EllieKini/Herta
Audio-to-Audio
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This class is a wrapper over the Dataset component and can be used to
create Examples for Blocks / Interfaces. Populates the Dataset component with
examples and assigns event listener so that clicking on an example populates
the input/output components. Optionally handles example caching for fast
inference.
|
Description
|
https://gradio.app/docs/gradio/examples
|
Gradio - Examples Docs
|
Parameters ▼
examples: list[Any] | list[list[Any]] | str
example inputs that can be clicked to populate specific components. Should be
nested list, in which the outer list consists of samples and each inner list
consists of an input corresponding to each input component. A string path to a
directory of examples can also be provided but it should be within the
directory with the python file running the gradio app. If there are multiple
input components and a directory is provided, a log.csv file must be present
in the directory to link corresponding inputs.
inputs: Component | list[Component]
the component or list of components corresponding to the examples
outputs: Component | list[Component] | None
default `= None`
optionally, provide the component or list of components corresponding to the
output of the examples. Required if `cache_examples` is not False.
fn: Callable | None
default `= None`
optionally, provide the function to run to generate the outputs corresponding
to the examples. Required if `cache_examples` is not False. Also required if
`run_on_click` is True.
cache_examples: bool | None
default `= None`
If True, caches examples in the server for fast runtime in examples. If
"lazy", then examples are cached (for all users of the app) after their first
use (by any user of the app). If None, will use the GRADIO_CACHE_EXAMPLES
environment variable, which should be either "true" or "false". In HuggingFace
Spaces, this parameter is True (as long as `fn` and `outputs` are also
provided). The default option otherwise is False. Note that examples are
cached separately from Gradio's queue() so certain features, such as
gr.Progress(), gr.Info(), gr.Warning(), etc. will not be displayed in Gradio's
UI for cached examples.
cache_mode: Literal['eager', 'lazy'] | None
default `= None`
if "lazy", examples are cached after their first use. If "eager", all examples
are
|
Initialization
|
https://gradio.app/docs/gradio/examples
|
Gradio - Examples Docs
|
d in Gradio's
UI for cached examples.
cache_mode: Literal['eager', 'lazy'] | None
default `= None`
if "lazy", examples are cached after their first use. If "eager", all examples
are cached at app launch. If None, will use the GRADIO_CACHE_MODE environment
variable if defined, or default to "eager".
examples_per_page: int
default `= 10`
how many examples to show per page.
label: str | I18nData | None
default `= "Examples"`
the label to use for the examples component (by default, "Examples")
elem_id: str | None
default `= None`
an optional string that is assigned as the id of this component in the HTML
DOM.
run_on_click: bool
default `= False`
if cache_examples is False, clicking on an example does not run the function
when an example is clicked. Set this to True to run the function when an
example is clicked. Has no effect if cache_examples is True.
preprocess: bool
default `= True`
if True, preprocesses the example input before running the prediction function
and caching the output. Only applies if `cache_examples` is not False.
postprocess: bool
default `= True`
if True, postprocesses the example output after running the prediction
function and before caching. Only applies if `cache_examples` is not False.
api_visibility: Literal['public', 'private', 'undocumented']
default `= "undocumented"`
Controls the visibility of the event associated with clicking on the examples.
Can be "public" (shown in API docs and callable), "private" (hidden from API
docs and not callable), or "undocumented" (hidden from API docs but callable).
api_name: str | None
default `= "load_example"`
Defines how the event associated with clicking on the examples 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, an auto-generated name
will be u
|
Initialization
|
https://gradio.app/docs/gradio/examples
|
Gradio - Examples Docs
|
icking on the examples 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, an auto-generated name
will be used.
api_description: str | None | Literal[False]
default `= None`
Description of the event associated with clicking on the examples in the API
docs. Can be a string, None, or False. If set to a string, the endpoint will
be exposed in the API docs with the given 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.
