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ill 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.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
|
Event Listeners
|
https://gradio.app/docs/gradio/image
|
Gradio - Image Docs
|
ll still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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/image
|
Gradio - Image Docs
|
Helper Classes
|
https://gradio.app/docs/gradio/image
|
Gradio - Image 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/image
|
Gradio - Image Docs
|
This component displays a table of value spreadsheet-like component. Can be
used to display data as an output component, or as an input to collect data
from the user.
|
Description
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
**As input component** : Passes the uploaded spreadsheet data as a
`pandas.DataFrame`, `numpy.array`, `polars.DataFrame`, or native 2D Python
`list[list]` depending on `type`
Your function should accept one of these types:
def predict(
value: pd.DataFrame | np.ndarray | pl.DataFrame | list[list]
)
...
**As output component** : Expects data in any of these formats:
`pandas.DataFrame`, `pandas.Styler`, `numpy.array`, `polars.DataFrame`,
`list[list]`, `list`, or a `dict` with keys 'data' (and optionally 'headers'),
or `str` path to a csv, which is rendered as the spreadsheet.
Your function should return one of these types:
def predict(···) -> pd.DataFrame | Styler | np.ndarray | pl.DataFrame | list | list[list] | dict | str | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
Parameters ▼
value: pd.DataFrame | Styler | np.ndarray | pl.DataFrame | list | list[list] | dict | str | Callable | None
default `= None`
Default value to display in the DataFrame. Supports pandas, numpy, polars, and
list of lists. If a Styler is provided, it will be used to set the displayed
value in the DataFrame (e.g. to set precision of numbers) if the `interactive`
is False. If a Callable function is provided, the function will be called
whenever the app loads to set the initial value of the component.
headers: list[str] | None
default `= None`
List of str header names. These are used to set the column headers of the
dataframe if the value does not have headers. If None, no headers are shown.
row_count: int | tuple[int, str]
default `= (1, 'dynamic')`
Limit number of rows for input and decide whether user can create new rows or
delete existing rows. The first element of the tuple is an `int`, the row
count; the second should be 'fixed' or 'dynamic', the new row behaviour. If an
`int` is passed the rows default to 'dynamic'
col_count: int | tuple[int, str] | None
default `= None`
Limit number of columns for input and decide whether user can create new
columns or delete existing columns. The first element of the tuple is an
`int`, the number of columns; the second should be 'fixed' or 'dynamic', the
new column behaviour. If an `int` is passed the columns default to 'dynamic'
datatype: Literal['str', 'number', 'bool', 'date', 'markdown', 'html', 'image', 'auto'] | list[Literal['str', 'number', 'bool', 'date', 'markdown', 'html']]
default `= "str"`
Datatype of values in sheet. Can be provided per column as a list of strings,
or for the entire sheet as a single string. Valid datatypes are "str",
"number", "bool", "date", and "markdown". Boolean columns will display as
checkboxes. If the datatype "auto" is used, the column datatypes are
automatically selected based on the value
|
Initialization
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
pes are "str",
"number", "bool", "date", and "markdown". Boolean columns will display as
checkboxes. If the datatype "auto" is used, the column datatypes are
automatically selected based on the value input if possible.
type: Literal['pandas', 'numpy', 'array', 'polars']
default `= "pandas"`
Type of value to be returned by component. "pandas" for pandas dataframe,
"numpy" for numpy array, "polars" for polars dataframe, or "array" for a
Python list of lists.
latex_delimiters: list[dict[str, str | bool]] | None
default `= None`
A list of dicts of the form {"left": open delimiter (str), "right": close
delimiter (str), "display": whether to display in newline (bool)} that will be
used to render LaTeX expressions. If not provided, `latex_delimiters` is set
to `[{ "left": "$$", "right": "$$", "display": True }]`, so only expressions
enclosed in $$ delimiters will be rendered as LaTeX, and in a new line. Pass
in an empty list to disable LaTeX rendering. For more information, see the
[KaTeX documentation](https://katex.org/docs/autorender.html). Only applies to
columns whose datatype is "markdown".
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.
show_label: bool | None
default `= None`
if True, will display label.
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 (
|
Initialization
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
l 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.
max_height: int | str
default `= 500`
The maximum height of the dataframe, specified in pixels if a number is
passed, or in CSS units if a string is passed. If more rows are created than
can fit in the height, a scrollbar will appear.
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 edit the dataframe; if False, can only be used to
display data. 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
|
Initialization
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
tr | 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.
wrap: bool
default `= False`
If True, the text in table cells will wrap when appropriate. If False and the
`column_width` parameter is not set, the column widths will expand based on
the cell contents and the table may need to be horizontally scrolled. If
`column_width` is set, then any overflow text will be hidden.
line_breaks: bool
default `= True`
If True (default), will enable Github-flavored Markdown line breaks in chatbot
messages. If False, single new lines will be ignored. Only applies for columns
of type "markdown."
column_widths: list[str | int] | None
default `= None`
An optional list representing the width of each column. The elements of the
list should be in the format "100px" (ints are also accepted and converted to
pixel values) or "10%". The percentage width is calculated based on the
viewport width of the table. If not provided, the column widths will be
au
|
Initialization
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
rmat "100px" (ints are also accepted and converted to
pixel values) or "10%". The percentage width is calculated based on the
viewport width of the table. If not provided, the column widths will be
automatically determined based on the content of the cells.
show_fullscreen_button: bool
default `= False`
If True, will show a button to view the values in the table in fullscreen
mode.
