text stringlengths 0 2k | heading1 stringlengths 4 79 | source_page_url stringclasses 183 values | source_page_title stringclasses 183 values |
|---|---|---|---|
r(). 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.
| Event Listeners | https://gradio.app/docs/gradio/checkbox | Gradio - Checkbox Docs |
Creates a dropdown of choices from which a single entry or multiple entries
can be selected (as an input component) or displayed (as an output component).
| Description | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
**Using Dropdown as an input component.**
How Dropdown will pass its value to your function:
Type: `str | int | float | list[str | int | float] | list[int | None] | None`
Passes the value of the selected dropdown choice as a `str | int | float` or its index as an `int` into the function, depending on `type`. Or, if `multiselect` is True, passes the values of the selected dropdown choices as a list of corresponding values/indices instead.
Example Code
import gradio as gr
def predict(
value: str | int | float | list[str | int | float] | list[int | None] | None
):
process value from the Dropdown component
return "prediction"
interface = gr.Interface(predict, gr.Dropdown(), gr.Textbox())
interface.launch()
**Using Dropdown as an output component**
How Dropdown expects you to return a value:
Type: `str | int | float | list[str | int | float] | None`
Expects a `str | int | float` corresponding to the value of the dropdown entry to be selected. Or, if `multiselect` is True, expects a `list` of values corresponding to the selected dropdown entries.
Example Code
import gradio as gr
def predict(text) -> str | int | float | list[str | int | float] | None
process value to return to the Dropdown component
return value
interface = gr.Interface(predict, gr.Textbox(), gr.Dropdown())
interface.launch()
| Behavior | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
Parameters ▼
choices: list[str | int | float | tuple[str, str | int | float]] | None
default `= None`
a list of string or numeric options to choose from. An option can also be a
tuple of the form (name, value), where name is the displayed name of the
dropdown choice and value is the value to be passed to the function, or
returned by the function.
value: str | int | float | list[str | int | float] | Callable | DefaultValue | None
default `= DefaultValue()`
the value selected in dropdown. If `multiselect` is true, this should be list,
otherwise a single string or number from among `choices`. By default, the
first choice in `choices` is initally selected. If set explicitly to None, no
value is initally selected. If a function is provided, the function will be
called each time the app loads to set the initial value of this component.
type: Literal['value', 'index']
default `= "value"`
type of value to be returned by component. "value" returns the string of the
choice selected, "index" returns the index of the choice selected.
multiselect: bool | None
default `= None`
if True, multiple choices can be selected.
allow_custom_value: bool
default `= False`
if True, allows user to enter a custom value that is not in the list of
choices.
max_choices: int | None
default `= None`
maximum number of choices that can be selected. If None, no limit is enforced.
filterable: bool
default `= True`
if True, user will be able to type into the dropdown and filter the choices by
typing. Can only be set to False if `allow_custom_value` is False.
label: str | I18nData | None
default `= None`
the label for this component, displayed above the component if `show_label` is
`True` and is also used as the header if there are a table of examples for
this component. If None and used in a `gr.Interface`, the label will be the
name of the parameter this compon | Initialization | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
`show_label` is
`True` and is also used as the header if there are a table of examples for
this component. If None and used in a `gr.Interface`, the label will be the
name of the parameter this component corresponds to.
info: str | I18nData | None
default `= None`
additional component description, appears below the label in smaller font.
Supports markdown / HTML syntax.
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.
show_label: bool | None
default `= None`
if True, will display label.
container: bool
default `= True`
if True, will place the component in a container - providing some extra
padding around the border.
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
default `= 160`
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 | None
default `= None`
if True, choices in this dropdown will be selectable; if False, selection will
be disabled. If not provided, this is inferred based on whether the component
is used as an input or output.
| Initialization | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
ne`
if True, choices in this dropdown will be selectable; if False, selection will
be disabled. If not provided, this is inferred based on whether the component
is used as an input or output.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
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 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 | tuple[int | str, ...] | None
default `= None`
preserved_by_key: list[str] | str | None
default `= "value"`
buttons: list[Button] | None
default `= None`
A list of gr.Button() instances to show in the top right corner of the
component. Custom buttons will appear in the toolbar with their configured
icon and/or label, and clicking them will trigger any .click() events
registered on the button.
| Initialization | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
Shortcuts
gradio.Dropdown
Interface String Shortcut `"dropdown"`
Initialization Uses default values
| Shortcuts | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
sentence_builder
| Demos | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
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 Dropdown component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listeners
Dropdown.change(fn, ···)
Triggered when the value of the Dropdown 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.
Dropdown.input(fn, ···)
This listener is triggered when the user changes the value of the Dropdown.
Dropdown.select(fn, ···)
Event listener for when the user selects or deselects the Dropdown. Uses event
data gradio.SelectData to carry `value` referring to the label of the
Dropdown, and `selected` to refer to state of the Dropdown. See
<https://www.gradio.app/main/docs/gradio/eventdata> for more details.
Dropdown.focus(fn, ···)
This listener is triggered when the Dropdown is focused.
Dropdown.blur(fn, ···)
This listener is triggered when the Dropdown is unfocused/blurred.
Dropdown.key_up(fn, ···)
This listener is triggered when the user presses a key while the Dropdown is
focused.
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.
| Event Listeners | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
he 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 s | Event Listeners | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
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', 'alway | Event Listeners | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
e
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`
| Event Listeners | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
r.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.
| Event Listeners | https://gradio.app/docs/gradio/dropdown | Gradio - Dropdown Docs |
Creates a component with arbitrary HTML. Can include CSS and JavaScript to
create highly customized and interactive components.
| Description | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
**Using HTML as an input component.**
How HTML will pass its value to your function:
Type: `str | None`
(Rarely used) passes the HTML as a `str`.
Example Code
import gradio as gr
def predict(
value: str | None
):
process value from the HTML component
return "prediction"
interface = gr.Interface(predict, gr.HTML(), gr.Textbox())
interface.launch()
**Using HTML as an output component**
How HTML expects you to return a value:
Type: `str | None`
Expects a `str` consisting of valid HTML.