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. Used only if
cache_examples is not False.
example_labels: list[str] | None
default `= None`
A list of labels for each example. If provided, the length of this list should
be the same as the number of examples, and these labels will be used in the UI
instead of rendering the example values.
visible: bool | Literal['hidden']
default `= True`
If False, the examples component will be hidden in the UI.
preload: int | Literal[False]
default `= 0`
If an integer is provided (and examples are being cached eagerly and none of
the input components have a developer-provided `value`), the example at that
index in the examples list will be preloaded when the Gradio app is first
loaded. If False, no example will be preloaded.
|
Initialization
|
https://gradio.app/docs/gradio/examples
|
Gradio - Examples Docs
|
Parameters ▼
dataset: gradio.Dataset
The `gr.Dataset` component corresponding to this Examples object.
load_input_event: gradio.events.Dependency
The Gradio event that populates the input values when the examples are
clicked. You can attach a `.then()` or a `.success()` to this event to trigger
subsequent events to fire after this event.
cache_event: gradio.events.Dependency | None
The Gradio event that populates the cached output values when the examples are
clicked. You can attach a `.then()` or a `.success()` to this event to trigger
subsequent events to fire after this event. This event is `None` if
`cache_examples` if False, and is the same as `load_input_event` if
`cache_examples` is `'lazy'`.
|
Attributes
|
https://gradio.app/docs/gradio/examples
|
Gradio - Examples Docs
|
**Updating Examples**
In this demo, we show how to update the examples by updating the samples of
the underlying dataset. Note that this only works if `cache_examples=False` as
updating the underlying dataset does not update the cache.
import gradio as gr
def update_examples(country):
if country == "USA":
return gr.Dataset(samples=[["Chicago"], ["Little Rock"], ["San Francisco"]])
else:
return gr.Dataset(samples=[["Islamabad"], ["Karachi"], ["Lahore"]])
with gr.Blocks() as demo:
dropdown = gr.Dropdown(label="Country", choices=["USA", "Pakistan"], value="USA")
textbox = gr.Textbox()
examples = gr.Examples([["Chicago"], ["Little Rock"], ["San Francisco"]], textbox)
dropdown.change(update_examples, dropdown, examples.dataset)
demo.launch()
|
Examples
|
https://gradio.app/docs/gradio/examples
|
Gradio - Examples Docs
|
calculator_blocks
|
Demos
|
https://gradio.app/docs/gradio/examples
|
Gradio - Examples Docs
|
This class allows you to pass custom error messages to the user. You can do
so by raising a gr.Error("custom message") anywhere in the code, and when that
line is executed the custom message will appear in a modal on the demo.
You can control for how long the error message is displayed with the
`duration` parameter. If it’s `None`, the message will be displayed forever
until the user closes it. If it’s a number, it will be shown for that many
seconds.
You can also hide the error modal from being shown in the UI by setting
`visible=False`.
Below is a demo of how different values of duration control the error,
info, and warning messages. You can see the code
[here](https://huggingface.co/spaces/freddyaboulton/gradio-error-
duration/blob/244331cf53f6b5fa2fd406ece3bf55c6ccb9f5f2/app.pyL17).
|
Description
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
import gradio as gr
def divide(numerator, denominator):
if denominator == 0:
raise gr.Error("Cannot divide by zero!")
gr.Interface(divide, ["number", "number"], "number").launch()
|
Example Usage
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
Parameters ▼
message: str
default `= "Error raised."`
The error message to be displayed to the user. Can be HTML, which will be
rendered in the modal.
duration: float | None
default `= 10`
The duration in seconds to display the error message. If None or 0, the error
message will be displayed until the user closes it.
visible: bool
default `= True`
Whether the error message should be displayed in the UI.
title: str
default `= "Error"`
The title to be displayed to the user at the top of the error modal.
print_exception: bool
default `= True`
Whether to print traceback of the error to the console when the error is
raised.
|
Initialization
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
calculatorblocks_chained_events
|
Demos
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
Creates a "Sign In" button that redirects the user to sign in with Hugging
Face OAuth. Once the user is signed in, the button will act as a logout
button, and you can retrieve a signed-in user's profile by adding a parameter
of type `gr.OAuthProfile` to any Gradio function. This will only work if this
Gradio app is running in a Hugging Face Space. Permissions for the OAuth app
can be configured in the Spaces README file, as described here:
<https://huggingface.co/docs/hub/en/spaces-oauth.> For local development,
instead of OAuth, the local Hugging Face account that is logged in (via `hf
auth login`) will be available through the `gr.OAuthProfile` object.
|
Description
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton Docs
|
**As input component** : (Rarely used) the `str` corresponding to the
button label when the button is clicked
Your function should accept one of these types:
def predict(
value: str | None
)
...