show_copy_button: bool
default `= False`
If True, will show a button to copy the table data to the clipboard.
show_row_numbers: bool
default `= False`
If True, will display row numbers in a separate column.
max_chars: int | None
default `= None`
Maximum number of characters to display in each cell before truncating
(single-clicking a cell value will still reveal the full content). If None, no
truncation is applied.
show_search: Literal['none', 'search', 'filter']
default `= "none"`
Show a search input in the toolbar. If "search", a search input is shown. If
"filter", a search input and filter buttons are shown. If "none", no search
input is shown.
pinned_columns: int | None
default `= None`
If provided, will pin the specified number of columns from the left.
static_columns: list[int] | None
default `= None`
List of column indices (int) that should not be editable. Only applies when
interactive=True. When specified, col_count is automatically set to "fixed"
and columns cannot be inserted or deleted.
|
Initialization
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.Dataframe` | "dataframe" | Uses default values
`gradio.Numpy` | "numpy" | Uses type="numpy"
`gradio.Matrix` | "matrix" | Uses type="array"
`gradio.List` | "list" | Uses type="array", col_count=1
|
Shortcuts
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
filter_recordsmatrix_transposetax_calculatorsort_records
Open in 🎢 ↗ import gradio as gr def filter_records(records, gender): return
records[records["gender"] == gender] demo = gr.Interface( filter_records, [
gr.Dataframe( headers=["name", "age", "gender"], datatype=["str", "number",
"str"], row_count=5, col_count=(3, "fixed"), ), gr.Dropdown(["M", "F", "O"]),
], "dataframe", description="Enter gender as 'M', 'F', or 'O' for other.", )
if __name__ == "__main__": demo.launch()
import gradio as gr
def filter_records(records, gender):
return records[records["gender"] == gender]
demo = gr.Interface(
filter_records,
[
gr.Dataframe(
headers=["name", "age", "gender"],
datatype=["str", "number", "str"],
row_count=5,
col_count=(3, "fixed"),
),
gr.Dropdown(["M", "F", "O"]),
],
"dataframe",
description="Enter gender as 'M', 'F', or 'O' for other.",
)
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import numpy as np import gradio as gr def transpose(matrix):
return matrix.T demo = gr.Interface( transpose, gr.Dataframe(type="numpy",
datatype="number", row_count=5, col_count=3, show_fullscreen_button=True),
"numpy", examples=[ [np.zeros((30, 30)).tolist()], [np.ones((2, 2)).tolist()],
[np.random.randint(0, 10, (3, 10)).tolist()], [np.random.randint(0, 10, (10,
3)).tolist()], [np.random.randint(0, 10, (10, 10)).tolist()], ],
cache_examples=False ) if __name__ == "__main__": demo.launch()
import numpy as np
import gradio as gr
def transpose(matrix):
return matrix.T
demo = gr.Interface(
transpose,
gr.Dataframe(type="numpy", datatype="number", row_count=5, col_count=3, show_fullscreen_button=True),
"numpy",
examples=[
[np.zeros((30, 30)).tolist()],
[np.ones((2,
|
Demos
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
aframe(type="numpy", datatype="number", row_count=5, col_count=3, show_fullscreen_button=True),
"numpy",
examples=[
[np.zeros((30, 30)).tolist()],
[np.ones((2, 2)).tolist()],
[np.random.randint(0, 10, (3, 10)).tolist()],
[np.random.randint(0, 10, (10, 3)).tolist()],
[np.random.randint(0, 10, (10, 10)).tolist()],
],
cache_examples=False
)
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import gradio as gr def tax_calculator(income, marital_status,
assets): tax_brackets = [(10, 0), (25, 8), (60, 12), (120, 20), (250, 30)]
total_deductible = sum(assets["Cost"]) taxable_income = income -
total_deductible total_tax = 0 for bracket, rate in tax_brackets: if
taxable_income > bracket: total_tax += (taxable_income - bracket) * rate / 100
if marital_status == "Married": total_tax *= 0.75 elif marital_status ==
"Divorced": total_tax *= 0.8 return round(total_tax) demo = gr.Interface(
tax_calculator, [ "number", gr.Radio(["Single", "Married", "Divorced"]),
gr.Dataframe( headers=["Item", "Cost"], datatype=["str", "number"],
label="Assets Purchased this Year", ), ], "number", examples=[ [10000,
"Married", [["Suit", 5000], ["Laptop", 800], ["Car", 1800]]], [80000,
"Single", [["Suit", 800], ["Watch", 1800], ["Car", 800]]], ], ) demo.launch()
import gradio as gr
def tax_calculator(income, marital_status, assets):
tax_brackets = [(10, 0), (25, 8), (60, 12), (120, 20), (250, 30)]
total_deductible = sum(assets["Cost"])
taxable_income = income - total_deductible
total_tax = 0
for bracket, rate in tax_brackets:
if taxable_income > bracket:
total_tax += (taxable_income - bracket) * rate / 100
if marital_status == "Married":
total_tax *= 0.75
elif marital_status == "Divorced":
total_tax *= 0.8
return round(to
|
Demos
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
- bracket) * rate / 100
if marital_status == "Married":
total_tax *= 0.75
elif marital_status == "Divorced":
total_tax *= 0.8
return round(total_tax)
demo = gr.Interface(
tax_calculator,
[
"number",
gr.Radio(["Single", "Married", "Divorced"]),
gr.Dataframe(
headers=["Item", "Cost"],
datatype=["str", "number"],
label="Assets Purchased this Year",
),
],
"number",
examples=[
[10000, "Married", [["Suit", 5000], ["Laptop", 800], ["Car", 1800]]],
[80000, "Single", [["Suit", 800], ["Watch", 1800], ["Car", 800]]],
],
)
demo.launch()
Open in 🎢 ↗ import gradio as gr def sort_records(records): return
records.sort("Quantity") demo = gr.Interface( sort_records, gr.Dataframe(
headers=["Item", "Quantity"], datatype=["str", "number"], row_count=3,
col_count=(2, "fixed"), type="polars" ), "dataframe", description="Sort by
Quantity" ) if __name__ == "__main__": demo.launch()
import gradio as gr
def sort_records(records):
return records.sort("Quantity")
demo = gr.Interface(
sort_records,
gr.Dataframe(
headers=["Item", "Quantity"],
datatype=["str", "number"],
row_count=3,
col_count=(2, "fixed"),
type="polars"
),
"dataframe",
description="Sort by Quantity"
)
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe 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 Dataframe component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`Dataframe.change(fn, ···)` | Triggered when the value of the Dataframe 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.
