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Set the static paths to be served by the gradio app.
Static files are are served directly from the file system instead of being
copied. They are served to users with The Content-Disposition HTTP header set
to "inline" when sending these files to users. This indicates that the file
should be displayed directly in the browser window if possible. This function
is useful when you want to serve files that you know will not be modified
during the lifetime of the gradio app (like files used in gr.Examples). By
setting static paths, your app will launch faster and it will consume less
disk space. Calling this function will set the static paths for all gradio
applications defined in the same interpreter session until it is called again
or the session ends.
|
Description
|
https://gradio.app/docs/gradio/set_static_paths
|
Gradio - Set_Static_Paths Docs
|
import gradio as gr
Paths can be a list of strings or pathlib.Path objects
corresponding to filenames or directories.
gr.set_static_paths(paths=["test/test_files/"])
The example files and the default value of the input
will not be copied to the gradio cache and will be served directly.
demo = gr.Interface(
lambda s: s.rotate(45),
gr.Image(value="test/test_files/cheetah1.jpg", type="pil"),
gr.Image(),
examples=["test/test_files/bus.png"],
)
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/set_static_paths
|
Gradio - Set_Static_Paths Docs
|
Parameters ▼
paths: str | Path | list[str | Path]
filepath or list of filepaths or directory names to be served by the gradio
app. If it is a directory name, ALL files located within that directory will
be considered static and not moved to the gradio cache. This also means that
ALL files in that directory will be accessible over the network.
|
Initialization
|
https://gradio.app/docs/gradio/set_static_paths
|
Gradio - Set_Static_Paths Docs
|
The gr.SelectData class is a subclass of gr.EventData that specifically
carries information about the `.select()` event. When gr.SelectData is added
as a type hint to an argument of an event listener method, a gr.SelectData
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/selectdata
|
Gradio - Selectdata Docs
|
import gradio as gr
with gr.Blocks() as demo:
table = gr.Dataframe([[1, 2, 3], [4, 5, 6]])
gallery = gr.Gallery([("cat.jpg", "Cat"), ("dog.jpg", "Dog")])
textbox = gr.Textbox("Hello World!")
statement = gr.Textbox()
def on_select(evt: gr.SelectData):
return f"You selected {evt.value} at {evt.index} from {evt.target}"
table.select(on_select, None, statement)
gallery.select(on_select, None, statement)
textbox.select(on_select, None, statement)
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/selectdata
|
Gradio - Selectdata Docs
|
Parameters ▼
index: int | tuple[int, int]
The index of the selected item. Is a tuple if the component is two dimensional
or selection is a range.
value: Any
The value of the selected item.
row_value: list[float | str]
The value of the entire row that the selected item belongs to, as a 1-D list.
Only implemented for the `Dataframe` component, returns None for other
components.
col_value: list[float | str]
The value of the entire column that the selected item belongs to, as a 1-D
list. Only implemented for the `Dataframe` component, returns None for other
components.
selected: bool
True if the item was selected, False if deselected.
|
Attributes
|
https://gradio.app/docs/gradio/selectdata
|
Gradio - Selectdata Docs
|
gallery_selectionstictactoe
Open in 🎢 ↗ import gradio as gr import numpy as np with gr.Blocks() as demo:
imgs = gr.State() gallery = gr.Gallery(allow_preview=False) def
deselect_images(): return gr.Gallery(selected_index=None) def
generate_images(): images = [] for _ in range(9): image = np.ones((100, 100,
3), dtype=np.uint8) * np.random.randint( 0, 255, 3 ) image is a solid single
color images.append(image) return images, images demo.load(generate_images,
None, [gallery, imgs]) with gr.Row(): selected = gr.Number(show_label=False)
darken_btn = gr.Button("Darken selected") deselect_button =
gr.Button("Deselect") deselect_button.click(deselect_images, None, gallery)
def get_select_index(evt: gr.SelectData): return evt.index
gallery.select(get_select_index, None, selected) def darken_img(imgs, index):
index = int(index) imgs[index] = np.round(imgs[index] * 0.8).astype(np.uint8)
return imgs, imgs darken_btn.click(darken_img, [imgs, selected], [imgs,
gallery]) if __name__ == "__main__": demo.launch()
import gradio as gr
import numpy as np
with gr.Blocks() as demo:
imgs = gr.State()
gallery = gr.Gallery(allow_preview=False)
def deselect_images():
return gr.Gallery(selected_index=None)
def generate_images():
images = []
for _ in range(9):
image = np.ones((100, 100, 3), dtype=np.uint8) * np.random.randint(
0, 255, 3
) image is a solid single color
images.append(image)
return images, images
demo.load(generate_images, None, [gallery, imgs])
with gr.Row():
selected = gr.Number(show_label=False)
darken_btn = gr.Button("Darken selected")
deselect_button = gr.Button("Deselect")
deselect_button.click(deselect_images, None, gallery)
def get_select_index(evt: gr.SelectData):
return evt.index
|
Demos
|
https://gradio.app/docs/gradio/selectdata
|
Gradio - Selectdata Docs
|
deselect_button = gr.Button("Deselect")
deselect_button.click(deselect_images, None, gallery)
def get_select_index(evt: gr.SelectData):
return evt.index
gallery.select(get_select_index, None, selected)
def darken_img(imgs, index):
index = int(index)
imgs[index] = np.round(imgs[index] * 0.8).astype(np.uint8)
return imgs, imgs
darken_btn.click(darken_img, [imgs, selected], [imgs, gallery])
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import gradio as gr with gr.Blocks() as demo: turn =
gr.Textbox("X", interactive=False, label="Turn") board =
gr.Dataframe(value=[["", "", ""]] * 3, interactive=False, type="array") def
place(board: list[list[int]], turn, evt: gr.SelectData): if evt.value: return
board, turn board[evt.index[0]][evt.index[1]] = turn turn = "O" if turn == "X"
else "X" return board, turn board.select(place, [board, turn], [board, turn],
show_progress="hidden") if __name__ == "__main__": demo.launch()
import gradio as gr
with gr.Blocks() as demo:
turn = gr.Textbox("X", interactive=False, label="Turn")
board = gr.Dataframe(value=[["", "", ""]] * 3, interactive=False, type="array")
def place(board: list[list[int]], turn, evt: gr.SelectData):
if evt.value:
return board, turn
board[evt.index[0]][evt.index[1]] = turn
turn = "O" if turn == "X" else "X"
return board, turn
board.select(place, [board, turn], [board, turn], show_progress="hidden")
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/selectdata
|
Gradio - Selectdata 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.
