps With Render Decorator Guide
|
Let's look at two examples that use all the features above. First, try out the to-do list app below:
$code_todo_list
$demo_todo_list
Note that almost the entire app is inside a single `gr.render` that reacts to the tasks `gr.State` variable. This variable is a nested list, which presents some complexity. If you design a `gr.render` to react to a list or dict structure, ensure you do the following:
1. Any event listener that modifies a state variable in a manner that should trigger a re-render must set the state variable as an output. This lets Gradio know to check if the variable has changed behind the scenes.
2. In a `gr.render`, if a variable in a loop is used inside an event listener function, that variable should be "frozen" via setting it to itself as a default argument in the function header. See how we have `task=task` in both `mark_done` and `delete`. This freezes the variable to its "loop-time" value.
Let's take a look at one last example that uses everything we learned. Below is an audio mixer. Provide multiple audio tracks and mix them together.
$code_audio_mixer
$demo_audio_mixer
Two things to note in this app:
1. Here we provide `key=` to all the components! We need to do this so that if we add another track after setting the values for an existing track, our input values to the existing track do not get reset on re-render.
2. When there are lots of components of different types and arbitrary counts passed to an event listener, it is easier to use the set and dictionary notation for inputs rather than list notation. Above, we make one large set of all the input `gr.Audio` and `gr.Slider` components when we pass the inputs to the `merge` function. In the function body we query the component values as a dict.
The `gr.render` expands gradio capabilities extensively - see what you can make out of it!
|
Putting it Together
|
https://gradio.app/guides/dynamic-apps-with-render-decorator
|
Building With Blocks - Dynamic Apps With Render Decorator Guide
|
**API endpoint names**
When you create a Gradio application, the API endpoint names are automatically generated based on the function names. You can change this by using the `api_name` parameter in `gr.Interface` or `gr.ChatInterface`. If you are using Gradio `Blocks`, you can name each event listener, like this:
```python
btn.click(add, [num1, num2], output, api_name="addition")
```
**Hiding API endpoints**
When building a complex Gradio app, you might want to hide certain API endpoints from appearing on the view API page, e.g. if they correspond to functions that simply update the UI. You can set the `show_api` parameter to `False` in any `Blocks` event listener to achieve this, e.g.
```python
btn.click(add, [num1, num2], output, show_api=False)
```
**Disabling API endpoints**
Hiding the API endpoint doesn't disable it. A user can still programmatically call the API endpoint if they know the name. If you want to disable an API endpoint altogether, set `api_name=False`, e.g.
```python
btn.click(add, [num1, num2], output, api_name=False)
```
Note: setting an `api_name=False` also means that downstream apps will not be able to load your Gradio app using `gr.load()` as this function uses the Gradio API under the hood.
**Adding API endpoints**
You can also add new API routes to your Gradio application that do not correspond to events in your UI.
For example, in this Gradio application, we add a new route that adds numbers and slices a list:
```py
import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
input = gr.Textbox()
button = gr.Button("Submit")
output = gr.Textbox()
def fn(a: int, b: int, c: list[str]) -> tuple[int, str]:
return a + b, c[a:b]
gr.api(fn, api_name="add_and_slice")
_, url, _ = demo.launch()
```
This will create a new route `/add_and_slice` which will show up in the "view API" page. It can be programmatically called by the Python or JS Clients (discussed below) like this:
```py
from grad
|
Configuring the API Page
|
https://gradio.app/guides/view-api-page
|
Additional Features - View Api Page Guide
|
``
This will create a new route `/add_and_slice` which will show up in the "view API" page. It can be programmatically called by the Python or JS Clients (discussed below) like this:
```py
from gradio_client import Client
client = Client(url)
result = client.predict(
a=3,
b=5,
c=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
api_name="/add_and_slice"
)
print(result)
```
|
Configuring the API Page
|
https://gradio.app/guides/view-api-page
|
Additional Features - View Api Page Guide
|
This API page not only lists all of the endpoints that can be used to query the Gradio app, but also shows the usage of both [the Gradio Python client](https://gradio.app/guides/getting-started-with-the-python-client/), and [the Gradio JavaScript client](https://gradio.app/guides/getting-started-with-the-js-client/).
For each endpoint, Gradio automatically generates a complete code snippet with the parameters and their types, as well as example inputs, allowing you to immediately test an endpoint. Here's an example showing an image file input and `str` output:
|
The Clients
|
https://gradio.app/guides/view-api-page
|
Additional Features - View Api Page Guide
|
Instead of reading through the view API page, you can also use Gradio's built-in API recorder to generate the relevant code snippet. Simply click on the "API Recorder" button, use your Gradio app via the UI as you would normally, and then the API Recorder will generate the code using the Clients to recreate your all of your interactions programmatically.
|
The API Recorder 🪄
|
https://gradio.app/guides/view-api-page
|
Additional Features - View Api Page Guide
|
The API page also includes instructions on how to use the Gradio app as an Model Context Protocol (MCP) server, which is a standardized way to expose functions as tools so that they can be used by LLMs.
For the MCP sever, each tool, its description, and its parameters are listed, along with instructions on how to integrate with popular MCP Clients. Read more about Gradio's [MCP integration here](https://www.gradio.app/guides/building-mcp-server-with-gradio).
|
MCP Server
|
https://gradio.app/guides/view-api-page
|
Additional Features - View Api Page Guide
|
You can access the complete OpenAPI (formerly Swagger) specification of your Gradio app's API at the endpoint `<your-gradio-app-url>/gradio_api/openapi.json`. The OpenAPI specification is a standardized, language-agnostic interface description for REST APIs that enables both humans and computers to discover and understand the capabilities of your service.
|
OpenAPI Specification
|
https://gradio.app/guides/view-api-page
|
Additional Features - View Api Page Guide
|
By default, Gradio automatically generates a navigation bar for multipage apps that displays all your pages with "Home" as the title for the main page. You can customize the navbar behavior using the `gr.Navbar` component.
Per-Page Navbar Configuration
You can have different navbar configurations for each page of your app:
```python
import gradio as gr
with gr.Blocks() as demo:
Navbar for the main page
navbar = gr.Navbar(
visible=True,
main_page_name="Dashboard",
value=[("About", "https://example.com/about")]
)
gr.Textbox(label="Main page content")
with demo.route("Settings"):
Different navbar for the Settings page
navbar = gr.Navbar(
visible=True,
main_page_name="Home",
value=[("Documentation", "https://docs.example.com")]
)
gr.Textbox(label="Settings page")
demo.launch()
```
**Important Notes:**
- You can have one `gr.Navbar` component per page. Each page's navbar configuration is independent.
- The `main_page_name` parameter customizes the title of the home page link in the navbar.
- The `value` parameter allows you to add additional links to the navbar, which can be internal pages or external URLs.
- If no `gr.Navbar` component is present on a page, the default navbar behavior is used (visible with "Home" as the home page title).
- You can update the navbar properties using standard Gradio event handling, just like with any other component.
Here's an example that demonstrates the last point:
$code_navbar_customization
|
Customizing the Navbar
|
https://gradio.app/guides/multipage-apps
|
Additional Features - Multipage Apps Guide
|
- **1. Static files**. You can designate static files or directories using the `gr.set_static_paths` function. Static files are not be copied to the Gradio cache (see below) and will be served directly from your computer. This can help save disk space and reduce the time your app takes to launch but be mindful of possible security implications as any static files are accessible to all useres of your Gradio app.