Example Code
import gradio as gr
def predict(text) -> str | None
process value to return to the HTML component
return value
interface = gr.Interface(predict, gr.Textbox(), gr.HTML())
interface.launch()
| Behavior | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
Parameters ▼
value: Any | Callable | None
default `= None`
The HTML content in the ${value} tag in the html_template. For example, if
html_template="<p>${value}</p>" and value="Hello, world!", the component will
render as `"<p>Hello, world!</p>"`.
label: str | I18nData | None
default `= None`
The label for this component. Is used as the header if there are a table of
examples for this component. If None and used in a `gr.Interface`, the label
will be the name of the parameter this component is assigned to.
html_template: str
default `= "${value}"`
A string representing the HTML template for this component as a JS template
string and Handlebars template. The `${value}` tag will be replaced with the
`value` parameter, and all other tags will be filled in with the values from
`props`. This element can have children when used in a `with gr.HTML(...):`
context, and the children will be rendered to replace `@children` substring,
which cannot be nested inside any HTML tags.
css_template: str
default `= ""`
A string representing the CSS template for this component as a JS template
string and Handlebars template. The CSS will be automatically scoped to this
component, and rules outside a block will target the component's root element.
The `${value}` tag will be replaced with the `value` parameter, and all other
tags will be filled in with the values from `props`.
js_on_load: str | None
default `= "element.addEventListener('click', function() { trigger('click')
});"`
A string representing the JavaScript code that will be executed when the
component is loaded. The `element` variable refers to the HTML element of this
component, and can be used to access children such as
`element.querySelector()`. The `trigger` function can be used to trigger
events, such as `trigger('click')`. The value and other props can be edited
through `props`, e.g. `props.value = "new value"` which will re-render th | Initialization | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
()`. The `trigger` function can be used to trigger
events, such as `trigger('click')`. The value and other props can be edited
through `props`, e.g. `props.value = "new value"` which will re-render the
HTML template. If `server_functions` is provided, a `server` object is also
available in `js_on_load`, where each function is accessible as an async
method, e.g. `server.list_files(path).then(files => ...)` or `const files =
await server.list_files(path)`. The `upload` async function can be used to
upload a JavaScript `File` object to the Gradio server, returning a dictionary
with `path` (the server-side file path) and `url` (the public URL to access
the file), e.g. `const { path, url } = await upload(file)`.
apply_default_css: bool
default `= True`
If True, default Gradio CSS styles will be applied to the HTML component.
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.
show_label: bool
default `= False`
If True, the label will be displayed. If False, the label will be hidden.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
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 a | Initialization | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
s 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 | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
min_height: int | None
default `= None`
The minimum height of the component, specified in pixels if a number is
passed, or in CSS units if a string is passed. If HTML content exceeds the
height, the component will expand to fit the content.
max_height: int | None
default `= None`
The maximum height of the component, specified in pixels if a number is
passed, or in CSS units if a string is passed. If content exceeds the height,
the component will scroll.
container: bool
default `= False`
If True, the HTML component will be displayed in a container. Default is
False.
padding: bool
default `= False`
If True, the HTML component will have a certain padding (set by the `--block-
padding` CSS variable) in all directions. Default | Initialization | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
ner. Default is
False.
padding: bool
default `= False`
If True, the HTML component will have a certain padding (set by the `--block-
padding` CSS variable) in all directions. Default is False.
autoscroll: bool
default `= False`
If True, will automatically scroll to the bottom of the component when the
content changes, unless the user has scrolled up. If False, will not scroll to
the bottom when the content changes.
buttons: list[Button] | None
default `= None`
A list of gr.Button() instances to show in the top right corner of the
component. Custom buttons will appear in the toolbar with their configured
icon and/or label, and clicking them will trigger any .click() events
registered on the button.
server_functions: list[Callable] | None
default `= None`
A list of Python functions that can be called from `js_on_load` via the
`server` object. For example, if you pass `server_functions=[my_func]`, you
can call `server.my_func(arg1, arg2)` in your `js_on_load` code. Each function
becomes an async method that sends the call to the Python backend and returns
the result.
props: Any
Additional keyword arguments to pass into the HTML and CSS templates for
rendering.
| Initialization | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
Shortcuts
gradio.HTML
Interface String Shortcut `"html"`
Initialization Uses default values
| Shortcuts | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
super_html
| Demos | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
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 HTML component supports the following event listeners. Each event listener
takes the same parameters, which are listed in the Event Parameters table
below.
Listeners
HTML.change(fn, ···)
Triggered when the value of the HTML 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.
HTML.input(fn, ···)
This listener is triggered when the user changes the value of the HTML.
HTML.click(fn, ···)
Triggered when the HTML is clicked.
HTML.double_click(fn, ···)
Triggered when the HTML is double clicked.
HTML.submit(fn, ···)
This listener is triggered when the user presses the Enter key while the HTML
is focused.
HTML.stop(fn, ···)
This listener is triggered when the user reaches the end of the media playing
in the HTML.
HTML.edit(fn, ···)
This listener is triggered when the user edits the HTML (e.g. image) using the
built-in editor.
HTML.clear(fn, ···)
This listener is triggered when the user clears the HTML using the clear
button for the component.
HTML.play(fn, ···)
This listener is triggered when the user plays the media in the HTML.
HTML.pause(fn, ···)
This listener is triggered when the media in the HTML stops for any reason.
HTML.end(fn, ···)
This listener is triggered when the user reaches the end of the media playing
in the HTML.
HTML.start_recording(fn, ···)
This listener is triggered when the user starts recordi | Event Listeners | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
, ···)
This listener is triggered when the user reaches the end of the media playing
in the HTML.
HTML.start_recording(fn, ···)
This listener is triggered when the user starts recording with the HTML.
HTML.pause_recording(fn, ···)
This listener is triggered when the user pauses recording with the HTML.
HTML.stop_recording(fn, ···)
This listener is triggered when the user stops recording with the HTML.
HTML.focus(fn, ···)
This listener is triggered when the HTML is focused.
HTML.blur(fn, ···)
This listener is triggered when the HTML is unfocused/blurred.
HTML.upload(fn, ···)
This listener is triggered when the user uploads a file into the HTML.