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Event Listeners
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https://gradio.app/docs/gradio/slider
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Gradio - Slider Docs
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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
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Event Listeners
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https://gradio.app/docs/gradio/slider
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Gradio - Slider Docs
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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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Event Listeners
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https://gradio.app/docs/gradio/slider
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Gradio - Slider Docs
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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
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https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue Docs
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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
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https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue Docs
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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
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Initialization
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https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue Docs
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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.
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Initialization
|
https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue 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
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Initialization
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https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue 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 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.
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Initialization
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https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue Docs
|
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.
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 web
|
Initialization
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
ths: 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:
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Initialization
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
ntainer 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,
|
Initialization
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
gress 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#interface-queue
|
Gradio - Interface#Interface Queue 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
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Demos
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https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue 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
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https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue Docs
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Methods
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https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue Docs
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|
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gradio.Interface.launch(···)
Description
%20Copyright%202022%20Fonticons,%20Inc.
|
launch
|
https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue Docs
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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)
Launches a simple web server that serves the demo. Can also be used to create
a public link used by anyone to access the demo from their browser by setting
share=True.
Example Usage
%20Copyright%202022%20Fonticons,
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2'%3e%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)
import gradio as gr
def reverse(text):
return text[::-1]
demo = gr.Interface(reverse, "text", "text")
demo.launch(share=True, auth=("username", "password"))
Parameters ▼
inline: bool | None
default `= None`
whether to display in the gradio app inline in an iframe. Defaults to True in
python notebooks; False otherwise.
inbrowser: bool
default `= False`
whether to automatically launch the gradio app in a new tab on the de
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pp inline in an iframe. Defaults to True in
python notebooks; False otherwise.
inbrowser: bool
default `= False`
whether to automatically launch the gradio app in a new tab on the default
browser.
share: bool | None
default `= None`
whether to create a publicly shareable link for the gradio app. Creates an SSH
tunnel to make your UI accessible from anywhere. If not provided, it is set to
False by default every time, except when running in Google Colab. When
localhost is not accessible (e.g. Google Colab), setting share=False is not
supported. Can be set by environment variable GRADIO_SHARE=True.
debug: bool
default `= False`
if True, blocks the main thread from running. If running in Google Colab, this
is needed to print the errors in the cell output.
max_threads: int
default `= 40`
the maximum number of total threads that the Gradio app can generate in
parallel. The default is inherited from the starlette library (currently 40).
auth: Callable[[str, str], bool] | tuple[str, str] | list[tuple[str, str]] | None
default `= None`
If provided, username and password (or list of username-password tuples)
required to access app. Can also provide function that takes username and
password and returns True if valid login.
auth_message: str | None
default `= None`
If provided, HTML message provided on login page.
prevent_thread_lock: bool
default `= False`
By default, the gradio app blocks the main thread while the server is running.
If set to True, the gradio app will not block and the gradio server will
terminate as soon as the script finishes.
show_error: bool
default `= False`
If True, any errors in the gradio app will be displayed in an alert modal and
printed in the browser console log. They will also be displayed in the alert
modal of downstream apps that gr.load() this app.
server_name: str | None
default `= No
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an alert modal and
printed in the browser console log. They will also be displayed in the alert
modal of downstream apps that gr.load() this app.
server_name: str | None
default `= None`
to make app accessible on local network, set this to "0.0.0.0". Can be set by
environment variable GRADIO_SERVER_NAME. If None, will use "127.0.0.1".
server_port: int | None
default `= None`
will start gradio app on this port (if available). Can be set by environment
variable GRADIO_SERVER_PORT. If None, will search for an available port
starting at 7860.
height: int
default `= 500`
The height in pixels of the iframe element containing the gradio app (used if
inline=True)
width: int | str
default `= "100%"`
The width in pixels of the iframe element containing the gradio app (used if
inline=True)
favicon_path: str | Path | None
default `= None`
If a path to a file (.png, .gif, or .ico) is provided, it will be used as the
favicon for the web page.