- **2. Files in the `allowed_paths` parameter in `launch()`**. This parameter allows you to pass in a list of additional directories or exact filepaths you'd like to allow users to have access to. (By default, this parameter is an empty list).
- **3. Files in Gradio's cache**. After you launch your Gradio app, Gradio copies certain files into a temporary cache and makes these files accessible to users. Let's unpack this in more detail below.
|
Files Gradio allows users to access
|
https://gradio.app/guides/file-access
|
Additional Features - File Access Guide
|
First, it's important to understand why Gradio has a cache at all. Gradio copies files to a cache directory before returning them to the frontend. This prevents files from being overwritten by one user while they are still needed by another user of your application. For example, if your prediction function returns a video file, then Gradio will move that video to the cache after your prediction function runs and returns a URL the frontend can use to show the video. Any file in the cache is available via URL to all users of your running application.
Tip: You can customize the location of the cache by setting the `GRADIO_TEMP_DIR` environment variable to an absolute path, such as `/home/usr/scripts/project/temp/`.
Files Gradio moves to the cache
Gradio moves three kinds of files into the cache
1. Files specified by the developer before runtime, e.g. cached examples, default values of components, or files passed into parameters such as the `avatar_images` of `gr.Chatbot`
2. File paths returned by a prediction function in your Gradio application, if they ALSO meet one of the conditions below:
* It is in the `allowed_paths` parameter of the `Blocks.launch` method.
* It is in the current working directory of the python interpreter.
* It is in the temp directory obtained by `tempfile.gettempdir()`.
**Note:** files in the current working directory whose name starts with a period (`.`) will not be moved to the cache, even if they are returned from a prediction function, since they often contain sensitive information.
If none of these criteria are met, the prediction function that is returning that file will raise an exception instead of moving the file to cache. Gradio performs this check so that arbitrary files on your machine cannot be accessed.
3. Files uploaded by a user to your Gradio app (e.g. through the `File` or `Image` input components).
Tip: If at any time Gradio blocks a file that you would like it to process, add its path to the `allowed_paths` p
|
The Gradio cache
|
https://gradio.app/guides/file-access
|
Additional Features - File Access Guide
|
d by a user to your Gradio app (e.g. through the `File` or `Image` input components).
Tip: If at any time Gradio blocks a file that you would like it to process, add its path to the `allowed_paths` parameter.
|
The Gradio cache
|
https://gradio.app/guides/file-access
|
Additional Features - File Access Guide
|
While running, Gradio apps will NOT ALLOW users to access:
- **Files that you explicitly block via the `blocked_paths` parameter in `launch()`**. You can pass in a list of additional directories or exact filepaths to the `blocked_paths` parameter in `launch()`. This parameter takes precedence over the files that Gradio exposes by default, or by the `allowed_paths` parameter or the `gr.set_static_paths` function.
- **Any other paths on the host machine**. Users should NOT be able to access other arbitrary paths on the host.
|
The files Gradio will not allow others to access
|
https://gradio.app/guides/file-access
|
Additional Features - File Access Guide
|
Sharing your Gradio application will also allow users to upload files to your computer or server. You can set a maximum file size for uploads to prevent abuse and to preserve disk space. You can do this with the `max_file_size` parameter of `.launch`. For example, the following two code snippets limit file uploads to 5 megabytes per file.
```python
import gradio as gr
demo = gr.Interface(lambda x: x, "image", "image")
demo.launch(max_file_size="5mb")
or
demo.launch(max_file_size=5 * gr.FileSize.MB)
```
|
Uploading Files
|
https://gradio.app/guides/file-access
|
Additional Features - File Access Guide
|
* Set a `max_file_size` for your application.
* Do not return arbitrary user input from a function that is connected to a file-based output component (`gr.Image`, `gr.File`, etc.). For example, the following interface would allow anyone to move an arbitrary file in your local directory to the cache: `gr.Interface(lambda s: s, "text", "file")`. This is because the user input is treated as an arbitrary file path.
* Make `allowed_paths` as small as possible. If a path in `allowed_paths` is a directory, any file within that directory can be accessed. Make sure the entires of `allowed_paths` only contains files related to your application.
* Run your gradio application from the same directory the application file is located in. This will narrow the scope of files Gradio will be allowed to move into the cache. For example, prefer `python app.py` to `python Users/sources/project/app.py`.
|
Best Practices
|
https://gradio.app/guides/file-access
|
Additional Features - File Access Guide
|
Both `gr.set_static_paths` and the `allowed_paths` parameter in launch expect absolute paths. Below is a minimal example to display a local `.png` image file in an HTML block.
```txt
├── assets
│ └── logo.png
└── app.py
```
For the example directory structure, `logo.png` and any other files in the `assets` folder can be accessed from your Gradio app in `app.py` as follows:
```python
from pathlib import Path
import gradio as gr
gr.set_static_paths(paths=[Path.cwd().absolute()/"assets"])
with gr.Blocks() as demo:
gr.HTML("<img src='/gradio_api/file=assets/logo.png'>")
demo.launch()
```
|
Example: Accessing local files
|
https://gradio.app/guides/file-access
|
Additional Features - File Access Guide
|
Let's create a demo where a user can choose a filter to apply to their webcam stream. Users can choose from an edge-detection filter, a cartoon filter, or simply flipping the stream vertically.
$code_streaming_filter
$demo_streaming_filter
You will notice that if you change the filter value it will immediately take effect in the output stream. That is an important difference of stream events in comparison to other Gradio events. The input values of the stream can be changed while the stream is being processed.
Tip: We set the "streaming" parameter of the image output component to be "True". Doing so lets the server automatically convert our output images into base64 format, a format that is efficient for streaming.
|
A Realistic Image Demo
|
https://gradio.app/guides/streaming-inputs
|
Additional Features - Streaming Inputs Guide
|
For some image streaming demos, like the one above, we don't need to display separate input and output components. Our app would look cleaner if we could just display the modified output stream.
We can do so by just specifying the input image component as the output of the stream event.
$code_streaming_filter_unified
$demo_streaming_filter_unified
|
Unified Image Demos
|
https://gradio.app/guides/streaming-inputs
|
Additional Features - Streaming Inputs Guide
|
Your streaming function should be stateless. It should take the current input and return its corresponding output. However, there are cases where you may want to keep track of past inputs or outputs. For example, you may want to keep a buffer of the previous `k` inputs to improve the accuracy of your transcription demo. You can do this with Gradio's `gr.State()` component.
Let's showcase this with a sample demo:
```python
def transcribe_handler(current_audio, state, transcript):
next_text = transcribe(current_audio, history=state)
state.append(current_audio)
state = state[-3:]
return state, transcript + next_text
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
mic = gr.Audio(sources="microphone")
state = gr.State(value=[])
with gr.Column():
transcript = gr.Textbox(label="Transcript")
mic.stream(transcribe_handler, [mic, state, transcript], [state, transcript],
time_limit=10, stream_every=1)
demo.launch()
```
|
Keeping track of past inputs or outputs
|
https://gradio.app/guides/streaming-inputs
|
Additional Features - Streaming Inputs Guide
|
For an end-to-end example of streaming from the webcam, see the object detection from webcam [guide](/main/guides/object-detection-from-webcam-with-webrtc).
|
End-to-End Examples
|
https://gradio.app/guides/streaming-inputs
|
Additional Features - Streaming Inputs Guide
|
By default, each event listener has its own queue, which handles one request at a time. This can be configured via two arguments:
- `concurrency_limit`: This sets the maximum number of concurrent executions for an event listener. By default, the limit is 1 unless configured otherwise in `Blocks.queue()`. You can also set it to `None` for no limit (i.e., an unlimited number of concurrent executions). For example:
```python
import gradio as gr
with gr.Blocks() as demo:
prompt = gr.Textbox()
image = gr.Image()
generate_btn = gr.Button("Generate Image")
generate_btn.click(image_gen, prompt, image, concurrency_limit=5)
```
In the code above, up to 5 requests can be processed simultaneously for this event listener. Additional requests will be queued until a slot becomes available.
