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batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of '
|
Event Listeners
|
https://gradio.app/docs/gradio/dataset
|
Gradio - Dataset Docs
|
r 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 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 in
|
Event Listeners
|
https://gradio.app/docs/gradio/dataset
|
Gradio - Dataset Docs
|
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/dataset
|
Gradio - Dataset Docs
|
Set the static paths to be served by the gradio app.
Static files are are served directly from the file system instead of being
copied. They are served to users with The Content-Disposition HTTP header set
to "inline" when sending these files to users. This indicates that the file
should be displayed directly in the browser window if possible. This function
is useful when you want to serve files that you know will not be modified
during the lifetime of the gradio app (like files used in gr.Examples). By
setting static paths, your app will launch faster and it will consume less
disk space. Calling this function will set the static paths for all gradio
applications defined in the same interpreter session until it is called again
or the session ends.
|
Description
|
https://gradio.app/docs/gradio/set_static_paths
|
Gradio - Set_Static_Paths Docs
|
import gradio as gr
Paths can be a list of strings or pathlib.Path objects
corresponding to filenames or directories.
gr.set_static_paths(paths=["test/test_files/"])
The example files and the default value of the input
will not be copied to the gradio cache and will be served directly.
demo = gr.Interface(
lambda s: s.rotate(45),
gr.Image(value="test/test_files/cheetah1.jpg", type="pil"),
gr.Image(),
examples=["test/test_files/bus.png"],
)
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/set_static_paths
|
Gradio - Set_Static_Paths Docs
|
Parameters ▼
paths: str | 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
|
Mount a gradio.Blocks to an existing FastAPI application.
|
Description
|
https://gradio.app/docs/gradio/mount_gradio_app
|
Gradio - Mount_Gradio_App Docs
|
from fastapi import FastAPI
import gradio as gr
app = FastAPI()
@app.get("/")
def read_main():
return {"message": "This is your main app"}
io = gr.Interface(lambda x: "Hello, " + x + "!", "textbox", "textbox")
app = gr.mount_gradio_app(app, io, path="/gradio")
Then run `uvicorn run:app` from the terminal and navigate to
http://localhost:8000/gradio.
|
Example Usage
|
https://gradio.app/docs/gradio/mount_gradio_app
|
Gradio - Mount_Gradio_App Docs
|
Parameters ▼
app: fastapi.FastAPI
The parent FastAPI application.
blocks: gradio.Blocks
The blocks object we want to mount to the parent app.
path: str
The path at which the gradio application will be mounted, e.g. "/gradio".
server_name: str
default `= "0.0.0.0"`
The server name on which the Gradio app will be run.
server_port: int
default `= 7860`
The port on which the Gradio app will be run.
show_api: bool | None
default `= None`
If False, hides the "Use via API" button on the Gradio interface.
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"}`
auth: Callable | tuple[str, str] | list[tuple[str, str]] | None
default `= None`
If provided, username and password (or list of username-password tuples)
required to access the gradio 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 for this gradio app.
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 gradio app (they will see a 401 Unauthorized
response). To be used with external authentication systems like OAuth. Cannot
be used with `auth`.
root_path: str | None
default `= None`
The subpath corresponding to the public deployment of this FastAPI
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, wh
|
Initialization
|
https://gradio.app/docs/gradio/mount_gradio_app
|
Gradio - Mount_Gradio_App Docs
|
tAPI
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 in
its entirety. Normally, this does not need to provided (even if you are using
a custom `path`). However, if you are serving the FastAPI app behind a proxy,
the proxy may not provide the full path to the Gradio app in the request
headers. In which case, you can provide the root path here.
allowed_paths: list[str] | None
default `= None`
List of complete filepaths or parent directories that this gradio app 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.
blocked_paths: list[str] | None
default `= None`
List of complete filepaths or parent directories that this gradio app 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.
favicon_path: str | None
default `= None`
If a path to a file (.png, .gif, or .ico) is provided, it will be used as the
favicon for this gradio app's page.
show_error: bool
default `= True`
If True, any errors in the gradio app will be displayed in an alert modal and
printed in the browser console log. Otherwise, errors will only be visible in
the terminal session running the Gradio app.