`Dataframe.input(fn, ···)` | This listener is triggered when the user changes the value of the Dataframe.
`Dataframe.select(fn, ···)` | Event listener for when the user selects or deselects the Dataframe. Uses event data gradio.SelectData to carry `value` referring to the label of the Dataframe, and `selected` to refer to state of the Dataframe. See EventData documentation on how to use this event data
`Dataframe.edit(fn, ···)` | This listener is triggered when the user edits the Dataframe (e.g. image) using the built-in editor.
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 s
|
Event Listeners
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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
|
Event Listeners
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
ll
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `=
|
Event Listeners
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
s 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.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
key: int | str | tuple[int | s
|
Event Listeners
|
https://gradio.app/docs/gradio/dataframe
|
Gradio - Dataframe Docs
|
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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/dataframe
|
Gradio - Dataframe 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
|
|
%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
gradio.Tab.select(···)
Description
%20Copyright%202022%20Fonticons,%20Inc.%20--%
|
select
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
20Font%20Awesome%20Pro%206.0.0%20by%20@fontawesome%20-%20https://fontawesome.com%20License%20-%20https://fontawesome.com/license%20\(Commercial%20License\)%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
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
|
select
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
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 | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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 w
|
select
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
put component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
se
|
select
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
g 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
|
select
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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.
|
select
|
https://gradio.app/docs/gradio/tab
|
Gradio - Tab Docs
|
Creates a slider that ranges from `minimum` to `maximum` with a step size
of `step`.
|
Description
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
**As input component** : Passes slider value as a `float` into the
function.
Your function should accept one of these types:
def predict(
value: float
)
...
**As output component** : Expects an `int` or `float` returned from
function and sets slider value to it as long as it is within range (otherwise,
sets to minimum value).
Your function should return one of these types:
def predict(···) -> float | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
Parameters ▼
minimum: float
default `= 0`
minimum value for slider. When used as an input, if a user provides a smaller
value, a gr.Error exception is raised by the backend.
maximum: float
default `= 100`
maximum value for slider. When used as an input, if a user provides a larger
value, a gr.Error exception is raised by the backend.
value: float | Callable | None
default `= None`
default value for slider. If a function is provided, the function will be
called each time the app loads to set the initial value of this component.
Ignored if randomized=True.
step: float | None
default `= None`
increment between slider values.
precision: int | None
default `= None`
Precision to round input/output to. If set to 0, will round to nearest integer
and convert type to int. If None, no rounding happens.
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
|
Initialization
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
sed 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, slider will be adjustable; if False, adjusting 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 l
|
Initialization
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
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.
randomize: bool
default `= False`
If True, the value of the slider when the app loads is taken uniformly at
random from the range given by the minimum and maximum.
show_reset_button: bool
default `= True`
if False, will hide button to reset slider to default value.
|
Initialization
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.Slider` | "slider" | Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
sentence_builderslider_releaseinterface_random_sliderblocks_random_slider
Open in 🎢 ↗ import gradio as gr def sentence_builder(quantity, animal,
countries, place, activity_list, morning): return f"""The {quantity} {animal}s
from {" and ".join(countries)} went to the {place} where they {" and
".join(activity_list)} until the {"morning" if morning else "night"}""" demo =
gr.Interface( sentence_builder, [ gr.Slider(2, 20, value=4, label="Count",
info="Choose between 2 and 20"), gr.Dropdown( ["cat", "dog", "bird"],
label="Animal", info="Will add more animals later!" ),
gr.CheckboxGroup(["USA", "Japan", "Pakistan"], label="Countries", info="Where
are they from?"), gr.Radio(["park", "zoo", "road"], label="Location",
info="Where did they go?"), gr.Dropdown( ["ran", "swam", "ate", "slept"],
value=["swam", "slept"], multiselect=True, label="Activity", info="Lorem ipsum
dolor sit amet, consectetur adipiscing elit. Sed auctor, nisl eget ultricies
aliquam, nunc nisl aliquet nunc, eget aliquam nisl nunc vel nisl." ),
gr.Checkbox(label="Morning", info="Did they do it in the morning?"), ],
"text", examples=[ [2, "cat", ["Japan", "Pakistan"], "park", ["ate", "swam"],
True], [4, "dog", ["Japan"], "zoo", ["ate", "swam"], False], [10, "bird",
["USA", "Pakistan"], "road", ["ran"], False], [8, "cat", ["Pakistan"], "zoo",
["ate"], True], ] ) if __name__ == "__main__": demo.launch()
import gradio as gr
def sentence_builder(quantity, animal, countries, place, activity_list, morning):
return f"""The {quantity} {animal}s from {" and ".join(countries)} went to the {place} where they {" and ".join(activity_list)} until the {"morning" if morning else "night"}"""
demo = gr.Interface(
sentence_builder,
[
gr.Slider(2, 20, value=4, label="Count", info="Choose between 2 and 20"),
gr.Dropdown(
["cat", "dog", "bird"], label="Animal", info="Will add more animals later!"