If you want to manage multiple event listeners using a shared queue, you can use the `concurrency_id` argument:
- `concurrency_id`: This allows event listeners to share a queue by assigning them the same ID. For example, if your setup has only 2 GPUs but multiple functions require GPU access, you can create a shared queue for all those functions. Here's how that might look:
```python
import gradio as gr
with gr.Blocks() as demo:
prompt = gr.Textbox()
image = gr.Image()
generate_btn_1 = gr.Button("Generate Image via model 1")
generate_btn_2 = gr.Button("Generate Image via model 2")
generate_btn_3 = gr.Button("Generate Image via model 3")
generate_btn_1.click(image_gen_1, prompt, image, concurrency_limit=2, concurrency_id="gpu_queue")
generate_btn_2.click(image_gen_2, prompt, image, concurrency_id="gpu_queue")
generate_btn_3.click(image_gen_3, prompt, image, concurrency_id="gpu_queue")
```
In this example, all three event listeners share a queue identified by `"gpu_queue"`. The queue can handle up to 2 concurrent requests at a time, as defined by the `concurrency_limit`.
Notes
- To ensure unlimited concurrency for an event listener, se
|
Configuring the Queue
|
https://gradio.app/guides/queuing
|
Additional Features - Queuing Guide
|
identified by `"gpu_queue"`. The queue can handle up to 2 concurrent requests at a time, as defined by the `concurrency_limit`.
Notes
- To ensure unlimited concurrency for an event listener, set `concurrency_limit=None`. This is useful if your function is calling e.g. an external API which handles the rate limiting of requests itself.
- The default concurrency limit for all queues can be set globally using the `default_concurrency_limit` parameter in `Blocks.queue()`.
These configurations make it easy to manage the queuing behavior of your Gradio app.
|
Configuring the Queue
|
https://gradio.app/guides/queuing
|
Additional Features - Queuing Guide
|
1. `GRADIO_SERVER_PORT`
- **Description**: Specifies the port on which the Gradio app will run.
- **Default**: `7860`
- **Example**:
```bash
export GRADIO_SERVER_PORT=8000
```
2. `GRADIO_SERVER_NAME`
- **Description**: Defines the host name for the Gradio server. To make Gradio accessible from any IP address, set this to `"0.0.0.0"`
- **Default**: `"127.0.0.1"`
- **Example**:
```bash
export GRADIO_SERVER_NAME="0.0.0.0"
```
3. `GRADIO_NUM_PORTS`
- **Description**: Defines the number of ports to try when starting the Gradio server.
- **Default**: `100`
- **Example**:
```bash
export GRADIO_NUM_PORTS=200
```
4. `GRADIO_ANALYTICS_ENABLED`
- **Description**: Whether Gradio should provide
- **Default**: `"True"`
- **Options**: `"True"`, `"False"`
- **Example**:
```sh
export GRADIO_ANALYTICS_ENABLED="True"
```
5. `GRADIO_DEBUG`
- **Description**: Enables or disables debug mode in Gradio. If debug mode is enabled, the main thread does not terminate allowing error messages to be printed in environments such as Google Colab.
- **Default**: `0`
- **Example**:
```sh
export GRADIO_DEBUG=1
```
6. `GRADIO_FLAGGING_MODE`
- **Description**: Controls whether users can flag inputs/outputs in the Gradio interface. See [the Guide on flagging](/guides/using-flagging) for more details.
- **Default**: `"manual"`
- **Options**: `"never"`, `"manual"`, `"auto"`
- **Example**:
```sh
export GRADIO_FLAGGING_MODE="never"
```
7. `GRADIO_TEMP_DIR`
- **Description**: Specifies the directory where temporary files created by Gradio are stored.
- **Default**: System default temporary directory
- **Example**:
```sh
export GRADIO_TEMP_DIR="/path/to/temp"
```
8. `GRADIO_ROOT_PATH`
- **Description**: Sets the root path for the Gradio application. Useful if running Gradio [behind a reverse proxy](/guides/running-gradio-on-your-web-server-with-nginx).
- **Default**: `""`
- **Example**:
```sh
export GRADIO_ROOT_PATH=
|
Key Environment Variables
|
https://gradio.app/guides/environment-variables
|
Additional Features - Environment Variables Guide
|
r the Gradio application. Useful if running Gradio [behind a reverse proxy](/guides/running-gradio-on-your-web-server-with-nginx).
- **Default**: `""`
- **Example**:
```sh
export GRADIO_ROOT_PATH="/myapp"
```
9. `GRADIO_SHARE`
- **Description**: Enables or disables sharing the Gradio app.
- **Default**: `"False"`
- **Options**: `"True"`, `"False"`
- **Example**:
```sh
export GRADIO_SHARE="True"
```
10. `GRADIO_ALLOWED_PATHS`
- **Description**: Sets a list of complete filepaths or parent directories that gradio is allowed to serve. Must be absolute paths. Warning: if you provide directories, any files in these directories or their subdirectories are accessible to all users of your app. Multiple items can be specified by separating items with commas.
- **Default**: `""`
- **Example**:
```sh
export GRADIO_ALLOWED_PATHS="/mnt/sda1,/mnt/sda2"
```
11. `GRADIO_BLOCKED_PATHS`
- **Description**: Sets a list of complete filepaths or parent directories that gradio is not allowed to serve (i.e. users of your app are not allowed to access). Must be absolute paths. Warning: takes precedence over `allowed_paths` and all other directories exposed by Gradio by default. Multiple items can be specified by separating items with commas.
- **Default**: `""`
- **Example**:
```sh
export GRADIO_BLOCKED_PATHS="/users/x/gradio_app/admin,/users/x/gradio_app/keys"
```
12. `FORWARDED_ALLOW_IPS`
- **Description**: This is not a Gradio-specific environment variable, but rather one used in server configurations, specifically `uvicorn` which is used by Gradio internally. This environment variable is useful when deploying applications behind a reverse proxy. It defines a list of IP addresses that are trusted to forward traffic to your application. When set, the application will trust the `X-Forwarded-For` header from these IP addresses to determine the original IP address of the user making the request. This means that if you use the `gr.Request` [objec
|
Key Environment Variables
|
https://gradio.app/guides/environment-variables
|
Additional Features - Environment Variables Guide
|
the application will trust the `X-Forwarded-For` header from these IP addresses to determine the original IP address of the user making the request. This means that if you use the `gr.Request` [object's](https://www.gradio.app/docs/gradio/request) `client.host` property, it will correctly get the user's IP address instead of the IP address of the reverse proxy server. Note that only trusted IP addresses (i.e. the IP addresses of your reverse proxy servers) should be added, as any server with these IP addresses can modify the `X-Forwarded-For` header and spoof the client's IP address.
- **Default**: `"127.0.0.1"`
- **Example**:
```sh
export FORWARDED_ALLOW_IPS="127.0.0.1,192.168.1.100"
```
13. `GRADIO_CACHE_EXAMPLES`
- **Description**: Whether or not to cache examples by default in `gr.Interface()`, `gr.ChatInterface()` or in `gr.Examples()` when no explicit argument is passed for the `cache_examples` parameter. You can set this environment variable to either the string "true" or "false".