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.
ssr_mode: bool | None
default `= None`
If True, the Gradio app will be rendered using server-side rendering mode,
wh
|
Initialization
|
https://gradio.app/docs/gradio/mount_gradio_app
|
Gradio - Mount_Gradio_App Docs
|
is one of
"b", "kb", "mb", "gb", "tb". If None, no limit is set.
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.
node_server_name: str | None
default `= None`
The name of the Node server to use for SSR. If None, will use
GRADIO_NODE_SERVER_NAME environment variable or search for a node binary in
the system.
node_port: int | None
default `= None`
The port on which the Node server should run. If None, will use
GRADIO_NODE_SERVER_PORT environment variable or find a free port.
enable_monitoring: bool | None
default `= None`
pwa: bool | None
default `= None`
i18n: I18n | None
default `= None`
If provided, the i18n instance to use for this gradio app.
mcp_server: bool | None
default `= None`
If True, the MCP server will be launched on the gradio app. If None, will use
GRADIO_MCP_SERVER environment variable or default to False.
|
Initialization
|
https://gradio.app/docs/gradio/mount_gradio_app
|
Gradio - Mount_Gradio_App Docs
|
Sets up an API or MCP endpoint for a generic function without needing
define events listeners or components. Derives its typing from type hints in
the provided function's signature rather than the components.
|
Description
|
https://gradio.app/docs/gradio/api
|
Gradio - Api Docs
|
import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
input = gr.Textbox()
button = gr.Button("Submit")
output = gr.Textbox()
def fn(a: int, b: int, c: list[str]) -> tuple[int, str]:
return a + b, c[a:b]
gr.api(fn, api_name="add_and_slice")
_, url, _ = demo.launch()
from gradio_client import Client
client = Client(url)
result = client.predict(
a=3,
b=5,
c=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
api_name="/add_and_slice"
)
print(result)
|
Example Usage
|
https://gradio.app/docs/gradio/api
|
Gradio - Api Docs
|
Parameters ▼
fn: Callable | Literal['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. The function should be fully typed, and the type
hints will be used to derive the typing information for the API/MCP endpoint.
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 False, the endpoint will not be exposed in the api docs. If set to
None, will use the functions name as the endpoint route. If set to a string,
the endpoint will be exposed in the api docs with the given name.
api_description: str | None
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.
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)
concurrency_limit: int | None | Literal['default']
default `= "default"`
I
|
Initialization
|
https://gradio.app/docs/gradio/api
|
Gradio - Api Docs
|
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
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`
The time limit for the function to run. Parameter only used for the
`.stream()` event.
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 the `.stream()` event.
|
Initialization
|
https://gradio.app/docs/gradio/api
|
Gradio - Api Docs
|
Row is a layout element within Blocks that renders all children
horizontally.
|
Description
|
https://gradio.app/docs/gradio/row
|
Gradio - Row Docs
|
with gr.Blocks() as demo:
with gr.Row():
gr.Image("lion.jpg", scale=2)
gr.Image("tiger.jpg", scale=1)
demo.launch()
|
Example Usage
|
https://gradio.app/docs/gradio/row
|
Gradio - Row Docs
|
Parameters ▼
variant: Literal['default', 'panel', 'compact']
default `= "default"`
row type, 'default' (no background), 'panel' (gray background color and
rounded corners), or 'compact' (rounded corners and no internal gap).
visible: bool | Literal['hidden']
default `= True`
If False, row will be hidden.
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional string or list of strings that are assigned as the class of this
component in the HTML DOM. Can be used for targeting CSS styles.
scale: int | None
default `= None`
relative height compared to adjacent elements. 1 or greater indicates the Row
will expand in height, and any child columns will also expand to fill the
height.
render: bool
default `= True`
If False, this layout will not be rendered in the Blocks context. Should be
used if the intention is to assign event listeners now but render the
component later.
height: int | str | None
default `= None`
The height of the row, specified in pixels if a number is passed, or in CSS
units if a string is passed. If content exceeds the height, the row will
scroll vertically. If not set, the row will expand to fit the content.