),
gr.Checkb
|
Demos
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
abel="Count", info="Choose between 2 and 20"),
gr.Dropdown(
["cat", "dog", "bird"], label="Animal", info="Will add more animals later!"
),
gr.CheckboxGroup(["USA", "Japan", "Pakistan"], label="Countries", info="Where are they from?"),
gr.Radio(["park", "zoo", "road"], label="Location", info="Where did they go?"),
gr.Dropdown(
["ran", "swam", "ate", "slept"], value=["swam", "slept"], multiselect=True, label="Activity", info="Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed auctor, nisl eget ultricies aliquam, nunc nisl aliquet nunc, eget aliquam nisl nunc vel nisl."
),
gr.Checkbox(label="Morning", info="Did they do it in the morning?"),
],
"text",
examples=[
[2, "cat", ["Japan", "Pakistan"], "park", ["ate", "swam"], True],
[4, "dog", ["Japan"], "zoo", ["ate", "swam"], False],
[10, "bird", ["USA", "Pakistan"], "road", ["ran"], False],
[8, "cat", ["Pakistan"], "zoo", ["ate"], True],
]
)
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import gradio as gr def identity(x, state): state += 1 return x,
state, state with gr.Blocks() as demo: slider = gr.Slider(0, 100, step=0.1)
state = gr.State(value=0) with gr.Row(): number = gr.Number(label="On
release") number2 = gr.Number(label="Number of events fired")
slider.release(identity, inputs=[slider, state], outputs=[number, state,
number2], api_name="predict") if __name__ == "__main__": print("here")
demo.launch() print(demo.server_port)
import gradio as gr
def identity(x, state):
state += 1
return x, state, state
with gr.Blocks() as demo:
slider = gr.Slider(0, 100, step=0.1)
state = gr.State(value=0)
with gr.Row():
number = gr.Number(label="On release")
number2 = gr.Number(label="Number o
|
Demos
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
slider = gr.Slider(0, 100, step=0.1)
state = gr.State(value=0)
with gr.Row():
number = gr.Number(label="On release")
number2 = gr.Number(label="Number of events fired")
slider.release(identity, inputs=[slider, state], outputs=[number, state, number2], api_name="predict")
if __name__ == "__main__":
print("here")
demo.launch()
print(demo.server_port)
Open in 🎢 ↗ import gradio as gr def func(slider_1, slider_2, *args): return
slider_1 + slider_2 * 5 demo = gr.Interface( func, [ gr.Slider(minimum=1.5,
maximum=250000.89, randomize=True, label="Random Big Range"),
gr.Slider(minimum=-1, maximum=1, randomize=True, step=0.05, label="Random only
multiple of 0.05 allowed"), gr.Slider(minimum=0, maximum=1, randomize=True,
step=0.25, label="Random only multiples of 0.25 allowed"),
gr.Slider(minimum=-100, maximum=100, randomize=True, step=3, label="Random
between -100 and 100 step 3"), gr.Slider(minimum=-100, maximum=100,
randomize=True, label="Random between -100 and 100"), gr.Slider(value=0.25,
minimum=5, maximum=30, step=-1), ], "number", ) if __name__ == "__main__":
demo.launch()
import gradio as gr
def func(slider_1, slider_2, *args):
return slider_1 + slider_2 * 5
demo = gr.Interface(
func,
[
gr.Slider(minimum=1.5, maximum=250000.89, randomize=True, label="Random Big Range"),
gr.Slider(minimum=-1, maximum=1, randomize=True, step=0.05, label="Random only multiple of 0.05 allowed"),
gr.Slider(minimum=0, maximum=1, randomize=True, step=0.25, label="Random only multiples of 0.25 allowed"),
gr.Slider(minimum=-100, maximum=100, randomize=True, step=3, label="Random between -100 and 100 step 3"),
gr.Slider(minimum=-100, maximum=100, randomize=True, label="Random between -100 and 100"),
gr.Slider(value=0.25, minimum=5, maximum=30, step=-1),
],
|
Demos
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
d 100 step 3"),
gr.Slider(minimum=-100, maximum=100, randomize=True, label="Random between -100 and 100"),
gr.Slider(value=0.25, minimum=5, maximum=30, step=-1),
],
"number",
)
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import gradio as gr def func(slider_1, slider_2): return slider_1
* 5 + slider_2 with gr.Blocks() as demo: slider = gr.Slider(minimum=-10.2,
maximum=15, label="Random Slider (Static)", randomize=True) slider_1 =
gr.Slider(minimum=100, maximum=200, label="Random Slider (Input 1)",
randomize=True) slider_2 = gr.Slider(minimum=10, maximum=23.2, label="Random
Slider (Input 2)", randomize=True) slider_3 = gr.Slider(value=3, label="Non
random slider") btn = gr.Button("Run") btn.click(func, inputs=[slider_1,
slider_2], outputs=gr.Number()) if __name__ == "__main__": demo.launch()
import gradio as gr
def func(slider_1, slider_2):
return slider_1 * 5 + slider_2
with gr.Blocks() as demo:
slider = gr.Slider(minimum=-10.2, maximum=15, label="Random Slider (Static)", randomize=True)
slider_1 = gr.Slider(minimum=100, maximum=200, label="Random Slider (Input 1)", randomize=True)
slider_2 = gr.Slider(minimum=10, maximum=23.2, label="Random Slider (Input 2)", randomize=True)
slider_3 = gr.Slider(value=3, label="Non random slider")
btn = gr.Button("Run")
btn.click(func, inputs=[slider_1, slider_2], outputs=gr.Number())
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider 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 Slider component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`Slider.change(fn, ···)` | Triggered when the value of the Slider 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.
