Components
Navbar

New to Gradio? Start here: Getting Started

To install Gradio from main, run the following command:

pip install https://gradio-builds.s3.amazonaws.com/3fcd23a09df280468351eac4fb081e79c8e58216/gradio-6.0.1-py3-none-any.whl

*Note: Setting share=True in launch() will not work.

←

MultimodalTextbox

Number

→

Navbar

gradio.Navbar(···)

Description

Creates a navigation bar component for multipage Gradio apps. The navbar component allows customizing the appearance of the navbar for that page. Only one Navbar component can exist per page in a Blocks app, and it can be placed anywhere within the page.
The Navbar component is designed to control the appearance of the navigation bar in multipage applications. When present in a Blocks app, its properties override the default navbar behavior.

Behavior

As input component: The preprocessed input data sent to the user's function in the backend.

Your function should accept one of these types:

def predict(
	value: list[tuple[str, str]] | None
)
	...

As output component: The output data received by the component from the user's function in the backend.

Your function should return one of these types:

def predict(···) -> list[tuple[str, str]] | None
	...	
	return value

Initialization

🔗

value: list[tuple[str, str]] | None

default = None

If a list of tuples of (page_name, page_path) are provided, these additional pages will be added to the navbar alongside the existing pages defined in the Blocks app. The page_path can be either a relative path for internal Gradio app pages (e.g., "analytics") or an absolute URL for external links (e.g., "https://twitter.com/username"). Otherwise, only the pages defined using the `Blocks.route` method will be displayed. Example: [("Dashboard", "dashboard"), ("About", "https://twitter.com/abidlabs")]

🔗

render: bool

default = True

If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.

Shortcuts

Class	Interface String Shortcut	Initialization
`gradio.Navbar`	"navbar"	Uses default values

Event Listeners

Description

Event listeners allow you to respond to user interactions with the UI components you've defined in a Gradio Blocks app. When a user interacts with an element, such as changing a slider value or uploading an image, a function is called.

Supported Event Listeners

The Navbar component supports the following event listeners. Each event listener takes the same parameters, which are listed in the Event Parameters table below.

Listener	Description
`Navbar.change(fn, ···)`	Triggered when the value of the Navbar changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.

Event Parameters

🔗

fn: Callable | None | Literal['decorator']

default = "decorator"

the function to call when this event is triggered. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.

🔗

inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None

default = None

List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list.

🔗

outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None

default = None

List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list.

🔗

api_name: str | None

default = None

defines how the endpoint appears in the API docs. Can be a string or None. If set to a string, the endpoint will be exposed in the API docs with the given name. If None (default), the name of the function will be used as the API endpoint.

🔗

api_description: str | None | Literal[False]

default = None

Description of the API endpoint. Can be a string, None, or False. If set to a string, the endpoint will be exposed in the API docs with the given description. If None, the function's docstring will be used as the API endpoint description. If False, then no description will be displayed in the API docs.

🔗

scroll_to_output: bool

default = False

If True, will scroll to output component on completion

🔗

show_progress: Literal['full', 'minimal', 'hidden']

default = "full"

how to show the progress animation while event is running: "full" shows a spinner which covers the output component area as well as a runtime display in the upper right corner, "minimal" only shows the runtime display, "hidden" shows no progress animation at all

🔗

show_progress_on: Component | list[Component] | None

default = None

Component or list of components to show the progress animation on. If None, will show the progress animation on all of the output components.

🔗

queue: bool

default = True

If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app.

🔗

batch: bool

default = False

If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component.

🔗

max_batch_size: int

default = 4

Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True)

🔗

preprocess: bool

default = True

If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component).

🔗

postprocess: bool

default = True

If False, will not run postprocessing of component data before returning 'fn' output to the browser.

🔗

cancels: dict[str, Any] | list[dict[str, Any]] | None

default = None

A list of other events to cancel when this listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish.

🔗

trigger_mode: Literal['once', 'multiple', 'always_last'] | None

default = None

If "once" (default for all events except `.change()`) would not allow any submissions while an event is pending. If set to "multiple", unlimited submissions are allowed while pending, and "always_last" (default for `.change()` and `.key_up()` events) would allow a second submission after the pending event is complete.

🔗

js: str | Literal[True] | None

default = None

Optional frontend js method to run before running 'fn'. Input arguments for js method are values of 'inputs' and 'outputs', return should be a list of values for output components.

🔗

concurrency_limit: int | None | Literal['default']

default = "default"

If set, this is the maximum number of this event that can be running simultaneously. Can be set to None to mean no concurrency_limit (any number of this event can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `Blocks.queue()`, which itself is 1 by default).

🔗

concurrency_id: str | None

default = None

If set, this is the id of the concurrency group. Events with the same concurrency_id will be limited by the lowest set concurrency_limit.

🔗

api_visibility: Literal['public', 'private', 'undocumented']

default = "public"

controls the visibility and accessibility of this endpoint. Can be "public" (shown in API docs and callable by clients), "private" (hidden from API docs and not callable by clients), or "undocumented" (hidden from API docs but callable by clients and via gr.load). If fn is None, api_visibility will automatically be set to "private".

🔗

time_limit: int | None

default = None

🔗

stream_every: float

default = 0.5

🔗

key: int | str | tuple[int | str, ...] | None

default = None

A unique key for this event listener to be used in @gr.render(). If set, this value identifies an event as identical across re-renders when the key is identical.

🔗

validator: Callable | None

default = None

Optional validation function to run before the main function. If provided, this function will be executed first with queue=False, and only if it completes successfully will the main function be called. The validator receives the same inputs as the main function and should return a `gr.validate()` for each input value.

←

MultimodalTextbox

Number

→

Building Demos

Blocks Layout

Components

Helpers

Modals

Routes

Other

Navbar

Description

Behavior

As input component: The preprocessed input data sent to the user's function in the backend.

Your function should accept one of these types:

As output component: The output data received by the component from the user's function in the backend.

Your function should return one of these types:

Initialization

Shortcuts

Event Listeners

Description

Supported Event Listeners

Event Parameters