max_height: int | str | None
default `= None`
The maximum height of the row, specified in pixels if a number is passed, or
in CSS units if a string is passed. If content exceeds the height, the row
will scroll vertically. If content is shorter than the height, the row will
shrink to fit the content. Will not have any effect if `height` is set and is
smaller than `max_height`.
min_height: int | str | None
default `= None`
The minimum height of the row, specified in pixels if a number is passed, or
in CSS units if a string is
|
Initialization
|
https://gradio.app/docs/gradio/row
|
Gradio - Row Docs
|
is
smaller than `max_height`.
min_height: int | str | None
default `= None`
The minimum height of the row, specified in pixels if a number is passed, or
in CSS units if a string is passed. If content exceeds the height, the row
will expand to fit the content. Will not have any effect if `height` is set
and is larger than `min_height`.
equal_height: bool
default `= False`
If True, makes every child element have equal height
show_progress: bool
default `= False`
If True, shows progress animation when being updated.
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= None`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
|
Initialization
|
https://gradio.app/docs/gradio/row
|
Gradio - Row Docs
|
Creates a numeric field for user to enter numbers as input or display
numeric output.
|
Description
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
**As input component** : Passes field value as a `float` or `int` into the
function, depending on `precision`.
Your function should accept one of these types:
def predict(
value: float | int | None
)
...
**As output component** : Expects an `int` or `float` returned from the
function and sets field value to it.
Your function should return one of these types:
def predict(···) -> float | int | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
Parameters ▼
value: float | Callable | None
default `= None`
default value. If None, the component will be empty and show the `placeholder`
if is set. If no `placeholder` is set, the component will show 0. If a
function is provided, the function will be called each time the app loads to
set the initial value of this component.
label: str | I18nData | None
default `= None`
the label for this component, 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.
placeholder: str | I18nData | None
default `= None`
placeholder hint to provide behind number input.
info: str | I18nData | None
default `= None`
additional component description, appears below the label in smaller font.
Supports markdown / HTML syntax.
every: Timer | float | None
default `= None`
Continously calls `value` to recalculate it if `value` is a function (has no
effect otherwise). Can provide a Timer whose tick resets `value`, or a float
that provides the regular interval for the reset Timer.
inputs: Component | list[Component] | set[Component] | None
default `= None`
Components that are used as inputs to calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
show_label: bool | None
default `= None`
if True, will display label.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
scale: int | None
default `= None`
relative size compared to adjacent Components. For example if Components A and
B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide
as B. Should be an integer. scale applie
|
Initialization
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
`
relative size compared to adjacent Components. For example if Components A and
B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide
as B. Should be an integer. scale applies in Rows, and to top-level Components
in Blocks where fill_height=True.
min_width: int
default `= 160`
minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrower than
min_width, the min_width parameter will be respected first.
interactive: bool | None
default `= None`
if True, will be editable; if False, editing will be disabled. If not
provided, this is inferred based on whether the component is used as an input
or output.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional list of strings that are assigned as the classes of this component
in the HTML DOM. Can be used for targeting CSS styles.
render: bool
default `= True`
If False, component will not render be rendered in the Blocks context. Should
be used if the intention is to assign event listeners now but render the
component later.
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
funct
|
Initialization
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
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.
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.
minimum: float | None
default `= None`
Minimum value. Only applied when component is used as an input. If a user
provides a smaller value, a gr.Error exception is raised by the backend.
maximum: float | None
default `= None`
Maximum value. Only applied when component is used as an input. If a user
provides a larger value, a gr.Error exception is raised by the backend.
step: float
default `= 1`
The interval between allowed numbers in the component. Can be used along with
optional parameters `minimum` and `maximum` to create a range of legal values
starting from `minimum` and incrementing according to this parameter.