ssl_keyfile: str | None
default `= None`
If a path to a file is provided, will use this as the private key file to
create a local server running on https.
ssl_certfile: str | None
default `= None`
If a path to a file is provided, will use this as the signed certificate for
https. Needs to be provided if ssl_keyfile is provided.
ssl_keyfile_password: str | None
default `= None`
If a password is provided, will use this with the ssl certificate for https.
ssl_verify: bool
default `= True`
If False, skips certificate validation which allows self-signed certificates
to be used.
quiet: bool
default `= False`
If True, suppresses most print statements.
show_api: bool
default `= True`
If True, shows the api docs in the footer of the app. Default True.
allowed_paths: list[str] | None
default `= None`
List of complete filepaths or parent di
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: bool
default `= True`
If True, shows the api docs in the footer of the app. Default True.
allowed_paths: list[str] | None
default `= None`
List of complete filepaths or parent directories that gradio is allowed to
serve. Must be absolute paths. Warning: if you provide directories, any files
in these directories or their subdirectories are accessible to all users of
your app. Can be set by comma separated environment variable
GRADIO_ALLOWED_PATHS. These files are generally assumed to be secure and will
be displayed in the browser when possible.
blocked_paths: list[str] | None
default `= None`
List of complete filepaths or parent directories that gradio is not allowed to
serve (i.e. users of your app are not allowed to access). Must be absolute
paths. Warning: takes precedence over `allowed_paths` and all other
directories exposed by Gradio by default. Can be set by comma separated
environment variable GRADIO_BLOCKED_PATHS.
root_path: str | None
default `= None`
The root path (or "mount point") of the application, if it's not served from
the root ("/") of the domain. Often used when the application is behind a
reverse proxy that forwards requests to the application. For example, if the
application is served at "https://example.com/myapp", the `root_path` should
be set to "/myapp". A full URL beginning with http:// or https:// can be
provided, which will be used as the root path in its entirety. Can be set by
environment variable GRADIO_ROOT_PATH. Defaults to "".
app_kwargs: dict[str, Any] | None
default `= None`
Additional keyword arguments to pass to the underlying FastAPI app as a
dictionary of parameter keys and argument values. For example, `{"docs_url":
"/docs"}`
state_session_capacity: int
default `= 10000`
The maximum number of sessions whose information to store in memory. If the
number of sessions exceeds this number, the oldest sessions will be removed.
Reduce capac
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_capacity: int
default `= 10000`
The maximum number of sessions whose information to store in memory. If the
number of sessions exceeds this number, the oldest sessions will be removed.
Reduce capacity to reduce memory usage when using gradio.State or returning
updated components from functions. Defaults to 10000.
share_server_address: str | None
default `= None`
Use this to specify a custom FRP server and port for sharing Gradio apps (only
applies if share=True). If not provided, will use the default FRP server at
https://gradio.live. See https://github.com/huggingface/frp for more
information.
share_server_protocol: Literal['http', 'https'] | None
default `= None`
Use this to specify the protocol to use for the share links. Defaults to
"https", unless a custom share_server_address is provided, in which case it
defaults to "http". If you are using a custom share_server_address and want to
use https, you must set this to "https".
share_server_tls_certificate: str | None
default `= None`
The path to a TLS certificate file to use when connecting to a custom share
server. This parameter is not used with the default FRP server at
https://gradio.live. Otherwise, you must provide a valid TLS certificate file
(e.g. a "cert.pem") relative to the current working directory, or the
connection will not use TLS encryption, which is insecure.
auth_dependency: Callable[[fastapi.Request], str | None] | None
default `= None`
A function that takes a FastAPI request and returns a string user ID or None.
If the function returns None for a specific request, that user is not
authorized to access the app (they will see a 401 Unauthorized response). To
be used with external authentication systems like OAuth. Cannot be used with
`auth`.
max_file_size: str | int | None
default `= None`
The maximum file size in bytes that can be uploaded. Can be a string of the
form "<value><unit>", where value is any
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ed with
`auth`.
max_file_size: str | int | None
default `= None`
The maximum file size in bytes that can be uploaded. Can be a string of the
form "<value><unit>", where value is any positive integer and unit is one of
"b", "kb", "mb", "gb", "tb". If None, no limit is set.
enable_monitoring: bool | None
default `= None`
Enables traffic monitoring of the app through the /monitoring endpoint. By
default is None, which enables this endpoint. If explicitly True, will also
print the monitoring URL to the console. If False, will disable monitoring
altogether.
strict_cors: bool
default `= True`
If True, prevents external domains from making requests to a Gradio server
running on localhost. If False, allows requests to localhost that originate
from localhost but also, crucially, from "null". This parameter should
normally be True to prevent CSRF attacks but may need to be False when
embedding a *locally-running Gradio app* using web components.
node_server_name: str | None
default `= None`
node_port: int | None
default `= None`
ssr_mode: bool | None
default `= None`
If True, the Gradio app will be rendered using server-side rendering mode,
which is typically more performant and provides better SEO, but this requires
Node 20+ to be installed on the system. If False, the app will be rendered
using client-side rendering mode. If None, will use GRADIO_SSR_MODE
environment variable or default to False.