`Slider.input(fn, ···)` | This listener is triggered when the user changes the value of the Slider.
`Slider.release(fn, ···)` | This listener is triggered when the user releases the mouse on this Slider.
Event Parameters
Parameters ▼
fn: Callable | None | Literal['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `=
|
Event Listeners
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
one
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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`
|
Event Listeners
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
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/slider
|
Gradio - Slider Docs
|
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.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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 fun
|
Event Listeners
|
https://gradio.app/docs/gradio/slider
|
Gradio - Slider Docs
|
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/slider
|
Gradio - Slider Docs
|
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized
from a mapping object's (key, value) pairs dict(iterable) -> new dictionary
initialized as if via: d = `` for k, v in iterable: d[k] = v dict(__kwargs) -
> new dictionary initialized with the name=value pairs in the keyword argument
list. For example: dict(one=1, two=2)
|
Description
|
https://gradio.app/docs/gradio/dependency
|
Gradio - Dependency Docs
|
Accordion is a layout element which can be toggled to show/hide the
contained content.
|
Description
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
with gr.Accordion("See Details"):
gr.Markdown("lorem ipsum")
|
Example Usage
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
Parameters ▼
label: str | I18nData | None
default `= None`
name of accordion section.
open: bool
default `= True`
if True, accordion is open by default.
visible: bool | Literal['hidden']
default `= True`
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 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.
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`
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 `= None`
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/accordion
|
Gradio - Accordion Docs
|
Methods
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
|
%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
gradio.Accordion.expand(···)
Description
%20Copyright%202022%20Fonticons,%20Inc.
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
c!--!%20Font%20Awesome%20Pro%206.0.0%20by%20@fontawesome%20-%20https://fontawesome.com%20License%20-%20https://fontawesome.com/license%20\(Commercial%20License\)%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
This listener is triggered when the Accordion is expanded.
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
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
onds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
s a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
r 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.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limi
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
ame to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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.
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
gradio.Accordion.collapse(···)
Description
%20Copyright%202022%20Fonticons,%20In
|
collapse
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
%3c!--!%20Font%20Awesome%20Pro%206.0.0%20by%20@fontawesome%20-%20https://fontawesome.com%20License%20-%20https://fontawesome.com/license%20\(Commercial%20License\)%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
This listener is triggered when the Accordion is collapsed.
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: Compon
|
collapse
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
esponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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
|
collapse
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
hows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that
|
collapse
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
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.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_l
|
collapse
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
i_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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.
|
collapse
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
gradio.Accordion.expand(···)
Description
%20Copyright%202022%20Fonticons,%20Inc.
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
c!--!%20Font%20Awesome%20Pro%206.0.0%20by%20@fontawesome%20-%20https://fontawesome.com%20License%20-%20https://fontawesome.com/license%20\(Commercial%20License\)%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
This listener is triggered when the Accordion is expanded.
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
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
onds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
s a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
r 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.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limi
|
expand
|
https://gradio.app/docs/gradio/accordion
|
Gradio - Accordion Docs
|
ame to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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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Gradio - Accordion Docs
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%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
gradio.Accordion.collapse(···)
Description
%20Copyright%202022%20Fonticons,%20In
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collapse
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https://gradio.app/docs/gradio/accordion
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Gradio - Accordion Docs
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%3c!--!%20Font%20Awesome%20Pro%206.0.0%20by%20@fontawesome%20-%20https://fontawesome.com%20License%20-%20https://fontawesome.com/license%20\(Commercial%20License\)%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
This listener is triggered when the Accordion is collapsed.
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: Compon
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https://gradio.app/docs/gradio/accordion
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Gradio - Accordion Docs
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esponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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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collapse
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https://gradio.app/docs/gradio/accordion
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Gradio - Accordion Docs
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hows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that
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https://gradio.app/docs/gradio/accordion
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Gradio - Accordion Docs
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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.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_l
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Gradio - Accordion Docs
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i_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
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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https://gradio.app/docs/gradio/accordion
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Gradio - Accordion Docs
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The gr.EditData class is a subclass of gr.Event data that specifically
carries information about the `.edit()` event. When gr.EditData is added as a
type hint to an argument of an event listener method, a gr.EditData object
will automatically be passed as the value of that argument. The attributes of
this object contains information about the event that triggered the listener.
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Description
|
https://gradio.app/docs/gradio/editdata
|
Gradio - Editdata Docs
|
import gradio as gr
def edit(edit_data: gr.EditData, history: list[gr.MessageDict]):
history_up_to_edit = history[:edit_data.index]
history_up_to_edit[-1] = edit_data.value
return history_up_to_edit
with gr.Blocks() as demo:
chatbot = gr.Chatbot()
chatbot.undo(edit, chatbot, chatbot)
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/editdata
|
Gradio - Editdata Docs
|
Parameters ▼
index: int | tuple[int, int]
The index of the message that was edited.
previous_value: Any
The previous content of the message that was edited.
value: Any
The new content of the message that was edited.