|
Initialization
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.Number` | "number" | Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
tax_calculatorblocks_simple_squares
Open in 🎢 ↗ import gradio as gr def tax_calculator(income, marital_status,
assets): tax_brackets = [(10, 0), (25, 8), (60, 12), (120, 20), (250, 30)]
total_deductible = sum(assets["Cost"]) taxable_income = income -
total_deductible total_tax = 0 for bracket, rate in tax_brackets: if
taxable_income > bracket: total_tax += (taxable_income - bracket) * rate / 100
if marital_status == "Married": total_tax *= 0.75 elif marital_status ==
"Divorced": total_tax *= 0.8 return round(total_tax) demo = gr.Interface(
tax_calculator, [ "number", gr.Radio(["Single", "Married", "Divorced"]),
gr.Dataframe( headers=["Item", "Cost"], datatype=["str", "number"],
label="Assets Purchased this Year", ), ], "number", examples=[ [10000,
"Married", [["Suit", 5000], ["Laptop", 800], ["Car", 1800]]], [80000,
"Single", [["Suit", 800], ["Watch", 1800], ["Car", 800]]], ], ) demo.launch()
import gradio as gr
def tax_calculator(income, marital_status, assets):
tax_brackets = [(10, 0), (25, 8), (60, 12), (120, 20), (250, 30)]
total_deductible = sum(assets["Cost"])
taxable_income = income - total_deductible
total_tax = 0
for bracket, rate in tax_brackets:
if taxable_income > bracket:
total_tax += (taxable_income - bracket) * rate / 100
if marital_status == "Married":
total_tax *= 0.75
elif marital_status == "Divorced":
total_tax *= 0.8
return round(total_tax)
demo = gr.Interface(
tax_calculator,
[
"number",
gr.Radio(["Single", "Married", "Divorced"]),
gr.Dataframe(
headers=["Item", "Cost"],
datatype=["str", "number"],
label="Assets Purchased this Year",
),
],
"number",
examples=[
[10000, "Married", [["Suit", 5000], ["Laptop", 800], ["Car", 1800]]],
|
Demos
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
label="Assets Purchased this Year",
),
],
"number",
examples=[
[10000, "Married", [["Suit", 5000], ["Laptop", 800], ["Car", 1800]]],
[80000, "Single", [["Suit", 800], ["Watch", 1800], ["Car", 800]]],
],
)
demo.launch()
Open in 🎢 ↗ import gradio as gr demo = gr.Blocks(css="""btn {color: red} .abc
{font-family: "Comic Sans MS", "Comic Sans", cursive !important}""") with
demo: default_json = {"a": "a"} num = gr.State(value=0) squared =
gr.Number(value=0) btn = gr.Button("Next Square", elem_id="btn",
elem_classes=["abc", "def"]) stats = gr.State(value=default_json) table =
gr.JSON() def increase(var, stats_history): var += 1 stats_history[str(var)] =
var**2 return var, var**2, stats_history, stats_history btn.click(increase,
[num, stats], [num, squared, stats, table]) if __name__ == "__main__":
demo.launch()
import gradio as gr
demo = gr.Blocks(css="""btn {color: red} .abc {font-family: "Comic Sans MS", "Comic Sans", cursive !important}""")
with demo:
default_json = {"a": "a"}
num = gr.State(value=0)
squared = gr.Number(value=0)
btn = gr.Button("Next Square", elem_id="btn", elem_classes=["abc", "def"])
stats = gr.State(value=default_json)
table = gr.JSON()
def increase(var, stats_history):
var += 1
stats_history[str(var)] = var**2
return var, var**2, stats_history, stats_history
btn.click(increase, [num, stats], [num, squared, stats, table])
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/number
|
Gradio - Number 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 Number component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`Number.change(fn, ···)` | Triggered when the value of the Number 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.
`Number.input(fn, ···)` | This listener is triggered when the user changes the value of the Number.
`Number.submit(fn, ···)` | This listener is triggered when the user presses the Enter key while the Number is focused.
`Number.focus(fn, ···)` | This listener is triggered when the Number is focused.
`Number.blur(fn, ···)` | This listener is triggered when the Number is unfocused/blurred.
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
defau
|
Event Listeners
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enab
|
Event Listeners
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
n on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
|
Event Listeners
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
key: int | str | tuple[int | 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
|
Event Listeners
|
https://gradio.app/docs/gradio/number
|
Gradio - Number Docs
|
`
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/number
|
Gradio - Number Docs
|
Creates an image component that, as an input, can be used to upload and
edit images using simple editing tools such as brushes, strokes, cropping, and
layers. Or, as an output, this component can be used to display images.
|
Description
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
**As input component** : Passes the uploaded images as an instance of
EditorValue, which is just a `dict` with keys: 'background', 'layers', and
'composite'. The values corresponding to 'background' and 'composite' are
images, while 'layers' is a `list` of images. The images are of type
`PIL.Image`, `np.array`, or `str` filepath, depending on the `type` parameter.