pwa: bool | None
default `= None`
If True, the Gradio app will be set up as an installable PWA (Progressive Web
App). If set to None (default behavior), then the PWA feature will be enabled
if this Gradio app is launched on Spaces, but not otherwise.
mcp_server: bool | None
default `= None`
If True, the Gradio app will be set up as an MCP server and documented
functions will be added as MCP tools. If None (default behavior), then the
GRADIO_M
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mcp_server: bool | None
default `= None`
If True, the Gradio app will be set up as an MCP server and documented
functions will be added as MCP tools. If None (default behavior), then the
GRADIO_MCP_SERVER environment variable will be used to determine if the MCP
server should be enabled (which is "True" on Hugging Face Spaces).
i18n: I18n | None
default `= None`
An I18n instance containing custom translations, which are used to translate
strings in our components (e.g. the labels of components or Markdown strings).
This feature can only be used to translate static text in the frontend, not
values in the backend.
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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.Interface.load(block, ···)
Description
%20Copyright%202022%20Fonticons,%2
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%3e%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 Interface initially loads in the browser.
Parameters ▼
block: Block | None
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 correspondin
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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 which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime
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w the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click met
|
load
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
f 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,
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 w
|
load
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
ew_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.
|
load
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue 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.Interface.from_pipeline(pipeline, ···)
Description
%20Copyright%202022%20
|
from_pipeline
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
20640%20512'%3e%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)
Class method that constructs an Interface from a Hugging Face
transformers.Pipeline or diffusers.DiffusionPipeline object. The input and
output components are automatically determined from the pipeline.
Example Usage
%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)
import gradio as gr
from transformers import pipeline
pipe = pipeline("image-classification")
gr.Interface.from_pipeline(pipe).launch()
Parameters ▼
pipeline: Pipeline | DiffusionPipeline
the pipeline object to use.
|
from_pipeline
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
ne object to use.
|
from_pipeline
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue 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.Interface.integrate(···)
Description
%20Copyright%202022%20Fonticons,%20I
|
integrate
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
e%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)
A catch-all method for integrating with other libraries. This method should be
run after launch()
Parameters ▼
comet_ml: <class 'inspect._empty'>
default `= None`
If a comet_ml Experiment object is provided, will integrate with the
experiment and appear on Comet dashboard
wandb: ModuleType | None
default `= None`
If the wandb module is provided, will integrate with it and appear on WandB
dashboard
mlflow: ModuleType | None
default `= None`
|
integrate
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
wandb: ModuleType | None
default `= None`
If the wandb module is provided, will integrate with it and appear on WandB
dashboard
mlflow: ModuleType | None
default `= None`
If the mlflow module is provided, will integrate with the experiment and
appear on ML Flow dashboard
|
integrate
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue 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.Interface.queue(···)
Description
%20Copyright%202022%20Fonticons,%20Inc.%
|
queue
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue 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)
By enabling the queue you can control when users know their position in the
queue, and set a limit on maximum number of events allowed.
Example Usage
%20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.
|
queue
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
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demo = gr.Interface(image_generator, gr.Textbox(), gr.Image())
demo.queue(max_size=20)
demo.launch()
Parameters ▼
status_update_rate: float | Literal['auto']
default `= "auto"`
If "auto", Queue will send status estimations to all clients whenever a job is
finished. Otherwise Queue will send status at regular intervals set by this
parameter as the number of seconds.
api_open: bool | None
default `= None`
If True, the REST routes of the backend will be open, allowin
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queue
|
https://gradio.app/docs/gradio/interface#interface-queue
|
Gradio - Interface#Interface Queue Docs
|
send status at regular intervals set by this
parameter as the number of seconds.
api_open: bool | None
default `= None`
If True, the REST routes of the backend will be open, allowing requests made
directly to those endpoints to skip the queue.
max_size: int | None
default `= None`
The maximum number of events the queue will store at any given moment. If the
queue is full, new events will not be added and a user will receive a message
saying that the queue is full. If None, the queue size will be unlimited.
default_concurrency_limit: int | None | Literal['not_set']
default `= "not_set"`
The default value of `concurrency_limit` to use for event listeners that don't
specify a value. Can be set by environment variable
GRADIO_DEFAULT_CONCURRENCY_LIMIT. Defaults to 1 if not set otherwise.
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queue
|
https://gradio.app/docs/gradio/interface#interface-queue
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Gradio - Interface#Interface Queue 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
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https://gradio.app/docs/gradio/keyupdata
|
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()
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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()
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Demos
|
https://gradio.app/docs/gradio/keyupdata
|
Gradio - Keyupdata Docs
|
Creates a navigation bar component for multipage Gradio apps. The navbar
component allows customizing the appearance of the navbar for that page. Only
one Navbar component can exist per page in a Blocks app, and it can be placed
anywhere within the page.
The Navbar component is designed to control the appearance of the navigation
bar in multipage applications. When present in a Blocks app, its properties
override the default navbar behavior.
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Description
|
https://gradio.app/docs/gradio/navbar
|
Gradio - Navbar Docs
|
**As input component** : The preprocessed input data sent to the user's
function in the backend.