**As output component** : string corresponding to the button label
Your function should return one of these types:
def predict(···) -> str | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton Docs
|
Parameters ▼
value: str
default `= "Sign in with Hugging Face"`
logout_value: str
default `= "Logout ({})"`
The text to display when the user is signed in. The string should contain a
placeholder for the username with a call-to-action to logout, e.g. "Logout
({})".
every: Timer | float | None
default `= None`
inputs: Component | list[Component] | set[Component] | None
default `= None`
variant: Literal['primary', 'secondary', 'stop', 'huggingface']
default `= "huggingface"`
size: Literal['sm', 'md', 'lg']
default `= "lg"`
icon: str | Path | None
default `= "/home/runner/work/gradio/gradio/gradio/icons/huggingface-
logo.svg"`
link: str | None
default `= None`
link_target: Literal['_self', '_blank', '_parent', '_top']
default `= "_self"`
visible: bool | Literal['hidden']
default `= True`
interactive: bool
default `= True`
elem_id: str | None
default `= None`
elem_classes: list[str] | str | None
default `= None`
render: bool
default `= True`
key: int | str | tuple[int | str, ...] | None
default `= None`
preserved_by_key: list[str] | str | None
default `= "value"`
scale: int | None
default `= None`
min_width: int | None
default `= None`
|
Initialization
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton Docs
|
Class| Interface String Shortcut| Initialization
---|---|---
`gradio.LoginButton`| "loginbutton"| Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton Docs
|
login_with_huggingface
|
Demos
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton 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 LoginButton component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener| Description
---|---
`LoginButton.click(fn, ···)`| Triggered when the Button is clicked.
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 wi
|
Event Listeners
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton Docs
|
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preproces
|
Event Listeners
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton Docs
|
lt `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter i
|
Event Listeners
|
https://gradio.app/docs/gradio/loginbutton
|
Gradio - Loginbutton Docs
|
one 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/loginbutton
|
Gradio - Loginbutton Docs
|
Tab (or its alias TabItem) is a layout element. Components defined within
the Tab will be visible when this tab is selected tab.
|
Description
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
with gr.Blocks() as demo:
with gr.Tab("Lion"):
gr.Image("lion.jpg")
gr.Button("New Lion")
with gr.Tab("Tiger"):
gr.Image("tiger.jpg")
gr.Button("New Tiger")
|
Example Usage
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
Parameters ▼
label: str | I18nData | None
default `= None`
The visual label for the tab
visible: bool | Literal['hidden']
default `= True`
If False, Tab will be hidden.
interactive: bool
default `= True`
If False, Tab will not be clickable.
id: int | str | None
default `= None`
An optional identifier for the tab, required if you wish to control the
selected tab from a predict function.
elem_id: str | None
default `= None`
An optional string that is assigned as the id of the <div> containing the
contents of the Tab layout. The same string followed by "-button" is attached
to the Tab button. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional string or list of strings that are assigned as the class of this
component in the HTML DOM. Can be used for targeting CSS styles.
scale: int | None
default `= None`
relative size compared to adjacent elements. 1 or greater indicates the Tab
will expand in size.
render: bool
default `= True`
If False, this layout 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 `= None`
render_children: bool
default `= False`
If True, the children of this Tab will be rendered on the page (but hidden)
when the Tab is visible but inactive. This can be useful if you want to ensure
that any components (e.g. videos or audio) within the Tab are pre-loaded
before the user clicks on the Tab.