HTML.release(fn, ···)
This listener is triggered when the user releases the mouse on this HTML.
HTML.select(fn, ···)
Event listener for when the user selects or deselects the HTML. Uses event
data gradio.SelectData to carry `value` referring to the label of the HTML,
and `selected` to refer to state of the HTML. See
<https://www.gradio.app/main/docs/gradio/eventdata> for more details.
HTML.stream(fn, ···)
This listener is triggered when the user streams the HTML.
HTML.like(fn, ···)
This listener is triggered when the user likes/dislikes from within the HTML.
This event has EventData of type gradio.LikeData that carries information,
accessible through LikeData.index and LikeData.value. See EventData
documentation on how to use this event data.
HTML.example_select(fn, ···)
This listener is triggered when the user clicks on an example from within the
HTML. This event has SelectData of type gradio.SelectData that carries
information, accessible through SelectData.index and SelectData.value. See
SelectData documentation on how to use this event data.
HTML.option_select(fn, ···)
This listener is triggered when the user clicks on an option from | Event Listeners | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
ta.index and SelectData.value. See
SelectData documentation on how to use this event data.
HTML.option_select(fn, ···)
This listener is triggered when the user clicks on an option from within the
HTML. This event has SelectData of type gradio.SelectData that carries
information, accessible through SelectData.index and SelectData.value. See
SelectData documentation on how to use this event data.
HTML.load(fn, ···)
This listener is triggered when the HTML initially loads in the browser.
HTML.key_up(fn, ···)
This listener is triggered when the user presses a key while the HTML is
focused.
HTML.apply(fn, ···)
This listener is triggered when the user applies changes to the HTML through
an integrated UI action.
HTML.delete(fn, ···)
This listener is triggered when the user deletes and item from the HTML. Uses
event data gradio.DeletedFileData to carry `value` referring to the file that
was deleted as an instance of FileData. See EventData documentation on how to
use this event data
HTML.tick(fn, ···)
This listener is triggered at regular intervals defined by the HTML.
HTML.undo(fn, ···)
This listener is triggered when the user clicks the undo button in the chatbot
message.
HTML.retry(fn, ···)
This listener is triggered when the user clicks the retry button in the
chatbot message.
HTML.expand(fn, ···)
This listener is triggered when the HTML is expanded.
HTML.collapse(fn, ···)
This listener is triggered when the HTML is collapsed.
HTML.download(fn, ···)
This listener is triggered when the user downloads a file from the HTML. Uses
event data gradio.DownloadData to carry information about the downloaded file
as a FileData object. See EventData documentation on how to use this event
data
HTML.copy(fn, ···)
This listener is triggered when the user copies content from the HTML. Uses
event d | Event Listeners | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
e
as a FileData object. See EventData documentation on how to use this event
data
HTML.copy(fn, ···)
This listener is triggered when the user copies content from the HTML. Uses
event data gradio.CopyData to carry information about the copied content. See
EventData documentation on how to use this event data
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
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 Tru | Event Listeners | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
he 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 | Event Listeners | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
g '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 conc | Event Listeners | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
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.
[Custom HTML Components](../../guides/custom-HTML-components/)[Custom CSS And
JS](../../guides/custom-CSS-and-JS/)
| Event Listeners | https://gradio.app/docs/gradio/html | Gradio - Html Docs |
Used to display arbitrary JSON output prettily. As this component does not
accept user input, it is rarely used as an input component.
| Description | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
**Using JSON as an input component.**
How JSON will pass its value to your function:
Type: `dict | list | None`
Passes the JSON value as a `dict` or `list` depending on the value.
Example Code
import gradio as gr
def predict(
value: dict | list | None
):
process value from the JSON component
return "prediction"
interface = gr.Interface(predict, gr.JSON(), gr.Textbox())
interface.launch()
**Using JSON as an output component**
How JSON expects you to return a value:
Type: `dict | list | str | None`
Expects a valid JSON `str` \-- or a `list` or `dict` that can be serialized to
a JSON string. The `list` or `dict` value can contain numpy arrays.
Example Code
import gradio as gr
def predict(text) -> dict | list | str | None
process value to return to the JSON component
return value
interface = gr.Interface(predict, gr.Textbox(), gr.JSON())
interface.launch()
| Behavior | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
Parameters ▼
value: str | dict | list | Callable | None
default `= None`
Default value as a valid JSON `str` -- or a `list` or `dict` that can be
serialized to a JSON string. If a function is provided, the function will be
called each time the app loads to set the initial value of this component.
label: str | I18nData | None
default `= None`
the label for this component. Appears above the component and is also used as
the header if there are a table of examples for this component. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
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.
show_label: bool | None
default `= None`
if True, will display label.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
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
default `= 160`
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.
| Initialization | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
rap 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.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
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 | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
open: bool
default `= False`
If True, all JSON nodes will be expanded when rendered. By default, node
levels deeper than 3 are collapsed.
show_indices: bool
default `= False`
Whether to show numerical indices when displaying the elements of a list
within the JSON object.
| Initialization | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
levels deeper than 3 are collapsed.
show_indices: bool
default `= False`
Whether to show numerical indices when displaying the elements of a list
within the JSON object.
height: int | str | None
default `= None`
Height of the JSON component in pixels if a number is passed, or in CSS units
if a string is passed. Overflow will be scrollable. If None, the height will
be automatically adjusted to fit the content.
max_height: int | str | None
default `= 500`
min_height: int | str | None
default `= None`
buttons: list[Literal['copy'] | Button] | None
default `= None`
A list of buttons to show for the component. Valid options are "copy" or a
gr.Button() instance. The "copy" button allows users to copy the JSON to the
clipboard. Custom gr.Button() instances will appear in the toolbar with their
configured icon and/or label, and clicking them will trigger any .click()
events registered on the button. By default, the copy button is shown.
| Initialization | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
Shortcuts
gradio.JSON
Interface String Shortcut `"json"`
Initialization Uses default values
| Shortcuts | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
zip_to_jsonblocks_xray
| Demos | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
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 JSON component supports the following event listeners. Each event listener
takes the same parameters, which are listed in the Event Parameters table
below.
