Introducing Gradio Clients

Watch
  1. Components
  2. UploadButton

New to Gradio? Start here: Getting Started

See the Release History

UploadButton

gradio.UploadButton(···)
import gradio as gr def upload_file(files): file_paths = [file.name for file in files] return file_paths with gr.Blocks() as demo: file_output = gr.File() upload_button = gr.UploadButton("Click to Upload an Image or Video File", file_types=["image", "video"], file_count="multiple") upload_button.upload(upload_file, upload_button, file_output) demo.launch()

Description

Used to create an upload button, when clicked allows a user to upload files that satisfy the specified file type or generic files (if file_type not set).

Behavior

As input component: Passes the file as a str or bytes object, or a list of str or list of bytes objects, depending on type and file_count.

Your function should accept one of these types:
def predict(
	value: bytes | str | list[bytes] | list[str] | None
)
	...

As output component: Expects a str filepath or URL, or a list[str] of filepaths/URLs.

Your function should return one of these types:
def predict(···) -> str | list[str] | None
	...	
	return value

Initialization

Parameters
label: str
default = "Upload a File"

Text to display on the button. Defaults to "Upload a File".

value: str | list[str] | Callable | None
default = None

File or list of files to upload by default.

every: Timer | float | None
default = None

Continously calls `value` to recalculate it if `value` is a function (has no effect otherwise). Can provide a Timer whose tick resets `value`, or a float that provides the regular interval for the reset Timer.

inputs: Component | list[Component] | set[Component] | None
default = None

Components that are used as inputs to calculate `value` if `value` is a function (has no effect otherwise). `value` is recalculated any time the inputs change.

variant: Literal['primary', 'secondary', 'stop']
default = "secondary"

'primary' for main call-to-action, 'secondary' for a more subdued style, 'stop' for a stop button.

visible: bool
default = True

If False, component will be hidden.

size: Literal['sm', 'lg'] | None
default = None

Size of the button. Can be "sm" or "lg".

icon: str | None
default = None

URL or path to the icon file to display within the button. If None, no icon will be displayed.

scale: int | None
default = None

relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.

min_width: int | None
default = None

minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.

interactive: bool
default = True

If False, the UploadButton will be in a disabled state.

elem_id: str | None
default = None

An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.

elem_classes: list[str] | str | None
default = None

An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.

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.

key: int | str | None
default = None

if assigned, will be used to assume identity across a re-render. Components that have the same key across a re-render will have their value preserved.

type: Literal['filepath', 'binary']
default = "filepath"

Type of value to be returned by component. "file" returns a temporary file object with the same base name as the uploaded file, whose full path can be retrieved by file_obj.name, "binary" returns an bytes object.

file_count: Literal['single', 'multiple', 'directory']
default = "single"

if single, allows user to upload one file. If "multiple", user uploads multiple files. If "directory", user uploads all files in selected directory. Return type will be list for each file in case of "multiple" or "directory".

file_types: list[str] | None
default = None

List of type of files to be uploaded. "file" allows any file to be uploaded, "image" allows only image files to be uploaded, "audio" allows only audio files to be uploaded, "video" allows only video files to be uploaded, "text" allows only text files to be uploaded.

Shortcuts

Class Interface String Shortcut Initialization

gradio.UploadButton

"uploadbutton"

Uses default values

Demos

from pathlib import Path
import gradio as gr

def upload_file(filepath):
    name = Path(filepath).name
    return [gr.UploadButton(visible=False), gr.DownloadButton(label=f"Download {name}", value=filepath, visible=True)]

def download_file():
    return [gr.UploadButton(visible=True), gr.DownloadButton(visible=False)]

with gr.Blocks() as demo:
    gr.Markdown("First upload a file and and then you'll be able download it (but only once!)")
    with gr.Row():
        u = gr.UploadButton("Upload a file", file_count="single")
        d = gr.DownloadButton("Download the file", visible=False)

    u.upload(upload_file, u, [u, d])
    d.click(download_file, None, [u, d])

if __name__ == "__main__":
    demo.launch()

		

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

Listener Description

UploadButton.click(fn, ···)

Triggered when the UploadButton is clicked.

UploadButton.upload(fn, ···)

This listener is triggered when the user uploads a file into the UploadButton.

Event Parameters

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 | Literal[False]
default = None

defines how the endpoint appears in the API docs. Can be a string, None, or False. 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. If False, the endpoint will not be exposed in the API docs and downstream apps (including those that `gr.load` this app) will not be able to use this event.

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

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 | 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.

show_api: bool
default = True

whether to show this event in the "view API" page of the Gradio app, or in the ".view_api()" method of the Gradio clients. Unlike setting api_name to False, setting show_api to False will still allow downstream apps as well as the Clients to use this event. If fn is None, show_api will automatically be set to False.

time_limit: int | None
default = None
stream_every: float
default = 0.5
like_user_message: bool
default = False