Your function should accept one of these types:
def predict(
value: EditorValue | None
)
...
**As output component** : Expects a EditorValue, which is just a dictionary
with keys: 'background', 'layers', and 'composite'. The values corresponding
to 'background' and 'composite' should be images or None, while `layers`
should be a list of images. Images can be of type `PIL.Image`, `np.array`, or
`str` filepath/URL. Or, the value can be simply a single image (`ImageType`),
in which case it will be used as the background.
Your function should return one of these types:
def predict(···) -> EditorValue | ImageType | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
Parameters ▼
value: EditorValue | ImageType | None
default `= None`
Optional initial image(s) to populate the image editor. Should be a dictionary
with keys: `background`, `layers`, and `composite`. The values corresponding
to `background` and `composite` should be images or None, while `layers`
should be a list of images. Images can be of type PIL.Image, np.array, or str
filepath/URL. Or, the value can be a callable, in which case the function will
be called whenever the app loads to set the initial value of the component.
height: int | str | None
default `= None`
The height of the component, specified in pixels if a number is passed, or in
CSS units if a string is passed. This has no effect on the preprocessed image
files or numpy arrays, but will affect the displayed images. Beware of
conflicting values with the canvas_size paramter. If the canvas_size is larger
than the height, the editing canvas will not fit in the component.
width: int | str | None
default `= None`
The width of the component, specified in pixels if a number is passed, or in
CSS units if a string is passed. This has no effect on the preprocessed image
files or numpy arrays, but will affect the displayed images. Beware of
conflicting values with the canvas_size paramter. If the canvas_size is larger
than the height, the editing canvas will not fit in the component.
image_mode: Literal['1', 'L', 'P', 'RGB', 'RGBA', 'CMYK', 'YCbCr', 'LAB', 'HSV', 'I', 'F']
default `= "RGBA"`
"RGB" if color, or "L" if black and white. See
https://pillow.readthedocs.io/en/stable/handbook/concepts.html for other
supported image modes and their meaning.
sources: Iterable[Literal['upload', 'webcam', 'clipboard']] | Literal['upload', 'webcam', 'clipboard'] | None
default `= ('upload', 'webcam', 'clipboard')`
List of sources that can be used to set the background image. "upload" creates
a box where user can drop an image file, "webc
|
Initialization
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
bcam', 'clipboard'] | None
default `= ('upload', 'webcam', 'clipboard')`
List of sources that can be used to set the background image. "upload" creates
a box where user can drop an image file, "webcam" allows user to take snapshot
from their webcam, "clipboard" allows users to paste an image from the
clipboard.
type: Literal['numpy', 'pil', 'filepath']
default `= "numpy"`
The format the images are converted to before being passed into the prediction
function. "numpy" converts the images to numpy arrays with shape (height,
width, 3) and values from 0 to 255, "pil" converts the images to PIL image
objects, "filepath" passes images as str filepaths to temporary copies of the
images.
label: str | I18nData | None
default `= None`
the label for this component. Appears above the component and is also used as
the header if there are a table of examples for this component. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
every: Timer | float | None
default `= None`
Continously calls `value` to recalculate it if `value` is a function (has no
effect otherwise). Can provide a Timer whose tick resets `value`, or a float
that provides the regular interval for the reset Timer.
inputs: Component | list[Component] | set[Component] | None
default `= None`
Components that are used as inputs to calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
show_label: bool | None
default `= None`
if True, will display label.
show_download_button: bool
default `= True`
If True, will display button to download image.