Listeners
JSON.change(fn, ···)
Triggered when the value of the JSON 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
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.
| Event Listeners | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
PI 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: | Event Listeners | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
he 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 | Event Listeners | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
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.
| Event Listeners | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
lidate()` for each input value.
| Event Listeners | https://gradio.app/docs/gradio/json | Gradio - Json Docs |
Creates a video component that can be used to upload/record videos (as an
input) or display videos (as an output). For the video to be playable in the
browser it must have a compatible container and codec combination. Allowed
combinations are .mp4 with h264 codec, .ogg with theora codec, and .webm with
vp9 codec. If the component detects that the output video would not be
playable in the browser it will attempt to convert it to a playable mp4 video.
If the conversion fails, the original video is returned.
| Description | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
**Using Video as an input component.**
How Video will pass its value to your function:
Type: `str | None`
Passes the uploaded video as a `str` filepath or URL whose extension can be
modified by `format`.
Example Code
import gradio as gr
def predict(
value: str | None
):
process value from the Video component
return "prediction"
interface = gr.Interface(predict, gr.Video(), gr.Textbox())
interface.launch()
**Using Video as an output component**
How Video expects you to return a value:
Type: `str | Path | None`
Expects one of either:
* a `str` or `pathlib.Path` filepath to a video which is displayed
* a `Tuple[str | pathlib.Path, str | pathlib.Path | None]` where the first element is a filepath to a video and the second element is an optional filepath to a subtitle file.
Example Code
import gradio as gr
def predict(text) -> str | Path | None
process value to return to the Video component
return value
interface = gr.Interface(predict, gr.Textbox(), gr.Video())
interface.launch()
| Behavior | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
Parameters ▼
value: str | Path | Callable | None
default `= None`
path or URL for the default value that Video component is going to take. Or
can be callable, in which case the function will be called whenever the app
loads to set the initial value of the component.
format: str | None
default `= None`
the file extension with which to save video, such as 'avi' or 'mp4'. This
parameter applies both when this component is used as an input to determine
which file format to convert user-provided video to, and when this component
is used as an output to determine the format of video returned to the user. If
None, no file format conversion is done and the video is kept as is. Use 'mp4'
to ensure browser playability.
sources: list[Literal['upload', 'webcam']] | Literal['upload', 'webcam'] | None
default `= None`
list of sources permitted for video. "upload" creates a box where user can
drop a video file, "webcam" allows user to record a video from their webcam.
If None, defaults to both ["upload, "webcam"].
height: int | str | None
default `= None`
The height of the component, specified in pixels if a number is passed, or in
CSS units if a string is passed. This has no effect on the preprocessed video
file, but will affect the displayed video.
width: int | str | None
default `= None`
The width of the component, specified in pixels if a number is passed, or in
CSS units if a string is passed. This has no effect on the preprocessed video
file, but will affect the displayed video.
label: str | I18nData | None
default `= None`
the label for this component. Appears above the component and is also used as
the header if there are a table of examples for this component. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
every: Timer | float | None
default `= None`
continously calls `value` to reca | Initialization | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
nd
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
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.
show_label: bool | None
default `= None`
if True, will display label.
container: bool
default `= True`
if True, will place the component in a container - providing some extra
padding around the border.
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
default `= 160`
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 | None
default `= None`
if True, will allow users to upload a video; if False, can only be used to
display videos. If not provided, this is inferred based on whether the
component is used as an input or output.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
elem_id: str | None
default `= None`
an optional string that i | Initialization | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
e hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
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 | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
webcam_options: WebcamOptions | None
default `= None`
A `gr.WebcamOptions` instance that allows developers to specify custom media
constraints for the webcam stream. This parameter provides flexibility to
control the video stream's properties, such as resolution and front or rear
camera on mobile devices. See $demo/webcam_constraints
include_audio: bool | None
default `= None`
whether the component should record/retain the audio track for a video. By
default, audio is excluded for webcam videos and included for uploaded videos.
autoplay: bool
d | Initialization | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
lt `= None`
whether the component should record/retain the audio track for a video. By
default, audio is excluded for webcam videos and included for uploaded videos.
autoplay: bool
default `= False`
whether to automatically play the video when the component is used as an
output. Note: browsers will not autoplay video files if the user has not
interacted with the page yet.
buttons: list[Literal['download', 'share'] | Button] | None
default `= None`
A list of buttons to show in the top right corner of the component. Valid
options are "download", "share", or a gr.Button() instance. The "download"
button allows the user to save the video to their device. The "share" button
allows the user to share the video via Hugging Face Spaces Discussions. Custom
gr.Button() instances will appear in the toolbar with their configured icon
and/or label, and clicking them will trigger any .click() events registered on
the button. By default, no buttons are shown if the component is interactive
and both buttons are shown if the component is not interactive.
loop: bool
default `= False`
if True, the video will loop when it reaches the end and continue playing from
the beginning.
streaming: bool
default `= False`
when used set as an output, takes video chunks yielded from the backend and
combines them into one streaming video output. Each chunk should be a video
file with a .ts extension using an h.264 encoding. Mp4 files are also accepted
but they will be converted to h.264 encoding.
watermark: WatermarkOptions | None
default `= None`
A `gr.WatermarkOptions` instance that includes an image file and position to
be used as a watermark on the video. The image is not scaled and is displayed
on the provided position on the video. Valid formats for the image are: jpeg,
png.
subtitles: str | Path | list[dict[str, Any]] | None
default `= None`
A subtitle file (srt, vtt, or json) for the v | Initialization | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
position on the video. Valid formats for the image are: jpeg,
png.
subtitles: str | Path | list[dict[str, Any]] | None
default `= None`
A subtitle file (srt, vtt, or json) for the video, or a list of subtitle
dictionaries in the format [{"text": str, "timestamp": [start, end]}] where
timestamps are in seconds. JSON files should contain an array of subtitle
objects.
playback_position: float
default `= 0`
The starting playback position in seconds. This value is also updated as the
video plays, reflecting the current playback position.
| Initialization | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
Shortcuts
gradio.Video
Interface String Shortcut `"video"`
Initialization Uses default values
gradio.PlayableVideo
Interface String Shortcut `"playablevideo"`
Initialization Uses format="mp4"
| Shortcuts | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
video_identity_2
| Demos | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
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 Video component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listeners
Video.change(fn, ···)
Triggered when the value of the Video 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.