- **Default**: `"false"`
- **Example**:
```sh
export GRADIO_CACHE_EXAMPLES="true"
```
14. `GRADIO_CACHE_MODE`
- **Description**: How to cache examples. Only applies if `cache_examples` is set to `True` either via enviornment variable or by an explicit parameter, AND no no explicit argument is passed for the `cache_mode` parameter in `gr.Interface()`, `gr.ChatInterface()` or in `gr.Examples()`. Can be set to either the strings "lazy" or "eager." If "lazy", examples are cached after their first use for all users of the app. If "eager", all examples are cached at app launch.
- **Default**: `"eager"`
- **Example**:
```sh
export GRADIO_CACHE_MODE="lazy"
```
15. `GRADIO_EXAMPLES_CACHE`
- **Description**: If you set `cache_examples=True` in `gr.Interface()`, `gr.ChatInterface()` or in `gr.Examples()`, Gradio will run your prediction function and save the results to disk. By default, this is in the `.gradio/cached_examples//` subdirectory within your
|
Key Environment Variables
|
https://gradio.app/guides/environment-variables
|
Additional Features - Environment Variables Guide
|
e()`, `gr.ChatInterface()` or in `gr.Examples()`, Gradio will run your prediction function and save the results to disk. By default, this is in the `.gradio/cached_examples//` subdirectory within your app's working directory. You can customize the location of cached example files created by Gradio by setting the environment variable `GRADIO_EXAMPLES_CACHE` to an absolute path or a path relative to your working directory.
- **Default**: `".gradio/cached_examples/"`
- **Example**:
```sh
export GRADIO_EXAMPLES_CACHE="custom_cached_examples/"
```
16. `GRADIO_SSR_MODE`
- **Description**: Controls whether server-side rendering (SSR) is enabled. When enabled, the initial HTML is rendered on the server rather than the client, which can improve initial page load performance and SEO.
- **Default**: `"False"` (except on Hugging Face Spaces, where this environment variable sets it to `True`)
- **Options**: `"True"`, `"False"`
- **Example**:
```sh
export GRADIO_SSR_MODE="True"
```
17. `GRADIO_NODE_SERVER_NAME`
- **Description**: Defines the host name for the Gradio node server. (Only applies if `ssr_mode` is set to `True`.)
- **Default**: `GRADIO_SERVER_NAME` if it is set, otherwise `"127.0.0.1"`
- **Example**:
```sh
export GRADIO_NODE_SERVER_NAME="0.0.0.0"
```
18. `GRADIO_NODE_NUM_PORTS`
- **Description**: Defines the number of ports to try when starting the Gradio node server. (Only applies if `ssr_mode` is set to `True`.)
- **Default**: `100`
- **Example**:
```sh
export GRADIO_NODE_NUM_PORTS=200
```
19. `GRADIO_RESET_EXAMPLES_CACHE`
- **Description**: If set to "True", Gradio will delete and recreate the examples cache directory when the app starts instead of reusing the cached example if they already exist.
- **Default**: `"False"`
- **Options**: `"True"`, `"False"`
- **Example**:
```sh
export GRADIO_RESET_EXAMPLES_CACHE="True"
```
20. `GRADIO_CHAT_FLAGGING_MODE`
- **Description**: Controls whether users can flag
|
Key Environment Variables
|
https://gradio.app/guides/environment-variables
|
Additional Features - Environment Variables Guide
|
e"`
- **Options**: `"True"`, `"False"`
- **Example**:
```sh
export GRADIO_RESET_EXAMPLES_CACHE="True"
```
20. `GRADIO_CHAT_FLAGGING_MODE`
- **Description**: Controls whether users can flag messages in `gr.ChatInterface` applications. Similar to `GRADIO_FLAGGING_MODE` but specifically for chat interfaces.
- **Default**: `"never"`
- **Options**: `"never"`, `"manual"`
- **Example**:
```sh
export GRADIO_CHAT_FLAGGING_MODE="manual"
```
21. `GRADIO_WATCH_DIRS`
- **Description**: Specifies directories to watch for file changes when running Gradio in development mode. When files in these directories change, the Gradio app will automatically reload. Multiple directories can be specified by separating them with commas. This is primarily used by the `gradio` CLI command for development workflows.
- **Default**: `""`
- **Example**:
```sh
export GRADIO_WATCH_DIRS="/path/to/src,/path/to/templates"
```
22. `GRADIO_VIBE_MODE`
- **Description**: Enables the Vibe editor mode, which provides an in-browser chat that can be used to write or edit your Gradio app using natural language. When enabled, anyone who can access the Gradio endpoint can modify files and run arbitrary code on the host machine. Use with extreme caution in production environments.
- **Default**: `""`
- **Options**: Any non-empty string enables the mode
- **Example**:
```sh
export GRADIO_VIBE_MODE="1"
```
23. `GRADIO_MCP_SERVER`
- **Description**: Enables the MCP (Model Context Protocol) server functionality in Gradio. When enabled, the Gradio app will be set up as an MCP server and documented functions will be added as MCP tools that can be used by LLMs. This allows LLMs to interact with your Gradio app's functionality through the MCP protocol.
- **Default**: `"False"`
- **Options**: `"True"`, `"False"`
- **Example**:
```sh
export GRADIO_MCP_SERVER="True"
```
|
Key Environment Variables
|
https://gradio.app/guides/environment-variables
|
Additional Features - Environment Variables Guide
|
*Options**: `"True"`, `"False"`
- **Example**:
```sh
export GRADIO_MCP_SERVER="True"
```
|
Key Environment Variables
|
https://gradio.app/guides/environment-variables
|
Additional Features - Environment Variables Guide
|
To set environment variables in your terminal, use the `export` command followed by the variable name and its value. For example:
```sh
export GRADIO_SERVER_PORT=8000
```
If you're using a `.env` file to manage your environment variables, you can add them like this:
```sh
GRADIO_SERVER_PORT=8000
GRADIO_SERVER_NAME="localhost"
```
Then, use a tool like `dotenv` to load these variables when running your application.
|
How to Set Environment Variables
|
https://gradio.app/guides/environment-variables
|
Additional Features - Environment Variables Guide
|
When a user closes their browser tab, Gradio will automatically delete any `gr.State` variables associated with that user session after 60 minutes. If the user connects again within those 60 minutes, no state will be deleted.
You can control the deletion behavior further with the following two parameters of `gr.State`:
1. `delete_callback` - An arbitrary function that will be called when the variable is deleted. This function must take the state value as input. This function is useful for deleting variables from GPU memory.
2. `time_to_live` - The number of seconds the state should be stored for after it is created or updated. This will delete variables before the session is closed, so it's useful for clearing state for potentially long running sessions.
|
Automatic deletion of `gr.State`
|
https://gradio.app/guides/resource-cleanup
|
Additional Features - Resource Cleanup Guide
|
Your Gradio application will save uploaded and generated files to a special directory called the cache directory. Gradio uses a hashing scheme to ensure that duplicate files are not saved to the cache but over time the size of the cache will grow (especially if your app goes viral 😉).
Gradio can periodically clean up the cache for you if you specify the `delete_cache` parameter of `gr.Blocks()`, `gr.Interface()`, or `gr.ChatInterface()`.
This parameter is a tuple of the form `[frequency, age]` both expressed in number of seconds.