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Attributes
|
https://gradio.app/docs/gradio/editdata
|
Gradio - Editdata Docs
|
The gr.KeyUpData class is a subclass of gr.EventData that specifically
carries information about the `.key_up()` event. When gr.KeyUpData is added as
a type hint to an argument of an event listener method, a gr.KeyUpData object
will automatically be passed as the value of that argument. The attributes of
this object contains information about the event that triggered the listener.
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Description
|
https://gradio.app/docs/gradio/keyupdata
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Gradio - Keyupdata Docs
|
import gradio as gr
def test(value, key_up_data: gr.KeyUpData):
return {
"component value": value,
"input value": key_up_data.input_value,
"key": key_up_data.key
}
with gr.Blocks() as demo:
d = gr.Dropdown(["abc", "def"], allow_custom_value=True)
t = gr.JSON()
d.key_up(test, d, t)
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/keyupdata
|
Gradio - Keyupdata Docs
|
Parameters ▼
key: str
The key that was pressed.
input_value: str
The displayed value in the input textbox after the key was pressed. This may
be different than the `value` attribute of the component itself, as the
`value` attribute of some components (e.g. Dropdown) are not updated until the
user presses Enter.
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Attributes
|
https://gradio.app/docs/gradio/keyupdata
|
Gradio - Keyupdata Docs
|
dropdown_key_up
Open in 🎢 ↗ import gradio as gr def test(value, key_up_data: gr.KeyUpData):
return { "component value": value, "input value": key_up_data.input_value,
"key": key_up_data.key } with gr.Blocks() as demo: d = gr.Dropdown(["abc",
"def"], allow_custom_value=True) t = gr.JSON() d.key_up(test, d, t) if
__name__ == "__main__": demo.launch()
import gradio as gr
def test(value, key_up_data: gr.KeyUpData):
return {
"component value": value,
"input value": key_up_data.input_value,
"key": key_up_data.key
}
with gr.Blocks() as demo:
d = gr.Dropdown(["abc", "def"], allow_custom_value=True)
t = gr.JSON()
d.key_up(test, d, t)
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/keyupdata
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Gradio - Keyupdata Docs
|
The FileData class is a subclass of the GradioModel class that represents a
file object within a Gradio interface. It is used to store file data and
metadata when a file is uploaded.
|
Description
|
https://gradio.app/docs/gradio/filedata
|
Gradio - Filedata Docs
|
from gradio_client import Client, FileData, handle_file
def get_url_on_server(data: FileData):
print(data['url'])
client = Client("gradio/gif_maker_main", download_files=False)
job = client.submit([handle_file("./cheetah.jpg")], api_name="/predict")
data = job.result()
video: FileData = data['video']
get_url_on_server(video)
|
Example Usage
|
https://gradio.app/docs/gradio/filedata
|
Gradio - Filedata Docs
|
Parameters ▼
path: str
The server file path where the file is stored.
url: Optional[str]
The normalized server URL pointing to the file.
size: Optional[int]
The size of the file in bytes.
orig_name: Optional[str]
The original filename before upload.
mime_type: Optional[str]
The MIME type of the file.
is_stream: bool
Indicates whether the file is a stream.
meta: dict
Additional metadata used internally (should not be changed).
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Attributes
|
https://gradio.app/docs/gradio/filedata
|
Gradio - Filedata Docs
|
The gr.CopyData class is a subclass of gr.EventData that specifically
carries information about the `.copy()` event. When gr.CopyData is added as a
type hint to an argument of an event listener method, a gr.CopyData object
will automatically be passed as the value of that argument. The attributes of
this object contains information about the event that triggered the listener.
|
Description
|
https://gradio.app/docs/gradio/copydata
|
Gradio - Copydata Docs
|
import gradio as gr
def on_copy(copy_data: gr.CopyData):
return f"Copied text: {copy_data.value}"
with gr.Blocks() as demo:
textbox = gr.Textbox("Hello World!")
copied = gr.Textbox()
textbox.copy(on_copy, None, copied)
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/copydata
|
Gradio - Copydata Docs
|
Parameters ▼
value: Any
The value that was copied.
|
Attributes
|
https://gradio.app/docs/gradio/copydata
|
Gradio - Copydata Docs
|
Interface is Gradio's main high-level class, and allows you to create a
web-based GUI / demo around a machine learning model (or any Python function)
in a few lines of code. You must specify three parameters: (1) the function to
create a GUI for (2) the desired input components and (3) the desired output
components. Additional parameters can be used to control the appearance and
behavior of the demo.
|
Description
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
import gradio as gr
def image_classifier(inp):
return {'cat': 0.3, 'dog': 0.7}
demo = gr.Interface(fn=image_classifier, inputs="image", outputs="label")
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
Parameters ▼
fn: Callable
the function to wrap an interface around. 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: str | Component | list[str | Component] | None
a single Gradio component, or list of Gradio components. Components can either
be passed as instantiated objects, or referred to by their string shortcuts.
The number of input components should match the number of parameters in fn. If
set to None, then only the output components will be displayed.
outputs: str | Component | list[str | Component] | None
a single Gradio component, or list of Gradio components. Components can either
be passed as instantiated objects, or referred to by their string shortcuts.