Video.clear(fn, ···)
This listener is triggered when the user clears the Video using the clear
button for the component.
Video.start_recording(fn, ···)
This listener is triggered when the user starts recording with the Video.
Video.stop_recording(fn, ···)
This listener is triggered when the user stops recording with the Video.
Video.stop(fn, ···)
This listener is triggered when the user reaches the end of the media playing
in the Video.
Video.play(fn, ···)
This listener is triggered when the user plays the media in the Video.
Video.pause(fn, ···)
This listener is triggered when the media in the Video stops for any reason.
Video.end(fn, ···)
This listener is triggered when the user reaches the end of the media playing
in the Video.
Video.upload(fn, ···)
This listener is triggered when the user uploads a file into the Video.
Video.input(fn, ···)
This listener is triggered when the user changes the value of the Video.
Event Parameters
Parameters ▼
fn: Callable | None | Literal['decorator']
default `= "decorator"`
the function to call when this | Event Listeners | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
d when the user changes the value of the Video.
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
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 runti | Event Listeners | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
s: 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, | Event Listeners | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
ict[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 c | Event Listeners | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
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.
| Event Listeners | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
Helper Classes | https://gradio.app/docs/gradio/video | Gradio - Video Docs | |
gradio.WebcamOptions(···)
Description
A dataclass for specifying options for the webcam tool in the ImageEditor
component. An instance of this class can be passed to the `webcam_options`
parameter of `gr.ImageEditor`.
Initialization
Parameters ▼
mirror: bool
default `= True`
If True, the webcam will be mirrored.
constraints: dict[str, Any] | None
default `= None`
A dictionary of constraints for the webcam.
| Webcam Options | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
Validates that the audio length is within the specified min and max length (in
seconds). You can use this to construct a validator that will check if the
user-provided audio is either too short or too long.
import gradio as gr
demo = gr.Interface(
lambda x: x,
inputs="video",
outputs="video",
validator=lambda video: gr.validators.is_video_correct_length(video, min_length=1, max_length=5)
)
demo.launch()
Initialization
Parameters ▼
video: <class 'str'>
The path to the video file.
min_length: float | None
Minimum length of video in seconds. If None, no minimum length check is
performed.
max_length: float | None
Maximum length of video in seconds. If None, no maximum length check is
performed.
[Streaming Inputs](../../guides/streaming-inputs/)[Streaming
Outputs](../../guides/streaming-outputs/)[Object Detection From
Video](../../guides/object-detection-from-video/)
| is_video_correct_length | https://gradio.app/docs/gradio/video | Gradio - Video Docs |
Set the static paths to be served by the gradio app.
Static files are are served directly from the file system instead of being
copied. They are served to users with The Content-Disposition HTTP header set
to "inline" when sending these files to users. This indicates that the file
should be displayed directly in the browser window if possible. This function
is useful when you want to serve files that you know will not be modified
during the lifetime of the gradio app (like files used in gr.Examples). By
setting static paths, your app will launch faster and it will consume less
disk space. Calling this function will set the static paths for all gradio
applications defined in the same interpreter session until it is called again
or the session ends.
| Description | https://gradio.app/docs/gradio/set_static_paths | Gradio - Set_Static_Paths Docs |
import gradio as gr
Paths can be a list of strings or pathlib.Path objects
corresponding to filenames or directories.
gr.set_static_paths(paths=["test/test_files/"])
The example files and the default value of the input
will not be copied to the gradio cache and will be served directly.
demo = gr.Interface(
lambda s: s.rotate(45),
gr.Image(value="test/test_files/cheetah1.jpg", type="pil"),
gr.Image(),
examples=["test/test_files/bus.png"],
)
demo.launch()
| Example Usage | https://gradio.app/docs/gradio/set_static_paths | Gradio - Set_Static_Paths Docs |
Parameters ▼
paths: str | pathlib.Path | list[str | pathlib.Path]
filepath or list of filepaths or directory names to be served by the gradio
app. If it is a directory name, ALL files located within that directory will
be considered static and not moved to the gradio cache. This also means that
ALL files in that directory will be accessible over the network.
[File Access](../../guides/file-access)
| Initialization | https://gradio.app/docs/gradio/set_static_paths | Gradio - Set_Static_Paths Docs |
Creates an image component that, as an input, can be used to upload and
edit images using simple editing tools such as brushes, strokes, cropping, and
layers. Or, as an output, this component can be used to display images.
| Description | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
**Using ImageEditor as an input component.**
How ImageEditor will pass its value to your function:
Type: `EditorValue | None`
Passes the uploaded images as an instance of EditorValue, which is just a
`dict` with keys: 'background', 'layers', and 'composite'.
* The values corresponding to 'background' and 'composite' are images
* the value corresponding to 'layers' is a `list` of images.
Depending on the `type` parameter, the images are of type:
* `PIL.Image`
* `np.array`
* `str` filepath.
Example Code
import gradio as gr
def predict(
value: EditorValue | None
):
process value from the ImageEditor component
return "prediction"
interface = gr.Interface(predict, gr.ImageEditor(), gr.Textbox())
interface.launch()
**Using ImageEditor as an output component**
How ImageEditor expects you to return a value:
Type: `EditorValue | ImageType | None`
Expects a EditorValue, which is just a dictionary with keys: 'background',
'layers', and 'composite'.
* The values corresponding to 'background' and 'composite' should be images or None
* the value corresponding to `layers` should be a list of images.
Images can be of type:
* `PIL.Image`
* `np.array`
* `str` filepath/URL
Or, the value can be simply a single image (`ImageType`), in which case it
will be used as the background.