Every `frequency` seconds, the temporary files created by this Blocks instance will be deleted if more than `age` seconds have passed since the file was created.
For example, setting this to (86400, 86400) will delete temporary files every day if they are older than a day old.
Additionally, the cache will be deleted entirely when the server restarts.
|
Automatic cache cleanup via `delete_cache`
|
https://gradio.app/guides/resource-cleanup
|
Additional Features - Resource Cleanup Guide
|
Additionally, Gradio now includes a `Blocks.unload()` event, allowing you to run arbitrary cleanup functions when users disconnect (this does not have a 60 minute delay).
Unlike other gradio events, this event does not accept inputs or outptus.
You can think of the `unload` event as the opposite of the `load` event.
|
The `unload` event
|
https://gradio.app/guides/resource-cleanup
|
Additional Features - Resource Cleanup Guide
|
The following demo uses all of these features. When a user visits the page, a special unique directory is created for that user.
As the user interacts with the app, images are saved to disk in that special directory.
When the user closes the page, the images created in that session are deleted via the `unload` event.
The state and files in the cache are cleaned up automatically as well.
$code_state_cleanup
$demo_state_cleanup
|
Putting it all together
|
https://gradio.app/guides/resource-cleanup
|
Additional Features - Resource Cleanup Guide
|
Gradio can stream audio and video directly from your generator function.
This lets your user hear your audio or see your video nearly as soon as it's `yielded` by your function.
All you have to do is
1. Set `streaming=True` in your `gr.Audio` or `gr.Video` output component.
2. Write a python generator that yields the next "chunk" of audio or video.
3. Set `autoplay=True` so that the media starts playing automatically.
For audio, the next "chunk" can be either an `.mp3` or `.wav` file or a `bytes` sequence of audio.
For video, the next "chunk" has to be either `.mp4` file or a file with `h.264` codec with a `.ts` extension.
For smooth playback, make sure chunks are consistent lengths and larger than 1 second.
We'll finish with some simple examples illustrating these points.
Streaming Audio
```python
import gradio as gr
from time import sleep
def keep_repeating(audio_file):
for _ in range(10):
sleep(0.5)
yield audio_file
gr.Interface(keep_repeating,
gr.Audio(sources=["microphone"], type="filepath"),
gr.Audio(streaming=True, autoplay=True)
).launch()
```
Streaming Video
```python
import gradio as gr
from time import sleep
def keep_repeating(video_file):
for _ in range(10):
sleep(0.5)
yield video_file
gr.Interface(keep_repeating,
gr.Video(sources=["webcam"], format="mp4"),
gr.Video(streaming=True, autoplay=True)
).launch()
```
|
Streaming Media
|
https://gradio.app/guides/streaming-outputs
|
Additional Features - Streaming Outputs Guide
|
For an end-to-end example of streaming media, see the object detection from video [guide](/main/guides/object-detection-from-video) or the streaming AI-generated audio with [transformers](https://huggingface.co/docs/transformers/index) [guide](/main/guides/streaming-ai-generated-audio).
|
End-to-End Examples
|
https://gradio.app/guides/streaming-outputs
|
Additional Features - Streaming Outputs Guide
|
Gradio demos can be easily shared publicly by setting `share=True` in the `launch()` method. Like this:
```python
import gradio as gr
def greet(name):
return "Hello " + name + "!"
demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox")
demo.launch(share=True) Share your demo with just 1 extra parameter 🚀
```
This generates a public, shareable link that you can send to anybody! When you send this link, the user on the other side can try out the model in their browser. Because the processing happens on your device (as long as your device stays on), you don't have to worry about any packaging any dependencies.
A share link usually looks something like this: **https://07ff8706ab.gradio.live**. Although the link is served through the Gradio Share Servers, these servers are only a proxy for your local server, and do not store any data sent through your app. Share links expire after 1 week. (it is [also possible to set up your own Share Server](https://github.com/huggingface/frp/) on your own cloud server to overcome this restriction.)
Tip: Keep in mind that share links are publicly accessible, meaning that anyone can use your model for prediction! Therefore, make sure not to expose any sensitive information through the functions you write, or allow any critical changes to occur on your device. Or you can [add authentication to your Gradio app](authentication) as discussed below.
Note that by default, `share=False`, which means that your server is only running locally. (This is the default, except in Google Colab notebooks, where share links are automatically created). As an alternative to using share links, you can use use [SSH port-forwarding](https://www.ssh.com/ssh/tunneling/example) to share your local server with specific users.
|
Sharing Demos
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
If you'd like to have a permanent link to your Gradio demo on the internet, use Hugging Face Spaces. [Hugging Face Spaces](http://huggingface.co/spaces/) provides the infrastructure to permanently host your machine learning model for free!
After you have [created a free Hugging Face account](https://huggingface.co/join), you have two methods to deploy your Gradio app to Hugging Face Spaces:
1. From terminal: run `gradio deploy` in your app directory. The CLI will gather some basic metadata, upload all the files in the current directory (respecting any `.gitignore` file that may be present in the root of the directory), and then launch your app on Spaces. To update your Space, you can re-run this command or enable the Github Actions option in the CLI to automatically update the Spaces on `git push`.
2. From your browser: Drag and drop a folder containing your Gradio model and all related files [here](https://huggingface.co/new-space). See [this guide how to host on Hugging Face Spaces](https://huggingface.co/blog/gradio-spaces) for more information, or watch the embedded video:
<video autoplay muted loop>
<source src="https://github.com/gradio-app/gradio/blob/main/guides/assets/hf_demo.mp4?raw=true" type="video/mp4" />
</video>
|
Hosting on HF Spaces
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
You can add a button to your Gradio app that creates a unique URL you can use to share your app and all components **as they currently are** with others. This is useful for sharing unique and interesting generations from your application , or for saving a snapshot of your app at a particular point in time.
To add a deep link button to your app, place the `gr.DeepLinkButton` component anywhere in your app.
For the URL to be accessible to others, your app must be available at a public URL. So be sure to host your app like Hugging Face Spaces or use the `share=True` parameter when launching your app.
Let's see an example of how this works. Here's a simple Gradio chat ap that uses the `gr.DeepLinkButton` component. After a couple of messages, click the deep link button and paste it into a new browser tab to see the app as it is at that point in time.
$code_deep_link
$demo_deep_link
|
Sharing Deep Links
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
Once you have hosted your app on Hugging Face Spaces (or on your own server), you may want to embed the demo on a different website, such as your blog or your portfolio. Embedding an interactive demo allows people to try out the machine learning model that you have built, without needing to download or install anything — right in their browser! The best part is that you can embed interactive demos even in static websites, such as GitHub pages.
There are two ways to embed your Gradio demos. You can find quick links to both options directly on the Hugging Face Space page, in the "Embed this Space" dropdown option:
Embedding with Web Components
Web components typically offer a better experience to users than IFrames. Web components load lazily, meaning that they won't slow down the loading time of your website, and they automatically adjust their height based on the size of the Gradio app.
To embed with Web Components:
1. Import the gradio JS library into into your site by adding the script below in your site (replace {GRADIO_VERSION} in the URL with the library version of Gradio you are using).