Your function should accept one of these types:
def predict(
value: list[tuple[str, str]] | None
)
...
**As output component** : The output data received by the component from
the user's function in the backend.
Your function should return one of these types:
def predict(···) -> list[tuple[str, str]] | None
...
return value
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Behavior
|
https://gradio.app/docs/gradio/navbar
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Gradio - Navbar Docs
|
Parameters ▼
value: list[tuple[str, str]] | None
default `= None`
If a list of tuples of (page_name, page_path) are provided, these additional
pages will be added to the navbar alongside the existing pages defined in the
Blocks app. The page_path can be either a relative path for internal Gradio
app pages (e.g., "analytics") or an absolute URL for external links (e.g.,
"https://twitter.com/username"). Otherwise, only the pages defined using the
`Blocks.route` method will be displayed. Example: [("Dashboard", "dashboard"),
("About", "https://twitter.com/abidlabs")]
visible: bool
default `= True`
If True, the navbar will be visible. If False, the navbar will be hidden.
main_page_name: str | Literal[False]
default `= "Home"`
The title to display in the navbar for the main page of the Gradio. If False,
the main page will not be displayed in the navbar.
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional list of strings that are assigned as the classes of this component
in the HTML DOM. Can be used for targeting CSS styles.
render: bool
default `= True`
If False, component will not render be rendered in the Blocks context. Should
be used if the intention is to assign event listeners now but render the
component later.
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component.
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Initialization
|
https://gradio.app/docs/gradio/navbar
|
Gradio - Navbar Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.Navbar` | "navbar" | Uses default values
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Shortcuts
|
https://gradio.app/docs/gradio/navbar
|
Gradio - Navbar 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 Navbar component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`Navbar.change(fn, ···)` | Triggered when the value of the Navbar changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.
Event Parameters
Parameters ▼
fn: Callable | None | Literal['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of t
|
Event Listeners
|
https://gradio.app/docs/gradio/navbar
|
Gradio - Navbar Docs
|
efines 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`
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
|
Event Listeners
|
https://gradio.app/docs/gradio/navbar
|
Gradio - Navbar Docs
|
e, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of value
|
Event Listeners
|
https://gradio.app/docs/gradio/navbar
|
Gradio - Navbar Docs
|
r | 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 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.valid
|
Event Listeners
|
https://gradio.app/docs/gradio/navbar
|
Gradio - Navbar Docs
|
ll 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/navbar
|
Gradio - Navbar Docs
|
This class allows you to pass custom error messages to the user. You can do
so by raising a gr.Error("custom message") anywhere in the code, and when that
line is executed the custom message will appear in a modal on the demo.
You can control for how long the error message is displayed with the
`duration` parameter. If it’s `None`, the message will be displayed forever
until the user closes it. If it’s a number, it will be shown for that many
seconds.
You can also hide the error modal from being shown in the UI by setting
`visible=False`.
Below is a demo of how different values of duration control the error,
info, and warning messages. You can see the code
[here](https://huggingface.co/spaces/freddyaboulton/gradio-error-
duration/blob/244331cf53f6b5fa2fd406ece3bf55c6ccb9f5f2/app.pyL17).
|
Description
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
import gradio as gr
def divide(numerator, denominator):
if denominator == 0:
raise gr.Error("Cannot divide by zero!")
gr.Interface(divide, ["number", "number"], "number").launch()
|
Example Usage
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
Parameters ▼
message: str
default `= "Error raised."`
The error message to be displayed to the user. Can be HTML, which will be
rendered in the modal.
duration: float | None
default `= 10`
The duration in seconds to display the error message. If None or 0, the error
message will be displayed until the user closes it.
visible: bool
default `= True`
Whether the error message should be displayed in the UI.
title: str
default `= "Error"`
The title to be displayed to the user at the top of the error modal.
print_exception: bool
default `= True`
Whether to print traceback of the error to the console when the error is
raised.
|
Initialization
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
calculatorblocks_chained_events
Open in 🎢 ↗ import gradio as gr def calculator(num1, operation, num2): if
operation == "add": return num1 + num2 elif operation == "subtract": return
num1 - num2 elif operation == "multiply": return num1 * num2 elif operation ==
"divide": if num2 == 0: raise gr.Error("Cannot divide by zero!") return num1 /
num2 demo = gr.Interface( calculator, [ "number", gr.Radio(["add", "subtract",
"multiply", "divide"]), "number" ], "number", examples=[ [45, "add", 3],
[3.14, "divide", 2], [144, "multiply", 2.5], [0, "subtract", 1.2], ],
title="Toy Calculator", description="Here's a sample toy calculator.", ) if
__name__ == "__main__": demo.launch()
import gradio as gr
def calculator(num1, operation, num2):
if operation == "add":
return num1 + num2
elif operation == "subtract":
return num1 - num2
elif operation == "multiply":
return num1 * num2
elif operation == "divide":
if num2 == 0:
raise gr.Error("Cannot divide by zero!")