|
Initialization
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
Methods
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
|
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gradio.Tab.select(···)
Description
%20Copyright%202022%20Fonticons,%20Inc.%20--%
|
select
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
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Event listener for when the user selects or deselects the Tab. Uses event data
gradio.SelectData to carry `value` referring to the label of the Tab, and
`selected` to refer to state of the Tab. See EventData documentation on how to
use this event data
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
i
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select
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https://gradio.app/docs/gradio/tab
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Gradio - Tab Docs
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eral['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None
default `= None`
defines how the endpoint appears in the API docs. Can be a string or None. If
set to a string, the endpoint will be exposed in the API docs with the given
name. If None (default), the name of the function will be used as the API
endpoint.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
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select
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https://gradio.app/docs/gradio/tab
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Gradio - Tab Docs
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shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators tha
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select
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https://gradio.app/docs/gradio/tab
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Gradio - Tab Docs
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d. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
api_visibility: Literal['public', 'private', 'undocumented']
default `= "public"`
controls the visibility and accessibility of this endpoint. Can be "public"
(shown in API docs and callable by clients), "private" (hidden from API docs
and not callable by clients), or "undocumented" (hidden from API docs but
callable by clients and via gr.load). If fn is None, api_visi
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select
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https://gradio.app/docs/gradio/tab
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Gradio - Tab Docs
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I 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.
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select
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https://gradio.app/docs/gradio/tab
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Gradio - Tab Docs
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Displays a classification label, along with confidence scores of top
categories, if provided. As this component does not accept user input, it is
rarely used as an input component.
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Description
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https://gradio.app/docs/gradio/label
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Gradio - Label Docs
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**As input component** : Depending on the value, passes the label as a `str | int | float`, or the labels and confidences as a `dict[str, float]`.
Your function should accept one of these types:
def predict(
value: dict[str, float] | str | int | float | None
)
...
**As output component** : Expects a `dict[str, float]` of classes and confidences, or `str` with just the class or an `int | float` for regression outputs, or a `str` path to a .json file containing a json dictionary in one of the preceding formats.
Your function should return one of these types:
def predict(···) -> dict[str, float] | str | int | float | None
...
return value
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Behavior
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https://gradio.app/docs/gradio/label
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Gradio - Label Docs
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Parameters ▼
value: dict[str, float] | str | float | Callable | None
default `= None`
Default value to show in the component. If a str or number is provided, simply
displays the string or number. If a {Dict[str, float]} of classes and
confidences is provided, displays the top class on top and the
`num_top_classes` below, along with their confidence bars. If a function is
provided, the function will be called each time the app loads to set the
initial value of this component.
num_top_classes: int | None
default `= None`
number of most confident classes to show.
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_he
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Initialization
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https://gradio.app/docs/gradio/label
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Gradio - Label Docs
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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 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.
color: str | Non
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Initialization
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https://gradio.app/docs/gradio/label
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Gradio - Label Docs
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meters 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.
color: str | None
default `= None`
The background color of the label (either a valid css color name or
hexadecimal string).
show_heading: bool
default `= True`
If False, the heading will not be displayed if a dictionary of labels and
confidences is provided. The heading will still be visible if the value is a
string or number.
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Initialization
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https://gradio.app/docs/gradio/label
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Gradio - Label Docs
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Class| Interface String Shortcut| Initialization
---|---|---
`gradio.Label`| "label"| Uses default values
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Shortcuts
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https://gradio.app/docs/gradio/label
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Gradio - Label Docs
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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 Label component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener| Description
---|---
`Label.change(fn, ···)`| Triggered when the value of the Label 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.
`Label.select(fn, ···)`| Event listener for when the user selects or deselects
the Label. Uses event data gradio.SelectData to carry `value` referring to the
label of the Label, and `selected` to refer to state of the Label. 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
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Event Listeners
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https://gradio.app/docs/gradio/label
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Gradio - Label Docs
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ext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None
default `= None`
defines how the endpoint appears in the API docs. Can be a string or None. If
set to a string, the endpoint will be exposed in the API docs with the given
name. If None (default), the name of the function will be used as the API
endpoint.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input v
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Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
ll use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. In
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Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
vents) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
api_visibility: Literal['public', 'private', 'undocumented']
default `= "public"`
controls the visibility and accessibility of this endpoint. Can be "public"
(shown in API docs and callable by clients), "private" (hidden from API docs
and not callable by clients), or "undocumented" (hidden from API docs but
callable by clients and via gr.load). If fn is None, api_visibility will
automatically be set to "private".