```html
<script
type="module"
src="https://gradio.s3-us-west-2.amazonaws.com/{GRADIO_VERSION}/gradio.js"
></script>
```
2. Add
```html
<gradio-app src="https://$your_space_host.hf.space"></gradio-app>
```
element where you want to place the app. Set the `src=` attribute to your Space's embed URL, which you can find in the "Embed this Space" button. For example:
```html
<gradio-app
src="https://abidlabs-pytorch-image-classifier.hf.space"
></gradio-app>
```
<script>
fetch("https://pypi.org/pypi/gradio/json"
).then(r => r.json()
).then(obj => {
let v = obj.info.version;
content = document.querySelector('.prose');
content.innerHTML = content.innerHTML.replaceAll("{GRADIO_VERSION}", v);
});
</script>
You can see examples of h
|
Embedding Hosted Spaces
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
=> {
let v = obj.info.version;
content = document.querySelector('.prose');
content.innerHTML = content.innerHTML.replaceAll("{GRADIO_VERSION}", v);
});
</script>
You can see examples of how web components look <a href="https://www.gradio.app">on the Gradio landing page</a>.
You can also customize the appearance and behavior of your web component with attributes that you pass into the `<gradio-app>` tag:
- `src`: as we've seen, the `src` attributes links to the URL of the hosted Gradio demo that you would like to embed
- `space`: an optional shorthand if your Gradio demo is hosted on Hugging Face Space. Accepts a `username/space_name` instead of a full URL. Example: `gradio/Echocardiogram-Segmentation`. If this attribute attribute is provided, then `src` does not need to be provided.
- `control_page_title`: a boolean designating whether the html title of the page should be set to the title of the Gradio app (by default `"false"`)
- `initial_height`: the initial height of the web component while it is loading the Gradio app, (by default `"300px"`). Note that the final height is set based on the size of the Gradio app.
- `container`: whether to show the border frame and information about where the Space is hosted (by default `"true"`)
- `info`: whether to show just the information about where the Space is hosted underneath the embedded app (by default `"true"`)
- `autoscroll`: whether to autoscroll to the output when prediction has finished (by default `"false"`)
- `eager`: whether to load the Gradio app as soon as the page loads (by default `"false"`)
- `theme_mode`: whether to use the `dark`, `light`, or default `system` theme mode (by default `"system"`)
- `render`: an event that is triggered once the embedded space has finished rendering.
Here's an example of how to use these attributes to create a Gradio app that does not lazy load and has an initial height of 0px.
```html
<gradio-app
space="gradio/Echocardiogram-Segmentation"
eager="true"
init
|
Embedding Hosted Spaces
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
ple of how to use these attributes to create a Gradio app that does not lazy load and has an initial height of 0px.
```html
<gradio-app
space="gradio/Echocardiogram-Segmentation"
eager="true"
initial_height="0px"
></gradio-app>
```
Here's another example of how to use the `render` event. An event listener is used to capture the `render` event and will call the `handleLoadComplete()` function once rendering is complete.
```html
<script>
function handleLoadComplete() {
console.log("Embedded space has finished rendering");
}
const gradioApp = document.querySelector("gradio-app");
gradioApp.addEventListener("render", handleLoadComplete);
</script>
```
_Note: While Gradio's CSS will never impact the embedding page, the embedding page can affect the style of the embedded Gradio app. Make sure that any CSS in the parent page isn't so general that it could also apply to the embedded Gradio app and cause the styling to break. Element selectors such as `header { ... }` and `footer { ... }` will be the most likely to cause issues._
Embedding with IFrames
To embed with IFrames instead (if you cannot add javascript to your website, for example), add this element:
```html
<iframe src="https://$your_space_host.hf.space"></iframe>
```
Again, you can find the `src=` attribute to your Space's embed URL, which you can find in the "Embed this Space" button.
Note: if you use IFrames, you'll probably want to add a fixed `height` attribute and set `style="border:0;"` to remove the border. In addition, if your app requires permissions such as access to the webcam or the microphone, you'll need to provide that as well using the `allow` attribute.
|
Embedding Hosted Spaces
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
You can use almost any Gradio app as an API! In the footer of a Gradio app [like this one](https://huggingface.co/spaces/gradio/hello_world), you'll see a "Use via API" link.
This is a page that lists the endpoints that can be used to query the Gradio app, via our supported clients: either [the Python client](https://gradio.app/guides/getting-started-with-the-python-client/), or [the JavaScript client](https://gradio.app/guides/getting-started-with-the-js-client/). For each endpoint, Gradio automatically generates the parameters and their types, as well as example inputs, like this.
The endpoints are automatically created when you launch a Gradio application. If you are using Gradio `Blocks`, you can also name each event listener, such as
```python
btn.click(add, [num1, num2], output, api_name="addition")
```
This will add and document the endpoint `/addition/` to the automatically generated API page. Read more about the [API page here](./view-api-page).
|
API Page
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
When a user makes a prediction to your app, you may need the underlying network request, in order to get the request headers (e.g. for advanced authentication), log the client's IP address, getting the query parameters, or for other reasons. Gradio supports this in a similar manner to FastAPI: simply add a function parameter whose type hint is `gr.Request` and Gradio will pass in the network request as that parameter. Here is an example:
```python
import gradio as gr
def echo(text, request: gr.Request):
if request:
print("Request headers dictionary:", request.headers)
print("IP address:", request.client.host)
print("Query parameters:", dict(request.query_params))
return text
io = gr.Interface(echo, "textbox", "textbox").launch()
```
Note: if your function is called directly instead of through the UI (this happens, for
example, when examples are cached, or when the Gradio app is called via API), then `request` will be `None`.
You should handle this case explicitly to ensure that your app does not throw any errors. That is why
we have the explicit check `if request`.
|
Accessing the Network Request Directly
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
In some cases, you might have an existing FastAPI app, and you'd like to add a path for a Gradio demo.
You can easily do this with `gradio.mount_gradio_app()`.
Here's a complete example:
$code_custom_path
Note that this approach also allows you run your Gradio apps on custom paths (`http://localhost:8000/gradio` in the example above).
|
Mounting Within Another FastAPI App
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
Password-protected app
You may wish to put an authentication page in front of your app to limit who can open your app. With the `auth=` keyword argument in the `launch()` method, you can provide a tuple with a username and password, or a list of acceptable username/password tuples; Here's an example that provides password-based authentication for a single user named "admin":
```python
demo.launch(auth=("admin", "pass1234"))
```
For more complex authentication handling, you can even pass a function that takes a username and password as arguments, and returns `True` to allow access, `False` otherwise.
Here's an example of a function that accepts any login where the username and password are the same:
```python
def same_auth(username, password):
return username == password
demo.launch(auth=same_auth)
```
If you have multiple users, you may wish to customize the content that is shown depending on the user that is logged in. You can retrieve the logged in user by [accessing the network request directly](accessing-the-network-request-directly) as discussed above, and then reading the `.username` attribute of the request. Here's an example:
```python
import gradio as gr
def update_message(request: gr.Request):
return f"Welcome, {request.username}"
with gr.Blocks() as demo:
m = gr.Markdown()
demo.load(update_message, None, m)
demo.launch(auth=[("Abubakar", "Abubakar"), ("Ali", "Ali")])
```
Note: For authentication to work properly, third party cookies must be enabled in your browser. This is not the case by default for Safari or for Chrome Incognito Mode.