Example Code
import gradio as gr
def predict(text) -> EditorValue | ImageType | None
process value to return to the ImageEditor component
return value
interface = gr.Interface(predict, gr.Textbox(), gr.ImageEditor())
interface.launch()
| Behavior | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
Parameters ▼
value: EditorValue | ImageType | None
default `= None`
Optional initial image(s) to populate the image editor. Should be a dictionary
with keys: `background`, `layers`, and `composite`. The values corresponding
to `background` and `composite` should be images or None, while `layers`
should be a list of images. Images can be of type PIL.Image, np.array, or str
filepath/URL. Or, the value can be a callable, in which case the function will
be called whenever the app loads to set the initial value of the component.
height: int | str | None
default `= None`
The height of the component, specified in pixels if a number is passed, or in
CSS units if a string is passed. This has no effect on the preprocessed image
files or numpy arrays, but will affect the displayed images. Beware of
conflicting values with the canvas_size parameter. If the canvas_size is
larger than the height, the editing canvas will not fit in the component.
width: int | str | None
default `= None`
The width of the component, specified in pixels if a number is passed, or in
CSS units if a string is passed. This has no effect on the preprocessed image
files or numpy arrays, but will affect the displayed images. Beware of
conflicting values with the canvas_size parameter. If the canvas_size is
larger than the height, the editing canvas will not fit in the component.
image_mode: Literal['1', 'L', 'P', 'RGB', 'RGBA', 'CMYK', 'YCbCr', 'LAB', 'HSV', 'I', 'F']
default `= "RGBA"`
"RGB" if color, or "L" if black and white. See
https://pillow.readthedocs.io/en/stable/handbook/concepts.html for other
supported image modes and their meaning.
sources: Iterable[Literal['upload', 'webcam', 'clipboard']] | Literal['upload', 'webcam', 'clipboard'] | None
default `= ('upload', 'webcam', 'clipboard')`
List of sources that can be used to set the background image. "upload" creates
a box where user can drop an image file, "we | Initialization | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
webcam', 'clipboard'] | None
default `= ('upload', 'webcam', 'clipboard')`
List of sources that can be used to set the background image. "upload" creates
a box where user can drop an image file, "webcam" allows user to take snapshot
from their webcam, "clipboard" allows users to paste an image from the
clipboard.
type: Literal['numpy', 'pil', 'filepath']
default `= "numpy"`
The format the images are converted to before being passed into the prediction
function. "numpy" converts the images to numpy arrays with shape (height,
width, 3) and values from 0 to 255, "pil" converts the images to PIL image
objects, "filepath" passes images as str filepaths to temporary copies of the
images.
label: str | I18nData | None
default `= None`
the label for this component. Appears above the component and is also used as
the header if there are a table of examples for this component. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
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.
show_label: bool | None
default `= None`
if True, will display label.
buttons: list[Literal['download', 'share', 'fullscreen']] | None
default `= None`
A list of buttons to show in the corner of the component. Valid options are
"download" to download the image, "share" to share to Hugging Face Spaces
Discussions, and "fullscreen" to view in fullscreen mode. By default, all
buttons are shown.
| Initialization | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
nt. Valid options are
"download" to download the image, "share" to share to Hugging Face Spaces
Discussions, and "fullscreen" to view in fullscreen mode. By default, all
buttons are shown.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
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
default `= 160`
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 | None
default `= None`
if True, will allow users to upload and edit an image; if False, can only be
used to display images. If not provided, this is inferred based on whether the
component is used as an input or output.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
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.
| Initialization | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
r: 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 | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
placeholder: str | None
default `= None`
Custom text for the upload area. Overrides default upload messages when
provided. Accepts new lines and `` to designate a heading.
transforms: Iterable[Literal['crop', 'resize']] | None
default `= ('crop', 'resize')`
The transforms tools to make available to users. "crop" allows the user to
crop the image.
eraser: Eraser | None | Literal[False]
default `= None`
The options for the eraser tool in the image editor. Should be an instance of
the `gr.Eraser` class, or None to use the default settings. Can also be False
to hide the eraser tool. See `gr.Eraser` docs.
brush: Brush | None | Literal[False]
default `= None`
The options for the brush tool in the image editor. Should be an instance of
the `gr.Brush` class, or None to use the default settings. Can also be False
to hide the brush tool, which will also hide the eraser tool. See `gr.Brush`
docs.
format: str
default `= "webp"`
Format to save image if it does not already have a valid format (e.g. if the
image is being returned to | Initialization | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
also hide the eraser tool. See `gr.Brush`
docs.
format: str
default `= "webp"`
Format to save image if it does not already have a valid format (e.g. if the
image is being returned to the frontend as a numpy array or PIL Image). The
format should be supported by the PIL library. This parameter has no effect on
SVG files.
layers: bool | LayerOptions
default `= True`
The options for the layer tool in the image editor. Can be a boolean or an
instance of the `gr.LayerOptions` class. If True, will allow users to add
layers to the image. If False, the layers option will be hidden. If an
instance of `gr.LayerOptions`, it will be used to configure the layer tool.
See `gr.LayerOptions` docs.
canvas_size: tuple[int, int]
default `= (800, 800)`
The initial size of the canvas in pixels. The first value is the width and the
second value is the height. If `fixed_canvas` is `True`, uploaded images will
be rescaled to fit the canvas size while preserving the aspect ratio.
Otherwise, the canvas size will change to match the size of an uploaded image.
fixed_canvas: bool
default `= False`
If True, the canvas size will not change based on the size of the background
image and the image will be rescaled to fit (while preserving the aspect
ratio) and placed in the center of the canvas.
webcam_options: WebcamOptions | None
default `= None`
The options for the webcam tool in the image editor. Can be an instance of the
`gr.WebcamOptions` class, or None to use the default settings. See
`gr.WebcamOptions` docs.
| Initialization | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
Shortcuts
gradio.ImageEditor
Interface String Shortcut `"imageeditor"`
Initialization Uses default values
gradio.Sketchpad
Interface String Shortcut `"sketchpad"`
Initialization Uses sources=(), brush=Brush(colors=["000000"],
color_mode="fixed")
gradio.Paint
Interface String Shortcut `"paint"`
Initialization Uses sources=()
gradio.ImageMask
Interface String Shortcut `"imagemask"`
Initialization Uses brush=Brush(colors=["000000"], color_mode="fixed")
| Shortcuts | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
image_editor
| Demos | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
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 ImageEditor component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listeners
ImageEditor.clear(fn, ···)
This listener is triggered when the user clears the ImageEditor using the
clear button for the component.