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
key: int | str | tuple[int | str, ...] | None
default `= None`
A unique key for this event listener to be used in @gr.render(). If set, this
value identifies an event as identical across re-renders when the key is
identical.
validator: Callable | None
default `= None`
Optional validation function to run before the main function. If provided,
this function will be executed first with queue=False, and only if it
completes successfully will the main fun
|
Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
ault `= 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.
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Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label 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.
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Description
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
**As input component** : 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, while 'layers' is a `list` of images. The images are of type
`PIL.Image`, `np.array`, or `str` filepath, depending on the `type` parameter.
Your function should accept one of these types:
def predict(
value: EditorValue | None
)
...
**As output component** : 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, 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 simply a single image (`ImageType`),
in which case it will be used as the background.
Your function should return one of these types:
def predict(···) -> EditorValue | ImageType | None
...
return value
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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
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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.
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Initialization
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https://gradio.app/docs/gradio/imageeditor
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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.
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Initialization
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https://gradio.app/docs/gradio/imageeditor
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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
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Initialization
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https://gradio.app/docs/gradio/imageeditor
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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
|
Class| Interface String Shortcut| Initialization
---|---|---
`gradio.ImageEditor`| "imageeditor"| Uses default values
`gradio.Sketchpad`| "sketchpad"| Uses sources=(),
brush=Brush(colors=["000000"], color_mode="fixed")
`gradio.Paint`| "paint"| Uses sources=()
`gradio.ImageMask`| "imagemask"| 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.
Listener| Description
---|---
`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 EventData documentation on how to use this event data
`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 single value or a tuple of
values, with each element in
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Event Listeners
|
https://gradio.app/docs/gradio/imageeditor
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Gradio - Imageeditor Docs
|
achine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None
default `= None`
defines how the endpoint appears in the API docs. Can be a string or None. If
set to a string, the endpoint will be exposed in the API docs with the given
name. If None (default), the name of the function will be used as the API
endpoint.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list
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Event Listeners
|
https://gradio.app/docs/gradio/imageeditor
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Gradio - Imageeditor Docs
|
corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
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Event Listeners
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
rn value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
api_visibility: Literal['public', 'private', 'undocumented']
default `= "public"`
controls the visibility and accessibility of this endpoint. Can be "public"
(shown in API docs and callable by clients), "private" (hidden from API docs
and not callable by clients), or "undocumented" (hidden from API docs but
callable by clients and via gr.load). If fn is None, api_visibility will
automatically be set to "private".
time_limit: int | None
default `= None`
|
Event Listeners
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
umented" (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
|
Creates a bar plot component to display data from a pandas DataFrame.
|
Description
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
**As input component** : The data to display in a line plot.
Your function should accept one of these types:
def predict(
value: AltairPlotData
)
...
**As output component** : Expects a pandas DataFrame containing the data to
display in the line plot. The DataFrame should contain at least two columns,
one for the x-axis (corresponding to this component's `x` argument) and one
for the y-axis (corresponding to `y`).
Your function should return one of these types:
def predict(···) -> pd.DataFrame | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
Parameters ▼
value: pd.DataFrame | Callable | None
default `= None`
The pandas dataframe containing the data to display in the plot.
x: str | None
default `= None`
Column corresponding to the x axis. Column can be numeric, datetime, or
string/category.
y: str | None
default `= None`
Column corresponding to the y axis. Column must be numeric.
color: str | None
default `= None`
Column corresponding to series, visualized by color. Column must be
string/category.
title: str | None
default `= None`
The title to display on top of the chart.
x_title: str | None
default `= None`
The title given to the x axis. By default, uses the value of the x parameter.
y_title: str | None
default `= None`
The title given to the y axis. By default, uses the value of the y parameter.
color_title: str | None
default `= None`
The title given to the color legend. By default, uses the value of color
parameter.
x_bin: str | float | None
default `= None`
Grouping used to cluster x values. If x column is numeric, should be number to
bin the x values. If x column is datetime, should be string such as "1h",
"15m", "10s", using "s", "m", "h", "d" suffixes.
y_aggregate: Literal['sum', 'mean', 'median', 'min', 'max', 'count'] | None
default `= None`
Aggregation function used to aggregate y values, used if x_bin is provided or
x is a string/category. Must be one of "sum", "mean", "median", "min", "max".