return num1 / num2
demo = gr.Interface(
calculator,
[
"number",
gr.Radio(["add", "subtract", "multiply", "divide"]),
"number"
],
"number",
examples=[
[45, "add", 3],
[3.14, "divide", 2],
[144, "multiply", 2.5],
[0, "subtract", 1.2],
],
title="Toy Calculator",
description="Here's a sample toy calculator.",
)
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import gradio as gr def failure(): raise gr.Error("This should
fail!") def exception(): raise ValueError("Something went wrong") def
success(): return True def warning_fn(): gr.Warning("This is a warning!") def
info_fn(): gr.Info("This is some info") with gr.Blocks() as demo:
gr.Markdown("Used in E2E tests of success event trigger. The then event
covered
|
Demos
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
def warning_fn(): gr.Warning("This is a warning!") def
info_fn(): gr.Info("This is some info") with gr.Blocks() as demo:
gr.Markdown("Used in E2E tests of success event trigger. The then event
covered in chatbot E2E tests." " Also testing that the status modals show
up.") with gr.Row(): result = gr.Textbox(label="Result") result_2 =
gr.Textbox(label="Consecutive Event") result_failure =
gr.Textbox(label="Failure Event") with gr.Row(): success_btn =
gr.Button(value="Trigger Success") success_btn_2 = gr.Button(value="Trigger
Consecutive Success") failure_btn = gr.Button(value="Trigger Failure")
failure_exception = gr.Button(value="Trigger Failure With ValueError") with
gr.Row(): trigger_warning = gr.Button(value="Trigger Warning") trigger_info =
gr.Button(value="Trigger Info") success_btn_2.click(success, None,
None).success(lambda: "First Event Trigered", None, result).success(lambda:
"Consecutive Event Triggered", None, result_2) success_event =
success_btn.click(success, None, None) success_event.success(lambda: "Success
event triggered", inputs=None, outputs=result) success_event.failure(lambda:
"Should not be triggered", inputs=None, outputs=result_failure) failure_event
= failure_btn.click(failure, None, None) failure_event.success(lambda: "Should
not be triggered", inputs=None, outputs=result) failure_event.failure(lambda:
"Failure event triggered", inputs=None, outputs=result_failure)
failure_exception.click(exception, None, None)
trigger_warning.click(warning_fn, None, None) trigger_info.click(info_fn,
None, None) if __name__ == "__main__": demo.launch(show_error=True)
import gradio as gr
def failure():
raise gr.Error("This should fail!")
def exception():
raise ValueError("Something went wrong")
def success():
return True
def warning_fn():
gr.Warning("This is a warning!")
def info_fn():
gr.Info("This is some info")
with gr.Blocks() as demo:
gr.
|
Demos
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
s():
return True
def warning_fn():
gr.Warning("This is a warning!")
def info_fn():
gr.Info("This is some info")
with gr.Blocks() as demo:
gr.Markdown("Used in E2E tests of success event trigger. The then event covered in chatbot E2E tests."
" Also testing that the status modals show up.")
with gr.Row():
result = gr.Textbox(label="Result")
result_2 = gr.Textbox(label="Consecutive Event")
result_failure = gr.Textbox(label="Failure Event")
with gr.Row():
success_btn = gr.Button(value="Trigger Success")
success_btn_2 = gr.Button(value="Trigger Consecutive Success")
failure_btn = gr.Button(value="Trigger Failure")
failure_exception = gr.Button(value="Trigger Failure With ValueError")
with gr.Row():
trigger_warning = gr.Button(value="Trigger Warning")
trigger_info = gr.Button(value="Trigger Info")
success_btn_2.click(success, None, None).success(lambda: "First Event Trigered", None, result).success(lambda: "Consecutive Event Triggered", None, result_2)
success_event = success_btn.click(success, None, None)
success_event.success(lambda: "Success event triggered", inputs=None, outputs=result)
success_event.failure(lambda: "Should not be triggered", inputs=None, outputs=result_failure)
failure_event = failure_btn.click(failure, None, None)
failure_event.success(lambda: "Should not be triggered", inputs=None, outputs=result)
failure_event.failure(lambda: "Failure event triggered", inputs=None, outputs=result_failure)
failure_exception.click(exception, None, None)
trigger_warning.click(warning_fn, None, None)
trigger_info.click(info_fn, None, None)
if __name__ == "__main__":
demo.launch(show_error=True)
|
Demos
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
trigger_warning.click(warning_fn, None, None)
trigger_info.click(info_fn, None, None)
if __name__ == "__main__":
demo.launch(show_error=True)
|
Demos
|
https://gradio.app/docs/gradio/error
|
Gradio - Error Docs
|
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.
|
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.
|
Attributes
|
https://gradio.app/docs/gradio/editdata
|
Gradio - Editdata Docs
|
Creates an audio component that can be used to upload/record audio (as an
input) or display audio (as an output).
|
Description
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
**As input component** : passes audio as one of these formats (depending on
`type`): a `str` filepath, or `tuple` of (sample rate in Hz, audio data as
numpy array). If the latter, the audio data is a 16-bit `int` array whose
values range from -32768 to 32767 and shape of the audio data array is
(samples,) for mono audio or (samples, channels) for multi-channel audio.
Your function should accept one of these types:
def predict(
value: str | tuple[int, np.ndarray] | None
)
...