ImageEditor.change(fn, ···)
Triggered when the value of the ImageEditor 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.
ImageEditor.input(fn, ···)
This listener is triggered when the user changes the value of the ImageEditor.
ImageEditor.select(fn, ···)
Event listener for when the user selects or deselects the ImageEditor. Uses
event data gradio.SelectData to carry `value` referring to the label of the
ImageEditor, and `selected` to refer to state of the ImageEditor. See
<https://www.gradio.app/main/docs/gradio/eventdata> for more details.
ImageEditor.upload(fn, ···)
This listener is triggered when the user uploads a file into the ImageEditor.
ImageEditor.apply(fn, ···)
This listener is triggered when the user applies changes to the ImageEditor
through an integrated UI action.
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 | Event Listeners | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
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 | Event Listeners | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
nt 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
function | Event Listeners | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
ll 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".
| Event Listeners | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
en 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.
| Event Listeners | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
Helper Classes | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs | |
gradio.Brush(···)
Description
A dataclass for specifying options for the brush tool in the ImageEditor
component. An instance of this class can be passed to the `brush` parameter of
`gr.ImageEditor`.
Initialization
Parameters ▼
default_size: int | Literal['auto']
default `= "auto"`
The default radius, in pixels, of the brush tool. Defaults to "auto" in which
case the radius is automatically determined based on the size of the image
(generally 1/50th of smaller dimension).
colors: list[str | tuple[str, float]] | str | tuple[str, float] | None
default `= None`
A list of colors to make available to the user when using the brush. Defaults
to a list of 5 colors.
default_color: str | tuple[str, float] | None
default `= None`
The default color of the brush. Defaults to the first color in the `colors`
list.
color_mode: Literal['fixed', 'defaults']
default `= "defaults"`
If set to "fixed", user can only select from among the colors in `colors`. If
"defaults", the colors in `colors` are provided as a default palette, but the
user can also select any color using a color picker.
| Brush | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
gradio.Eraser(···)
Description
A dataclass for specifying options for the eraser tool in the ImageEditor
component. An instance of this class can be passed to the `eraser` parameter
of `gr.ImageEditor`.
Initialization
Parameters ▼
default_size: int | Literal['auto']
default `= "auto"`
The default radius, in pixels, of the eraser tool. Defaults to "auto" in which
case the radius is automatically determined based on the size of the image
(generally 1/50th of smaller dimension).
| Eraser | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
gradio.LayerOptions(···)
Description
A dataclass for specifying options for the layer tool in the ImageEditor
component. An instance of this class can be passed to the `layers` parameter
of `gr.ImageEditor`.
Initialization
Parameters ▼
allow_additional_layers: bool
default `= True`
If True, users can add additional layers to the image. If False, the add layer
button will not be shown.
layers: list[str] | None
default `= None`
A list of layers to make available to the user when using the layer tool. One
layer must be provided, if the length of the list is 0 then a layer will be
generated automatically.
disabled: bool
default `= False`
| Layer Options | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
gradio.WebcamOptions(···)
Description
A dataclass for specifying options for the webcam tool in the ImageEditor
component. An instance of this class can be passed to the `webcam_options`
parameter of `gr.ImageEditor`.
Initialization
Parameters ▼
mirror: bool
default `= True`
If True, the webcam will be mirrored.
constraints: dict[str, Any] | None
default `= None`
A dictionary of constraints for the webcam.
| Webcam Options | https://gradio.app/docs/gradio/imageeditor | Gradio - Imageeditor Docs |
A Gradio request object that can be used to access the request headers,
cookies, query parameters and other information about the request from within
the prediction function. The class is a thin wrapper around the
fastapi.Request class. Attributes of this class include: `headers`, `client`,
`query_params`, `session_hash`, and `path_params`. If auth is enabled, the
`username` attribute can be used to get the logged in user. In some
environments, the dict-like attributes (e.g. `requests.headers`,
`requests.query_params`) of this class are automatically converted to
dictionaries, so we recommend converting them to dictionaries before accessing
attributes for consistent behavior in different environments.
| Description | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
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))
print("Session hash:", request.session_hash)
return text
io = gr.Interface(echo, "textbox", "textbox").launch()
| Example Usage | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
Parameters ▼
request: fastapi.Request | None
default `= None`
A fastapi.Request
username: str | None
default `= None`
The username of the logged in user (if auth is enabled)
session_hash: str | None
default `= None`
The session hash of the current session. It is unique for each page load.
| Initialization | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
request_ip_headers
| Demos | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
Displays text that contains spans that are highlighted by category or
numerical value.
| Description | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
**Using HighlightedText as an input component.**
How HighlightedText will pass its value to your function:
Type: `list[tuple[str, str | float | None]] | None`
Passes the value as a list of tuples: `list[tuple]`. Each `tuple` consists of:
* a `str` substring of the text (so the entire text is included)
* a `str | float | None` label, which is the category or confidence of that substring.
Example Code
import gradio as gr
def predict(
value: list[tuple[str, str | float | None]] | None
):
process value from the HighlightedText component
return "prediction"
interface = gr.Interface(predict, gr.HighlightedText(), gr.Textbox())
interface.launch()
**Using HighlightedText as an output component**
How HighlightedText expects you to return a value:
Type: `list[tuple[str, str | float | None]] | dict | None`
Expects either of:
* a list of (word, category) tuples
* a dictionary of two keys: "text", and "entities".