color_map: dict[str, str] | None
default `= None`
Mapping of series to color names or codes. For example, {"success": "green",
"fail": "FF8888"}.
colors_in_legend: list[str] | None
default `= None`
List containing column names of the series to show in the legend. By default,
all series are shown.
x_lim: list[float | None] | None
default `= None`
A tuple or list containing
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
ne`
List containing column names of the series to show in the legend. By default,
all series are shown.
x_lim: list[float | None] | None
default `= None`
A tuple or list containing the limits for the x-axis, specified as [x_min,
x_max]. To fix only one of these values, set the other to None, e.g. [0, None]
to scale from 0 to the maximum value. If x column is datetime type, x_lim
should be timestamps.
y_lim: list[float | None]
default `= None`
A tuple of list containing the limits for the y-axis, specified as [y_min,
y_max]. To fix only one of these values, set the other to None, e.g. [0, None]
to scale from 0 to the maximum to value.
x_label_angle: float
default `= 0`
The angle of the x-axis labels in degrees offset clockwise.
y_label_angle: float
default `= 0`
The angle of the y-axis labels in degrees offset clockwise.
x_axis_labels_visible: bool | Literal['hidden']
default `= True`
Whether the x-axis labels should be visible. Can be hidden when many x-axis
labels are present.
caption: str | I18nData | None
default `= None`
The (optional) caption to display below the plot.
sort: Literal['x', 'y', '-x', '-y'] | list[str] | None
default `= None`
The sorting order of the x values, if x column is type string/category. Can be
"x", "y", "-x", "-y", or list of strings that represent the order of the
categories.
tooltip: Literal['axis', 'none', 'all'] | list[str]
default `= "axis"`
The tooltip to display when hovering on a point. "axis" shows the values for
the axis columns, "all" shows all column values, and "none" shows no tooltips.
Can also provide a list of strings representing columns to show in the
tooltip, which will be displayed along with axis values.
height: int | None
default `= None`
The height of the plot in pixels.
label: str | I18nData | None
default `= None`
The (optional) label
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
ed along with axis values.
height: int | None
default `= None`
The height of the plot in pixels.
label: str | I18nData | None
default `= None`
The (optional) label to display on the top left corner of the plot.
show_label: bool | None
default `= None`
Whether the label should be displayed.
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.
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.
visible: bool | Literal['hidden']
default `= True`
Whether the plot should be visible.
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 a
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
signed 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.
buttons: list[Literal['fullscreen', 'export']] | None
default `= None`
A list of buttons to show for the component. Valid options are "fullscreen"
and "export". The "fullscreen" button allows the user to view the plot in
fullscreen mode. The "export" button allows the user to export and download
the current view of the plot as a PNG image. By default, no buttons are shown.
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.
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
Class| Interface String Shortcut| Initialization
---|---|---
`gradio.BarPlot`| "barplot"| Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
bar_plot_demo
|
Demos
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot 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 BarPlot component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener| Description
---|---
`BarPlot.select(fn, ···)`| Event listener for when the user selects or
deselects the NativePlot. Uses event data gradio.SelectData to carry `value`
referring to the label of the NativePlot, and `selected` to refer to state of
the NativePlot. See EventData documentation on how to use this event data
`BarPlot.double_click(fn, ···)`| Triggered when the NativePlot is double
clicked.
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
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
st.
api_name: str | None
default `= None`
defines how the endpoint appears in the API docs. Can be a string or None. If
set to a string, the endpoint will be exposed in the API docs with the given
name. If None (default), the name of the function will be used as the API
endpoint.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
ues for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `=
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
t arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
api_visibility: Literal['public', 'private', 'undocumented']
default `= "public"`
controls the visibility and accessibility of this endpoint. Can be "public"
(shown in API docs and callable by clients), "private" (hidden from API docs
and not callable by clients), or "undocumented" (hidden from API docs but
callable by clients and via gr.load). If fn is None, api_visibility will
automatically be set to "private".
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
key: int | str | tuple[int | str, ...] | None
default `= None`
A unique key for this event listener to be used in @gr.render(). If set, this
value identifies an event as identical across re-renders when the key is
identical.
validator: Callable | None
default `= None`
Optional validation function to run before the main function. If provided,
this function will be executed first with queue=False, and only if it
completes successfully will the main function be called. The validator
receives the same inputs as the main function and should return a
`gr.validate()` for each input value.