The number of output components should match the number of values returned by
fn. If set to None, then only the input components will be displayed.
examples: list[Any] | list[list[Any]] | str | None
default `= None`
sample inputs for the function; if provided, appear below the UI components
and can be clicked to populate the interface. 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.
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
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
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 defaults to True (as long as `fn` and `outputs` are
also provided). 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 cached at app launch. If None, will use the GRADIO_CACHE_MODE environment
variable if defined, or default to "eager". In HuggingFace Spaces, this
parameter defaults to "eager" except for ZeroGPU Spaces, in which case it
defaults to "lazy".
examples_per_page: int
default `= 10`
if examples are provided, how many to display per page.
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.
preload_example: int | Literal[False]
default `= False`
If an integer is provided (and examples are being cached), 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.
live: bool
default `= False`
whether the interface should automatically rerun if any of the inputs change.
title: str | I18nData | None
default `= None`
a title for the interface; if provided, appears above the input and output
components in large font. Also used as the tab title when opened in a browser
window.
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
I18nData | None
default `= None`
a title for the interface; if provided, appears above the input and output
components in large font. Also used as the tab title when opened in a browser
window.
description: str | None
default `= None`
a description for the interface; if provided, appears above the input and
output components and beneath the title in regular font. Accepts Markdown and
HTML content.
article: str | None
default `= None`
an expanded article explaining the interface; if provided, appears below the
input and output components in regular font. Accepts Markdown and HTML
content. If it is an HTTP(S) link to a downloadable remote file, the content
of this file is displayed.
theme: Theme | str | None
default `= None`
a Theme object or a string representing a theme. If a string, will look for a
built-in theme with that name (e.g. "soft" or "default"), or will attempt to
load a theme from the Hugging Face Hub (e.g. "gradio/monochrome"). If None,
will use the Default theme.
flagging_mode: Literal['never'] | Literal['auto'] | Literal['manual'] | None
default `= None`
one of "never", "auto", or "manual". If "never" or "auto", users will not see
a button to flag an input and output. If "manual", users will see a button to
flag. If "auto", every input the user submits will be automatically flagged,
along with the generated output. If "manual", both the input and outputs are
flagged when the user clicks flag button. This parameter can be set with
environmental variable GRADIO_FLAGGING_MODE; otherwise defaults to "manual".
flagging_options: list[str] | list[tuple[str, str]] | None
default `= None`
if provided, allows user to select from the list of options when flagging.
Only applies if flagging_mode is "manual". Can either be a list of tuples of
the form (label, value), where label is the string that will be displayed on
the button and value is the string that will be stored i
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
es if flagging_mode is "manual". Can either be a list of tuples of
the form (label, value), where label is the string that will be displayed on
the button and value is the string that will be stored in the flagging CSV; or
it can be a list of strings ["X", "Y"], in which case the values will be the
list of strings and the labels will ["Flag as X", "Flag as Y"], etc.
flagging_dir: str
default `= ".gradio/flagged"`
path to the directory where flagged data is stored. If the directory does not
exist, it will be created.
flagging_callback: FlaggingCallback | None
default `= None`
either None or an instance of a subclass of FlaggingCallback which will be
called when a sample is flagged. If set to None, an instance of
gradio.flagging.CSVLogger will be created and logs will be saved to a local
CSV file in flagging_dir. Default to None.
analytics_enabled: bool | None
default `= None`
whether to allow basic telemetry. If None, will use GRADIO_ANALYTICS_ENABLED
environment variable if defined, or default to True.
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`
the maximum number of inputs to batch together if this is called from the
queue (only relevant if batch=True)
show_api: bool
default `= True`
whether to show the prediction endpoint in the "view API" page of the Gradio
app, or in the ".view_api()" method of the Gradio clients. Unlike setting
api_name to False, setting show_api to False will still allow downstream apps
as well as the Clients to use this event.
a
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
the ".view_api()" method of the Gradio clients. Unlike setting
api_name to False, setting show_api to False will still allow downstream apps
as well as the Clients to use this event.
api_name: str | Literal[False] | None
default `= "predict"`
defines how the prediction endpoint appears in the API docs. Can be a string,
None, or False. If set to a string, the endpoint will be exposed in the API
docs with the given name. If None, the name of the prediction function will be
used as the API endpoint. If False, the endpoint will not be exposed in the
API docs and downstream apps (including those that `gr.load` this app) will
not be able to use this prediction 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.
allow_duplication: bool
default `= False`
if True, then will show a 'Duplicate Spaces' button on Hugging Face Spaces.
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
`.queue()`, which itself is 1 by default).
css: str | None
default `= None`
Custom css as a code string. This css will be included in the demo webpage.
css_paths: str | Path | list[str | Path] | None
default `= None`
Custom css as a pathlib.Path to a css file or a list of such paths. This css
files will be read, concatenated, and included in the demo webpage
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
str | Path | list[str | Path] | None
default `= None`
Custom css as a pathlib.Path to a css file or a list of such paths. This css
files will be read, concatenated, and included in the demo webpage. If the
`css` parameter is also set, the css from `css` will be included first.
js: str | Literal[True] | None
default `= None`
Custom js as a code string. The custom js should be in the form of a single js
function. This function will automatically be executed when the page loads.
For more flexibility, use the head parameter to insert js inside <script>
tags.
head: str | None
default `= None`
Custom html code to insert into the head of the demo webpage. This can be used
to add custom meta tags, multiple scripts, stylesheets, etc. to the page.
head_paths: str | Path | list[str | Path] | None
default `= None`
Custom html code as a pathlib.Path to a html file or a list of such paths.