If users visit the `/logout` page of your Gradio app, they will automatically be logged out and session cookies deleted. This allows you to add logout functionality to your Gradio app as well. Let's update the previous example to include a log out button:
```python
import gradio as gr
def update_message(request: gr.Request):
return f"Welcome, {request.username}"
with gr.Blocks() as
|
Authentication
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
Let's update the previous example to include a log out button:
```python
import gradio as gr
def update_message(request: gr.Request):
return f"Welcome, {request.username}"
with gr.Blocks() as demo:
m = gr.Markdown()
logout_button = gr.Button("Logout", link="/logout")
demo.load(update_message, None, m)
demo.launch(auth=[("Pete", "Pete"), ("Dawood", "Dawood")])
```
By default, visiting `/logout` logs the user out from **all sessions** (e.g. if they are logged in from multiple browsers or devices, all will be signed out). If you want to log out only from the **current session**, add the query parameter `all_session=false` (i.e. `/logout?all_session=false`).
Note: Gradio's built-in authentication provides a straightforward and basic layer of access control but does not offer robust security features for applications that require stringent access controls (e.g. multi-factor authentication, rate limiting, or automatic lockout policies).
OAuth (Login via Hugging Face)
Gradio natively supports OAuth login via Hugging Face. In other words, you can easily add a _"Sign in with Hugging Face"_ button to your demo, which allows you to get a user's HF username as well as other information from their HF profile. Check out [this Space](https://huggingface.co/spaces/Wauplin/gradio-oauth-demo) for a live demo.
To enable OAuth, you must set `hf_oauth: true` as a Space metadata in your README.md file. This will register your Space
as an OAuth application on Hugging Face. Next, you can use `gr.LoginButton` to add a login button to
your Gradio app. Once a user is logged in with their HF account, you can retrieve their profile by adding a parameter of type
`gr.OAuthProfile` to any Gradio function. The user profile will be automatically injected as a parameter value. If you want
to perform actions on behalf of the user (e.g. list user's private repos, create repo, etc.), you can retrieve the user
token by adding a parameter of type `gr.OAuthToken`. You must def
|
Authentication
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
e. If you want
to perform actions on behalf of the user (e.g. list user's private repos, create repo, etc.), you can retrieve the user
token by adding a parameter of type `gr.OAuthToken`. You must define which scopes you will use in your Space metadata
(see [documentation](https://huggingface.co/docs/hub/spaces-oauthscopes) for more details).
Here is a short example:
$code_login_with_huggingface
When the user clicks on the login button, they get redirected in a new page to authorize your Space.
<center>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/gradio-guides/oauth_sign_in.png" style="width:300px; max-width:80%">
</center>
Users can revoke access to their profile at any time in their [settings](https://huggingface.co/settings/connected-applications).
As seen above, OAuth features are available only when your app runs in a Space. However, you often need to test your app
locally before deploying it. To test OAuth features locally, your machine must be logged in to Hugging Face. Please run `huggingface-cli login` or set `HF_TOKEN` as environment variable with one of your access token. You can generate a new token in your settings page (https://huggingface.co/settings/tokens). Then, clicking on the `gr.LoginButton` will log in to your local Hugging Face profile, allowing you to debug your app with your Hugging Face account before deploying it to a Space.
**Security Note**: It is important to note that adding a `gr.LoginButton` does not restrict users from using your app, in the same way that adding [username-password authentication](/guides/sharing-your-apppassword-protected-app) does. This means that users of your app who have not logged in with Hugging Face can still access and run events in your Gradio app -- the difference is that the `gr.OAuthProfile` or `gr.OAuthToken` will be `None` in the corresponding functions.
OAuth (with external providers)
It is also possible to authenticate with external OAuth pr
|
Authentication
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
erence is that the `gr.OAuthProfile` or `gr.OAuthToken` will be `None` in the corresponding functions.
OAuth (with external providers)
It is also possible to authenticate with external OAuth providers (e.g. Google OAuth) in your Gradio apps. To do this, first mount your Gradio app within a FastAPI app ([as discussed above](mounting-within-another-fast-api-app)). Then, you must write an *authentication function*, which gets the user's username from the OAuth provider and returns it. This function should be passed to the `auth_dependency` parameter in `gr.mount_gradio_app`.
Similar to [FastAPI dependency functions](https://fastapi.tiangolo.com/tutorial/dependencies/), the function specified by `auth_dependency` will run before any Gradio-related route in your FastAPI app. The function should accept a single parameter: the FastAPI `Request` and return either a string (representing a user's username) or `None`. If a string is returned, the user will be able to access the Gradio-related routes in your FastAPI app.
First, let's show a simplistic example to illustrate the `auth_dependency` parameter:
```python
from fastapi import FastAPI, Request
import gradio as gr
app = FastAPI()
def get_user(request: Request):
return request.headers.get("user")
demo = gr.Interface(lambda s: f"Hello {s}!", "textbox", "textbox")
app = gr.mount_gradio_app(app, demo, path="/demo", auth_dependency=get_user)
if __name__ == '__main__':
uvicorn.run(app)
```
In this example, only requests that include a "user" header will be allowed to access the Gradio app. Of course, this does not add much security, since any user can add this header in their request.
Here's a more complete example showing how to add Google OAuth to a Gradio app (assuming you've already created OAuth Credentials on the [Google Developer Console](https://console.cloud.google.com/project)):
```python
import os
from authlib.integrations.starlette_client import OAuth, OAuthError
from fastapi import FastA
|
Authentication
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
entials on the [Google Developer Console](https://console.cloud.google.com/project)):
```python
import os
from authlib.integrations.starlette_client import OAuth, OAuthError
from fastapi import FastAPI, Depends, Request
from starlette.config import Config
from starlette.responses import RedirectResponse
from starlette.middleware.sessions import SessionMiddleware
import uvicorn
import gradio as gr
app = FastAPI()
Replace these with your own OAuth settings
GOOGLE_CLIENT_ID = "..."
GOOGLE_CLIENT_SECRET = "..."
SECRET_KEY = "..."
config_data = {'GOOGLE_CLIENT_ID': GOOGLE_CLIENT_ID, 'GOOGLE_CLIENT_SECRET': GOOGLE_CLIENT_SECRET}
starlette_config = Config(environ=config_data)
oauth = OAuth(starlette_config)
oauth.register(
name='google',
server_metadata_url='https://accounts.google.com/.well-known/openid-configuration',
client_kwargs={'scope': 'openid email profile'},
)
SECRET_KEY = os.environ.get('SECRET_KEY') or "a_very_secret_key"
app.add_middleware(SessionMiddleware, secret_key=SECRET_KEY)
Dependency to get the current user
def get_user(request: Request):
user = request.session.get('user')
if user:
return user['name']
return None
@app.get('/')
def public(user: dict = Depends(get_user)):
if user:
return RedirectResponse(url='/gradio')
else:
return RedirectResponse(url='/login-demo')
@app.route('/logout')
async def logout(request: Request):
request.session.pop('user', None)
return RedirectResponse(url='/')
@app.route('/login')
async def login(request: Request):
redirect_uri = request.url_for('auth')
If your app is running on https, you should ensure that the
`redirect_uri` is https, e.g. uncomment the following lines:
from urllib.parse import urlparse, urlunparse
redirect_uri = urlunparse(urlparse(str(redirect_uri))._replace(scheme='https'))
return await oauth.google.authorize_redirect(request, redirect_uri)
@app.route('/auth')
async def auth(request: Reque
|
Authentication
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
direct_uri = urlunparse(urlparse(str(redirect_uri))._replace(scheme='https'))
return await oauth.google.authorize_redirect(request, redirect_uri)
@app.route('/auth')
async def auth(request: Request):
try:
access_token = await oauth.google.authorize_access_token(request)
except OAuthError:
return RedirectResponse(url='/')
request.session['user'] = dict(access_token)["userinfo"]
return RedirectResponse(url='/')
with gr.Blocks() as login_demo:
gr.Button("Login", link="/login")
app = gr.mount_gradio_app(app, login_demo, path="/login-demo")
def greet(request: gr.Request):
return f"Welcome to Gradio, {request.username}"
with gr.Blocks() as main_demo:
m = gr.Markdown("Welcome to Gradio!")