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
ion 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/barplot
|
Gradio - Barplot Docs
|
Button that clears the value of a component or a list of components when
clicked. It is instantiated with the list of components to clear.
|
Description
|
https://gradio.app/docs/gradio/clearbutton
|
Gradio - Clearbutton Docs
|
**As input component** : (Rarely used) the `str` corresponding to the
button label when the button is clicked
Your function should accept one of these types:
def predict(
value: str | None
)
...
**As output component** : string corresponding to the button label
Your function should return one of these types:
def predict(···) -> str | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/clearbutton
|
Gradio - Clearbutton Docs
|
Parameters ▼
components: None | list[Component] | Component
default `= None`
value: str
default `= "Clear"`
default text for the button to display. If a function is provided, the
function will be called each time the app loads to set the initial value of
this component.
every: Timer | float | None
default `= None`
continuously calls `value` to recalculate it if `value` is a function (has no
effect otherwise). Can provide a Timer whose tick resets `value`, or a float
that provides the regular interval for the reset Timer.
inputs: Component | list[Component] | set[Component] | None
default `= None`
components that are used as inputs to calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
variant: Literal['primary', 'secondary', 'stop']
default `= "secondary"`
sets the background and text color of the button. Use 'primary' for main call-
to-action buttons, 'secondary' for a more subdued style, 'stop' for a stop
button, 'huggingface' for a black background with white text, consistent with
Hugging Face's button styles.
size: Literal['sm', 'md', 'lg']
default `= "lg"`
size of the button. Can be "sm", "md", or "lg".
icon: str | Path | None
default `= None`
URL or path to the icon file to display within the button. If None, no icon
will be displayed.
link: str | None
default `= None`
URL to open when the button is clicked. If None, no link will be used.
link_target: Literal['_self', '_blank', '_parent', '_top']
default `= "_self"`
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
interactive: bool
default `= True`
if False, the Button will be in a disabled state.
|
Initialization
|
https://gradio.app/docs/gradio/clearbutton
|
Gradio - Clearbutton Docs
|
ent will be visually
hidden and not take up space in the layout but still exist in the DOM
interactive: bool
default `= True`
if False, the Button will be in a disabled state.
elem_id: str | None
default `= None`
an optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
an optional list of strings that are assigned as the classes of this component
in the HTML DOM. Can be used for targeting CSS styles.
render: bool
default `= True`
if False, component will not render be rendered in the Blocks context. Should
be used if the intention is to assign event listeners now but render the
component later.
key: int | str | 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.
scale: int | None
default `= None`
relative size compared to adjacent Components. For example if Components A and
B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide
as B. Should be an integer. scale applies in Rows, and to top-level Components
in Blocks where fill_height=True.
min_width: int | None
default `= None`
minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrowe
|
Initialization
|
https://gradio.app/docs/gradio/clearbutton
|
Gradio - Clearbutton Docs
|
min_width: int | None
default `= None`
minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrower than
min_width, the min_width parameter will be respected first.
api_name: str | None
default `= None`
api_visibility: Literal['public', 'private', 'undocumented']
default `= "undocumented"`
|
Initialization
|
https://gradio.app/docs/gradio/clearbutton
|
Gradio - Clearbutton Docs
|
Class| Interface String Shortcut| Initialization
---|---|---
`gradio.ClearButton`| "clearbutton"| Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/clearbutton
|
Gradio - Clearbutton 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 ClearButton component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener| Description
---|---
`ClearButton.add(fn, ···)`| Adds a component or list of components to the list
of components that will be cleared when the button is clicked.
`ClearButton.click(fn, ···)`| Triggered when the Button is clicked.
Event Parameters
Parameters ▼
components: None | Component | list[Component]
|
Event Listeners
|
https://gradio.app/docs/gradio/clearbutton
|
Gradio - Clearbutton Docs
|
Creates a checkbox that can be set to `True` or `False`. Can be used as an
input to pass a boolean value to a function or as an output to display a
boolean value.
|
Description
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
**As input component** : Passes the status of the checkbox as a `bool`.
Your function should accept one of these types:
def predict(
value: bool | None
)
...