This html files will be read, concatenated, and included in the head of the
demo webpage. If the `head` parameter is also set, the html from `head` will
be included first.
additional_inputs: str | Component | list[str | Component] | None
default `= None`
a single Gradio component, or list of Gradio components. Components can either
be passed as instantiated objects, or referred to by their string shortcuts.
These components will be rendered in an accordion below the main input
components. By default, no additional input components will be displayed.
additional_inputs_accordion: str | Accordion | None
default `= None`
if a string is provided, this is the label of the `gr.Accordion` to use to
contain additional inputs. A `gr.Accordion` object can be provided as well to
configure other properties of the container holding the additional inputs.
Defaults to a `gr.Accordion(label="Additional Inputs", open=False)`. This
parameter is only used if `additional_inputs` is provided.
submit_btn: str
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
ner holding the additional inputs.
Defaults to a `gr.Accordion(label="Additional Inputs", open=False)`. This
parameter is only used if `additional_inputs` is provided.
submit_btn: str | Button
default `= "Submit"`
the button to use for submitting inputs. Defaults to a `gr.Button("Submit",
variant="primary")`. This parameter does not apply if the Interface is output-
only, in which case the submit button always displays "Generate". Can be set
to a string (which becomes the button label) or a `gr.Button` object (which
allows for more customization).
stop_btn: str | Button
default `= "Stop"`
the button to use for stopping the interface. Defaults to a `gr.Button("Stop",
variant="stop", visible=False)`. Can be set to a string (which becomes the
button label) or a `gr.Button` object (which allows for more customization).
clear_btn: str | Button | None
default `= "Clear"`
the button to use for clearing the inputs. Defaults to a `gr.Button("Clear",
variant="secondary")`. Can be set to a string (which becomes the button label)
or a `gr.Button` object (which allows for more customization). Can be set to
None, which hides the button.
delete_cache: tuple[int, int] | None
default `= None`
a tuple corresponding [frequency, age] both expressed in number of seconds.
Every `frequency` seconds, the temporary files created by this Blocks instance
will be deleted if more than `age` seconds have passed since the file was
created. For example, setting this to (86400, 86400) will delete temporary
files every day. The cache will be deleted entirely when the server restarts.
If None, no cache deletion will occur.
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, "hid
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
s 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
fill_width: bool
default `= False`
whether to horizontally expand to fill container fully. If False, centers and
constrains app to a maximum width.
allow_flagging: Literal['never'] | Literal['auto'] | Literal['manual'] | None
default `= None`
time_limit: int | None
default `= 30`
The time limit for the stream to run. Default is 30 seconds. Parameter only
used for streaming images or audio if the interface is live and the input
components are set to "streaming=True".
stream_every: float
default `= 0.5`
The latency (in seconds) at which stream chunks are sent to the backend.
Defaults to 0.5 seconds. Parameter only used for streaming images or audio if
the interface is live and the input components are set to "streaming=True".
deep_link: str | DeepLinkButton | bool | None
default `= None`
a string or `gr.DeepLinkButton` object that creates a unique URL you can use
to share your app and all components **as they currently are** with others.
Automatically enabled on Hugging Face Spaces unless explicitly set to False.
validator: Callable | None
default `= None`
a function that takes in the inputs and can optionally return a gr.validate()
object for each input.
|
Initialization
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
hello_worldhello_world_2hello_world_3
Open in 🎢 ↗ import gradio as gr def greet(name): return "Hello " + name + "!"
demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox") if __name__
== "__main__": demo.launch()
import gradio as gr
def greet(name):
return "Hello " + name + "!"
demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox")
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import gradio as gr def greet(name, intensity): return "Hello, " +
name + "!" * intensity demo = gr.Interface( fn=greet, inputs=["text",
gr.Slider(value=2, minimum=1, maximum=10, step=1)],
outputs=[gr.Textbox(label="greeting", lines=3)], ) if __name__ == "__main__":
demo.launch()
import gradio as gr
def greet(name, intensity):
return "Hello, " + name + "!" * intensity
demo = gr.Interface(
fn=greet,
inputs=["text", gr.Slider(value=2, minimum=1, maximum=10, step=1)],
outputs=[gr.Textbox(label="greeting", lines=3)],
)
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import gradio as gr def greet(name, is_morning, temperature):
salutation = "Good morning" if is_morning else "Good evening" greeting =
f"{salutation} {name}. It is {temperature} degrees today" celsius =
(temperature - 32) * 5 / 9 return greeting, round(celsius, 2) demo =
gr.Interface( fn=greet, inputs=["text", "checkbox", gr.Slider(0, 100)],
outputs=["text", "number"], ) if __name__ == "__main__": demo.launch()
import gradio as gr
def greet(name, is_morning, temperature):
salutation = "Good morning" if is_morning else "Good evening"
greeting = f"{salutation} {name}. It is {temperature} degrees today"
celsius = (temperature - 32) * 5 / 9
return greeting, round(celsius, 2)
demo = gr.Interface(
fn=greet,
inputs=["text", "checkbox", gr.Slider(0, 10
|
Demos
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
grees today"
celsius = (temperature - 32) * 5 / 9
return greeting, round(celsius, 2)
demo = gr.Interface(
fn=greet,
inputs=["text", "checkbox", gr.Slider(0, 100)],
outputs=["text", "number"],
)
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
Methods
|
https://gradio.app/docs/gradio/interface
|
Gradio - Interface Docs
|
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