gr.Button("Logout", link="/logout")
main_demo.load(greet, None, m)
app = gr.mount_gradio_app(app, main_demo, path="/gradio", auth_dependency=get_user)
if __name__ == '__main__':
uvicorn.run(app)
```
There are actually two separate Gradio apps in this example! One that simply displays a log in button (this demo is accessible to any user), while the other main demo is only accessible to users that are logged in. You can try this example out on [this Space](https://huggingface.co/spaces/gradio/oauth-example).
|
Authentication
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
Gradio apps can function as MCP (Model Context Protocol) servers, allowing LLMs to use your app's functions as tools. By simply setting `mcp_server=True` in the `.launch()` method, Gradio automatically converts your app's functions into MCP tools that can be called by MCP clients like Claude Desktop, Cursor, or Cline. The server exposes tools based on your function names, docstrings, and type hints, and can handle file uploads, authentication headers, and progress updates. You can also create MCP-only functions using `gr.api` and expose resources and prompts using decorators. For a comprehensive guide on building MCP servers with Gradio, see [Building an MCP Server with Gradio](https://www.gradio.app/guides/building-mcp-server-with-gradio).
|
MCP Servers
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
When publishing your app publicly, and making it available via API or via MCP server, you might want to set rate limits to prevent users from abusing your app. You can identify users using their IP address (using the `gr.Request` object [as discussed above](accessing-the-network-request-directly)) or, if they are logged in via Hugging Face OAuth, using their username. To see a complete example of how to set rate limits, please see [this Gradio app](https://github.com/gradio-app/gradio/blob/main/demo/rate_limit/run.py).
|
Rate Limits
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
By default, Gradio collects certain analytics to help us better understand the usage of the `gradio` library. This includes the following information:
* What environment the Gradio app is running on (e.g. Colab Notebook, Hugging Face Spaces)
* What input/output components are being used in the Gradio app
* Whether the Gradio app is utilizing certain advanced features, such as `auth` or `show_error`
* The IP address which is used solely to measure the number of unique developers using Gradio
* The version of Gradio that is running
No information is collected from _users_ of your Gradio app. If you'd like to disable analytics altogether, you can do so by setting the `analytics_enabled` parameter to `False` in `gr.Blocks`, `gr.Interface`, or `gr.ChatInterface`. Or, you can set the GRADIO_ANALYTICS_ENABLED environment variable to `"False"` to apply this to all Gradio apps created across your system.
*Note*: this reflects the analytics policy as of `gradio>=4.32.0`.
|
Analytics
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
[Progressive Web Apps (PWAs)](https://developer.mozilla.org/en-US/docs/Web/Progressive_web_apps) are web applications that are regular web pages or websites, but can appear to the user like installable platform-specific applications.
Gradio apps can be easily served as PWAs by setting the `pwa=True` parameter in the `launch()` method. Here's an example:
```python
import gradio as gr
def greet(name):
return "Hello " + name + "!"
demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox")
demo.launch(pwa=True) Launch your app as a PWA
```
This will generate a PWA that can be installed on your device. Here's how it looks:
When you specify `favicon_path` in the `launch()` method, the icon will be used as the app's icon. Here's an example:
```python
demo.launch(pwa=True, favicon_path="./hf-logo.svg") Use a custom icon for your PWA
```
|
Progressive Web App (PWA)
|
https://gradio.app/guides/sharing-your-app
|
Additional Features - Sharing Your App Guide
|
You can initialize the `I18n` class with multiple language dictionaries to add custom translations:
```python
import gradio as gr
Create an I18n instance with translations for multiple languages
i18n = gr.I18n(
en={"greeting": "Hello, welcome to my app!", "submit": "Submit"},
es={"greeting": "¡Hola, bienvenido a mi aplicación!", "submit": "Enviar"},
fr={"greeting": "Bonjour, bienvenue dans mon application!", "submit": "Soumettre"}
)
with gr.Blocks() as demo:
Use the i18n method to translate the greeting
gr.Markdown(i18n("greeting"))
with gr.Row():
input_text = gr.Textbox(label="Input")
output_text = gr.Textbox(label="Output")
submit_btn = gr.Button(i18n("submit"))
Pass the i18n instance to the launch method
demo.launch(i18n=i18n)
```
|
Setting Up Translations
|
https://gradio.app/guides/internationalization
|
Additional Features - Internationalization Guide
|
When you use the `i18n` instance with a translation key, Gradio will show the corresponding translation to users based on their browser's language settings or the language they've selected in your app.
If a translation isn't available for the user's locale, the system will fall back to English (if available) or display the key itself.
|
How It Works
|
https://gradio.app/guides/internationalization
|
Additional Features - Internationalization Guide
|
Locale codes should follow the BCP 47 format (e.g., 'en', 'en-US', 'zh-CN'). The `I18n` class will warn you if you use an invalid locale code.
|
Valid Locale Codes
|
https://gradio.app/guides/internationalization
|
Additional Features - Internationalization Guide
|
The following component properties typically support internationalization:
- `description`
- `info`
- `title`
- `placeholder`
- `value`
- `label`
Note that support may vary depending on the component, and some properties might have exceptions where internationalization is not applicable. You can check this by referring to the typehint for the parameter and if it contains `I18nData`, then it supports internationalization.
|
Supported Component Properties
|
https://gradio.app/guides/internationalization
|
Additional Features - Internationalization Guide
|
Client side functions are ideal for updating component properties (like visibility, placeholders, interactive state, or styling).
Here's a basic example:
```py
import gradio as gr
with gr.Blocks() as demo:
with gr.Row() as row:
btn = gr.Button("Hide this row")
This function runs in the browser without a server roundtrip
btn.click(
lambda: gr.Row(visible=False),
None,
row,
js=True
)
demo.launch()
```
|
When to Use Client Side Functions
|
https://gradio.app/guides/client-side-functions
|
Additional Features - Client Side Functions Guide
|
Client side functions have some important restrictions:
* They can only update component properties (not values)
* They cannot take any inputs
Here are some functions that will work with `js=True`:
```py
Simple property updates
lambda: gr.Textbox(lines=4)
Multiple component updates
lambda: [gr.Textbox(lines=4), gr.Button(interactive=False)]
Using gr.update() for property changes
lambda: gr.update(visible=True, interactive=False)
```
We are working to increase the space of functions that can be transpiled to JavaScript so that they can be run in the browser. [Follow the Groovy library for more info](https://github.com/abidlabs/groovy-transpiler).
|
Limitations
|
https://gradio.app/guides/client-side-functions
|
Additional Features - Client Side Functions Guide
|
Here's a more complete example showing how client side functions can improve the user experience:
$code_todo_list_js
|
Complete Example
|
https://gradio.app/guides/client-side-functions
|
Additional Features - Client Side Functions Guide
|
When you set `js=True`, Gradio:
1. Transpiles your Python function to JavaScript
2. Runs the function directly in the browser
3. Still sends the request to the server (for consistency and to handle any side effects)
This provides immediate visual feedback while ensuring your application state remains consistent.
|
Behind the Scenes
|
https://gradio.app/guides/client-side-functions
|
Additional Features - Client Side Functions Guide
|
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