**As output component** : expects audio data in any of these formats: a
`str` or `pathlib.Path` filepath or URL to an audio file, or a `bytes` object
(recommended for streaming), or a `tuple` of (sample rate in Hz, audio data as
numpy array). Note: if audio is supplied as a numpy array, the audio will be
normalized by its peak value to avoid distortion or clipping in the resulting
audio.
Your function should return one of these types:
def predict(···) -> str | Path | bytes | tuple[int, np.ndarray] | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
Parameters ▼
value: str | Path | tuple[int, np.ndarray] | Callable | None
default `= None`
A path, URL, or [sample_rate, numpy array] tuple (sample rate in Hz, audio
data as a float or int numpy array) for the default value that Audio component
is going to take. If a function is provided, the function will be called each
time the app loads to set the initial value of this component.
sources: list[Literal['upload', 'microphone']] | Literal['upload', 'microphone'] | None
default `= None`
A list of sources permitted for audio. "upload" creates a box where user can
drop an audio file, "microphone" creates a microphone input. The first element
in the list will be used as the default source. If None, defaults to
["upload", "microphone"], or ["microphone"] if `streaming` is True.
type: Literal['numpy', 'filepath']
default `= "numpy"`
The format the audio file is converted to before being passed into the
prediction function. "numpy" converts the audio to a tuple consisting of: (int
sample rate, numpy.array for the data), "filepath" passes a str path to a
temporary file containing the audio.
label: str | I18nData | None
default `= None`
the label for this component. Appears above the component and is also used as
the header if there are a table of examples for this component. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
every: Timer | float | None
default `= None`
Continously calls `value` to recalculate it if `value` is a function (has no
effect otherwise). Can provide a Timer whose tick resets `value`, or a float
that provides the regular interval for the reset Timer.
inputs: Component | list[Component] | set[Component] | None
default `= None`
Components that are used as inputs to calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
|
Initialization
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
set[Component] | None
default `= None`
Components that are used as inputs to calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
show_label: bool | None
default `= None`
if True, will display label.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
scale: int | None
default `= None`
Relative width compared to adjacent Components in a Row. For example, if
Component A has scale=2, and Component B has scale=1, A will be twice as wide
as B. Should be an integer.
min_width: int
default `= 160`
Minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrower than
min_width, the min_width parameter will be respected first.
interactive: bool | None
default `= None`
If True, will allow users to upload and edit an audio file. If False, can only
be used to play audio. 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 If
"hidden", component will be visually hidden and not take up space in the
layout but still exist in the DOM.
streaming: bool
default `= False`
If set to True when used in a `live` interface as an input, will automatically
stream webcam feed. When used set as an output, takes audio chunks yield from
the backend and combines them into one streaming audio output.
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
|
Initialization
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional list of strings that are assigned as the classes of this component
in the HTML DOM. Can be used for targeting CSS styles.
render: bool
default `= True`
if False, component will not render be rendered in the Blocks context. Should
be used if the intention is to assign event listeners now but render the
component later.
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
format: Literal['wav', 'mp3'] | None
default `= None`
the file extension with which to save audio files. Either 'wav' or 'mp3'. wav
files are lossless but will tend to be larger files. mp3 files tend to be
smaller. This parameter applies both when this component is used as an input
(and `type` is "filepath") to determine which file format to convert user-
provided audio to, and when this component is used as an output to determine
the format of audio returned to the user. If None, no file format conversion
is done and the audio is kept as is. In the case where output audio is
returned from the prediction function as numpy array and no `format` is
provided, it will be returned as a "wav" file.
|
Initialization
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
s done and the audio is kept as is. In the case where output audio is
returned from the prediction function as numpy array and no `format` is
provided, it will be returned as a "wav" file.
autoplay: bool
default `= False`
Whether to automatically play the audio when the component is used as an
output. Note: browsers will not autoplay audio files if the user has not
interacted with the page yet.
show_download_button: bool | None
default `= None`
If True, will show a download button in the corner of the component for saving
audio. If False, icon does not appear. By default, it will be True for output
components and False for input components.
show_share_button: bool | None
default `= None`
If True, will show a share icon in the corner of the component that allows
user to share outputs to Hugging Face Spaces Discussions. If False, icon does
not appear. If set to None (default behavior), then the icon appears if this
Gradio app is launched on Spaces, but not otherwise.
editable: bool
default `= True`
If True, allows users to manipulate the audio file if the component is
interactive. Defaults to True.
min_length: int | None
default `= None`
The minimum length of audio (in seconds) that the user can pass into the
prediction function. If None, there is no minimum length.
max_length: int | None
default `= None`
The maximum length of audio (in seconds) that the user can pass into the
prediction function. If None, there is no maximum length.
waveform_options: WaveformOptions | dict | None
default `= None`
A dictionary of options for the waveform display. Options include:
waveform_color (str), waveform_progress_color (str), show_controls (bool),
skip_length (int), trim_region_color (str). Default is None, which uses the
default values for these options. See `gr.WaveformOptions` docs.
loop: bool
default `= False`
If True, the audio will
|
Initialization
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
(int), trim_region_color (str). Default is None, which uses the
default values for these options. See `gr.WaveformOptions` docs.
loop: bool
default `= False`
If True, the audio will loop when it reaches the end and continue playing from
the beginning.