**As output component** : Expects a `bool` value that is set as the status
of the checkbox
Your function should return one of these types:
def predict(···) -> bool | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
Parameters ▼
value: bool | Callable
default `= False`
if True, checked by default. 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 checkbox, displayed to the right of the checkbox if
`show_label` is `True`.
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, this checkbox can be ch
|
Initialization
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
e results in this Component being narrower than
min_width, the min_width parameter will be respected first.
interactive: bool | None
default `= None`
if True, this checkbox can be checked; 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, 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.
|
Initialization
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
es
provided during constructor.
|
Initialization
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
Class| Interface String Shortcut| Initialization
---|---|---
`gradio.Checkbox`| "checkbox"| Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
sentence_builderhello_world_3
|
Demos
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox 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 Checkbox component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener| Description
---|---
`Checkbox.change(fn, ···)`| Triggered when the value of the Checkbox 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.
`Checkbox.input(fn, ···)`| This listener is triggered when the user changes
the value of the Checkbox.
`Checkbox.select(fn, ···)`| Event listener for when the user selects or
deselects the Checkbox. Uses event data gradio.SelectData to carry `value`
referring to the label of the Checkbox, and `selected` to refer to state of
the Checkbox. 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] | Non
|
Event Listeners
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
o use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None
default `= None`
defines how the endpoint appears in the API docs. Can be a string or None. If
set to a string, the endpoint will be exposed in the API docs with the given
name. If None (default), the name of the function will be used as the API
endpoint.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
d
|
Event Listeners
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete
|
Event Listeners
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
t to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
api_visibility: Literal['public', 'private', 'undocumented']
default `= "public"`
controls the visibility and accessibility of this endpoint. Can be "public"
(shown in API docs and callable by clients), "private" (hidden from API docs
and not callable by clients), or "undocumented" (hidden from API docs but
callable by clients and via gr.load). If fn is None, api_visibility will
automatically be set to "private".
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
key: int | str | tuple[int | str, ...] | None
default `= None`
A unique key for this event listener to be used in @gr.render(). If set, this
value identifies an event as identical across re-renders when the key is
identical.
validator: Callable | None
default `= None`
Optional validation function to run before the main functio
|
Event Listeners
|
https://gradio.app/docs/gradio/checkbox
|
Gradio - Checkbox Docs
|
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 set of (string or numeric type) radio buttons of which only one
can be selected.
|
Description
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio Docs
|
**As input component** : Passes the value of the selected radio button as a `str | int | float`, or its index as an `int` into the function, depending on `type`.
Your function should accept one of these types:
def predict(
value: str | int | float | None
)
...
**As output component** : Expects a `str | int | float` corresponding to the value of the radio button to be selected
Your function should return one of these types:
def predict(···) -> str | int | float | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio 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 radio
button and value is the value to be passed to the function, or returned by the
function.
value: str | int | float | Callable | None
default `= None`
The option selected by default. If None, no option is selected by default. 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.
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.
show_label: bool | None
default `= None`
if True, will display label.
|
Initialization
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio Docs
|
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 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 radio group 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 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, Compon
|
Initialization
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio Docs
|
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.
rtl: bool
default `= False`
If True, the radio buttons will be displayed in right-to-left order. Default
is False.
|
Initialization
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio Docs
|
Class| Interface String Shortcut| Initialization
---|---|---
`gradio.Radio`| "radio"| Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio Docs
|
sentence_builderblocks_essay
|
Demos
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio 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 Radio component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener| Description
---|---
`Radio.select(fn, ···)`| Event listener for when the user selects or deselects
the Radio. Uses event data gradio.SelectData to carry `value` referring to the
label of the Radio, and `selected` to refer to state of the Radio. See
EventData documentation on how to use this event data
`Radio.change(fn, ···)`| Triggered when the value of the Radio 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.
`Radio.input(fn, ···)`| This listener is triggered when the user changes the
value of the Radio.
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 o
|
Event Listeners
|
https://gradio.app/docs/gradio/radio
|
Gradio - Radio Docs
|
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