* "entities" itself is a list of dictionaries, each of which have the keys: "entity" (or "entity_group"), "start", and "end"
Example Code
import gradio as gr
def predict(text) -> list[tuple[str, str | float | None]] | dict | None
process value to return to the HighlightedText component
return value
interface = gr.Interface(predict, gr.Textbox(), gr.HighlightedText())
interface.launch()
| Behavior | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
Parameters ▼
value: list[tuple[str, str | float | None]] | dict | Callable | None
default `= None`
Default value to show. If a function is provided, the function will be called
each time the app loads to set the initial value of this component.
color_map: dict[str, str] | None
default `= None`
A dictionary mapping labels to colors. The colors may be specified as hex
codes or by their names. For example: {"person": "red", "location": "FFEE22"}
show_legend: bool
default `= False`
whether to show span categories in a separate legend or inline.
show_inline_category: bool
default `= True`
If False, will not display span category label. Only applies if
show_legend=False and interactive=False.
combine_adjacent: bool
default `= False`
If True, will merge the labels of adjacent tokens belonging to the same
category.
adjacent_separator: str
default `= ""`
Specifies the separator to be used between tokens if combine_adjacent is True.
show_whitespaces: bool
default `= True`
If False, leading and trailing whitespace of each token will be stripped
before display.
label: str | I18nData | None
default `= None`
the label for this component. Appears above the component and is also used as
the header if there are a table of examples for this component. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
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 r | Initialization | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
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.
show_label: bool | None
default `= None`
if True, will display label.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
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
default `= 160`
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.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
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 | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same k | Initialization | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
e intention is to assign event listeners now but render the
component later.
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
interactive: bool | None
default `= None`
If True, the component will be editable, and allow user to select spans of
text and label them.
rtl: bool
default `= False`
If True, will display the text in right-to-left direction, and the labels in
the legend will also be aligned to the right.
buttons: list[Button] | None
default `= None`
A list of gr.Button() instances to show in the top right corner of the
component. Custom buttons will appear in the toolbar with their configured
icon and/or label, and clicking them will trigger any .click() events
registered on the button.
| Initialization | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
Shortcuts
gradio.HighlightedText
Interface String Shortcut `"highlightedtext"`
Initialization Uses default values
| Shortcuts | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
diff_texts
| Demos | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
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 HighlightedText component supports the following event listeners. Each
event listener takes the same parameters, which are listed in the Event
Parameters table below.
Listeners
HighlightedText.change(fn, ···)
Triggered when the value of the HighlightedText 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.
HighlightedText.select(fn, ···)
Event listener for when the user selects or deselects the HighlightedText.
Uses event data gradio.SelectData to carry `value` referring to the label of
the HighlightedText, and `selected` to refer to state of the HighlightedText.
See <https://www.gradio.app/main/docs/gradio/eventdata> for more details.
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.componen | Event Listeners | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
puts,
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 | Event Listeners | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
l 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] | | Event Listeners | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
llowed 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 execut | Event Listeners | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
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.
[Named Entity Recognition](../../guides/named-entity-recognition/)
| Event Listeners | https://gradio.app/docs/gradio/highlightedtext | Gradio - Highlightedtext Docs |
Creates a set of checkboxes. Can be used as an input to pass a set of
values to a function or as an output to display values, a subset of which are
selected.
| Description | https://gradio.app/docs/gradio/checkboxgroup | Gradio - Checkboxgroup Docs |
**Using CheckboxGroup as an input component.**
How CheckboxGroup will pass its value to your function:
Type: `list[str | int | float] | list[int | None]`
Passes the list of checked checkboxes as a `list[str | int | float]` or their indices as a `list[int]` into the function, depending on `type`.
Example Code
import gradio as gr
def predict(
value: list[str | int | float] | list[int | None]
):
process value from the CheckboxGroup component
return "prediction"
interface = gr.Interface(predict, gr.CheckboxGroup(), gr.Textbox())
interface.launch()
**Using CheckboxGroup as an output component**
How CheckboxGroup expects you to return a value:
Type: `list[str | int | float] | str | int | float | None`
Expects a `list[str | int | float]` of values or a single `str | int | float` value, the checkboxes with these values are checked.
Example Code
import gradio as gr
def predict(text) -> list[str | int | float] | str | int | float | None
process value to return to the CheckboxGroup component
return value
interface = gr.Interface(predict, gr.Textbox(), gr.CheckboxGroup())
interface.launch()
| Behavior | https://gradio.app/docs/gradio/checkboxgroup | Gradio - Checkboxgroup Docs |
Parameters ▼
choices: list[str | int | float | tuple[str, str | int | float]] | None
default `= None`
A list of string or numeric options to select from. An option can also be a
tuple of the form (name, value), where name is the displayed name of the
checkbox button and value is the value to be passed to the function, or
returned by the function.
value: list[str | float | int] | str | float | int | Callable | None
default `= None`
Default selected list of options. If a single choice is selected, it can be
passed in as a string or numeric type. If a function is provided, the function
will be called each time the app loads to set the initial value of this
component.
type: Literal['value', 'index']
default `= "value"`
Type of value to be returned by component. "value" returns the list of strings
of the choices selected, "index" returns the list of indices of the choices
selected.
label: str | I18nData | None
default `= None`
the label for this component, displayed above the component if `show_label` is
`True` and is also used as the header if there are a table of examples for
this component. If None and used in a `gr.Interface`, the label will be the
name of the parameter this component corresponds to.
info: str | I18nData | None
default `= None`
additional component description, appears below the label in smaller font.
Supports markdown / HTML syntax.
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.
| Initialization | https://gradio.app/docs/gradio/checkboxgroup | Gradio - Checkboxgroup Docs |
nt] | 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.
show_label: bool | None
default `= None`
If True, will display label.
show_select_all: bool
default `= False`
If True, will display a select/deselect all checkbox next to the label. Only
available when show_label is True.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
scale: int | None
default `= None`
Relative width compared to adjacent Components in a Row. For example, if
Component A has scale=2, and Component B has scale=1, A will be twice as wide
as B. Should be an integer.
min_width: int
default `= 160`
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 | None
default `= None`
If True, choices in this checkbox group will be checkable; if False, checking
will be disabled. If not provided, this is inferred based on whether the
component is used as an input or output.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
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, | Initialization | https://gradio.app/docs/gradio/checkboxgroup | Gradio - Checkboxgroup Docs |
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 | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
buttons: list[Button] | None
default `= None`
A list of gr.Button() instances to show in the top right corner of the
component. Custom buttons will appear in the toolbar with their configured
icon and/or label, and clicking them will trigger any .click() events
registered on the button.
| Initialization | https://gradio.app/docs/gradio/checkboxgroup | Gradio - Checkboxgroup Docs |
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