recording: bool
default `= False`
If True, the audio component will be set to record audio from the microphone
if the source is set to "microphone". Defaults to False.
subtitles: str | Path | list[dict[str, Any]] | None
default `= None`
A subtitle file (srt, vtt, or json) for the audio, or a list of subtitle
dictionaries in the format [{"text": str, "timestamp": [start, end]}] where
timestamps are in seconds. JSON files should contain an array of subtitle
objects.
|
Initialization
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.Audio` | "audio" | Uses default values
`gradio.Microphone` | "microphone" | Uses sources=["microphone"]
|
Shortcuts
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
generate_tonereverse_audio
Open in 🎢 ↗ import numpy as np import gradio as gr notes = ["C", "C", "D",
"D", "E", "F", "F", "G", "G", "A", "A", "B"] def generate_tone(note,
octave, duration): sr = 48000 a4_freq, tones_from_a4 = 440, 12 * (octave - 4)
+ (note - 9) frequency = a4_freq * 2 ** (tones_from_a4 / 12) duration =
int(duration) audio = np.linspace(0, duration, duration * sr) audio = (20000 *
np.sin(audio * (2 * np.pi * frequency))).astype(np.int16) return sr, audio
demo = gr.Interface( generate_tone, [ gr.Dropdown(notes, type="index"),
gr.Slider(4, 6, step=1), gr.Textbox(value="1", label="Duration in seconds"),
], "audio", ) if __name__ == "__main__": demo.launch()
import numpy as np
import gradio as gr
notes = ["C", "C", "D", "D", "E", "F", "F", "G", "G", "A", "A", "B"]
def generate_tone(note, octave, duration):
sr = 48000
a4_freq, tones_from_a4 = 440, 12 * (octave - 4) + (note - 9)
frequency = a4_freq * 2 ** (tones_from_a4 / 12)
duration = int(duration)
audio = np.linspace(0, duration, duration * sr)
audio = (20000 * np.sin(audio * (2 * np.pi * frequency))).astype(np.int16)
return sr, audio
demo = gr.Interface(
generate_tone,
[
gr.Dropdown(notes, type="index"),
gr.Slider(4, 6, step=1),
gr.Textbox(value="1", label="Duration in seconds"),
],
"audio",
)
if __name__ == "__main__":
demo.launch()
Open in 🎢 ↗ import numpy as np import gradio as gr def reverse_audio(audio):
sr, data = audio return (sr, np.flipud(data)) input_audio = gr.Audio(
sources=["microphone"], waveform_options=gr.WaveformOptions(
waveform_color="01C6FF", waveform_progress_color="0066B4", skip_length=2,
show_controls=False, ), ) demo = gr.Interface( fn=reverse_audio,
inputs=input_audio, outputs="audio" ) if __name__ == "__main__": demo.launch()
import numpy as np
|
Demos
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
ip_length=2,
show_controls=False, ), ) demo = gr.Interface( fn=reverse_audio,
inputs=input_audio, outputs="audio" ) if __name__ == "__main__": demo.launch()
import numpy as np
import gradio as gr
def reverse_audio(audio):
sr, data = audio
return (sr, np.flipud(data))
input_audio = gr.Audio(
sources=["microphone"],
waveform_options=gr.WaveformOptions(
waveform_color="01C6FF",
waveform_progress_color="0066B4",
skip_length=2,
show_controls=False,
),
)
demo = gr.Interface(
fn=reverse_audio,
inputs=input_audio,
outputs="audio"
)
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio 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 Audio component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`Audio.stream(fn, ···)` | This listener is triggered when the user streams the Audio.
`Audio.change(fn, ···)` | Triggered when the value of the Audio 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.
`Audio.clear(fn, ···)` | This listener is triggered when the user clears the Audio using the clear button for the component.
`Audio.play(fn, ···)` | This listener is triggered when the user plays the media in the Audio.
`Audio.pause(fn, ···)` | This listener is triggered when the media in the Audio stops for any reason.
`Audio.stop(fn, ···)` | This listener is triggered when the user reaches the end of the media playing in the Audio.
`Audio.pause(fn, ···)` | This listener is triggered when the media in the Audio stops for any reason.
`Audio.start_recording(fn, ···)` | This listener is triggered when the user starts recording with the Audio.
`Audio.pause_recording(fn, ···)` | This listener is triggered when the user pauses recording with the Audio.
`Audio.stop_recording(fn, ···)` | This listener is triggered when the user stops recording with the Audio.
`Audio.upload(fn, ···)` | This listener is triggered when the user uploads a file into the Audio.
`Audio.input(fn, ···)` | This listener is triggered when the user changes the value of the Audio.
Event Parameters
Parameters ▼
|
Event Listeners
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
s triggered when the user uploads a file into the Audio.
`Audio.input(fn, ···)` | This listener is triggered when the user changes the value of the Audio.
Event Parameters
Parameters ▼
fn: Callable | None | Literal['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
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
|
Event Listeners
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
iption. 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 `= "minimal"`
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 postpr
|
Event Listeners
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
nt data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited b
|
Event Listeners
|
https://gradio.app/docs/gradio/audio
|
Gradio - Audio Docs
|
()`, 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 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/audio
|
Gradio - Audio Docs
|
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