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 Componen
|
Initialization
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
ue`
If True, will place the component in a container - providing some extra
padding around the border.
scale: int | None
default `= None`
relative size compared to adjacent Components. For example if Components A and
B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide
as B. Should be an integer. scale applies in Rows, and to top-level Components
in Blocks where fill_height=True.
min_width: int
default `= 160`
minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrower than
min_width, the min_width parameter will be respected first.
interactive: bool | None
default `= None`
if True, will allow users to upload and edit an image; if False, can only be
used to display images. If not provided, this is inferred based on whether the
component is used as an input or output.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional list of strings that are assigned as the classes of this component
in the HTML DOM. Can be used for targeting CSS styles.
render: bool
default `= True`
If False, component will not render be rendered in the Blocks context. Should
be used if the intention is to assign event listeners now but render the
component later.
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
|
Initialization
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
nt | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
placeholder: str | None
default `= None`
Custom text for the upload area. Overrides default upload messages when
provided. Accepts new lines and `` to designate a heading.
mirror_webcam: bool | None
default `= None`
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.
crop_size: tuple[int | float, int | float] | str | None
default `= None`
Deprecated. Used to set the `canvas_size` parameter.
transforms: Iterable[Literal['crop', 'resize']] | None
default `= ('crop', 'resize')`
The transforms tools to make available to users. "crop" allows the user to
crop the image.
eraser: Eraser | None | Literal[False]
default `= None`
The options for the eraser tool in the image editor. Should be an instance of
the `gr.Eraser` class, or None to use the default settings. Can also be False
to hide the eraser tool. See `gr.Eraser` docs.
brush: Brush | None | Literal[False]
default `= None`
The options for the brush tool in the image editor. Should be an insta
|
Initialization
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
o be False
to hide the eraser tool. See `gr.Eraser` docs.
brush: Brush | None | Literal[False]
default `= None`
The options for the brush tool in the image editor. Should be an instance of
the `gr.Brush` class, or None to use the default settings. Can also be False
to hide the brush tool, which will also hide the eraser tool. See `gr.Brush`
docs.
format: str
default `= "webp"`
Format to save image if it does not already have a valid format (e.g. if the
image is being returned to the frontend as a numpy array or PIL Image). The
format should be supported by the PIL library. This parameter has no effect on
SVG files.
layers: bool | LayerOptions
default `= True`
The options for the layer tool in the image editor. Can be a boolean or an
instance of the `gr.LayerOptions` class. If True, will allow users to add
layers to the image. If False, the layers option will be hidden. If an
instance of `gr.LayerOptions`, it will be used to configure the layer tool.
See `gr.LayerOptions` docs.
canvas_size: tuple[int, int]
default `= (800, 800)`
The initial size of the canvas in pixels. The first value is the width and the
second value is the height. If `fixed_canvas` is `True`, uploaded images will
be rescaled to fit the canvas size while preserving the aspect ratio.
Otherwise, the canvas size will change to match the size of an uploaded image.
fixed_canvas: bool
default `= False`
If True, the canvas size will not change based on the size of the background
image and the image will be rescaled to fit (while preserving the aspect
ratio) and placed in the center of the canvas.
show_fullscreen_button: bool
default `= True`
If True, will display button to view image in fullscreen mode.
webcam_options: WebcamOptions | None
default `= None`
The options for the webcam tool in the image editor. Can be an instance of the
`gr.WebcamOptions` class, or None to use the def
|
Initialization
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
webcam_options: WebcamOptions | None
default `= None`
The options for the webcam tool in the image editor. Can be an instance of the
`gr.WebcamOptions` class, or None to use the default settings. See
`gr.WebcamOptions` docs.
|
Initialization
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.ImageEditor` | "imageeditor" | Uses default values
`gradio.Sketchpad` | "sketchpad" | Uses sources=(), brush=Brush(colors=["000000"], color_mode="fixed")
`gradio.Paint` | "paint" | Uses sources=()
`gradio.ImageMask` | "imagemask" | Uses brush=Brush(colors=["000000"], color_mode="fixed")
|
Shortcuts
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
image_editor
Open in 🎢 ↗ import gradio as gr import time def sleep(im): time.sleep(5)
return [im["background"], im["layers"][0], im["layers"][1], im["composite"]]
def predict(im): return im["composite"] with gr.Blocks() as demo: with
gr.Row(): im = gr.ImageEditor( type="numpy", crop_size="1:1", ) im_preview =
gr.Image() n_upload = gr.Number(0, label="Number of upload events", step=1)
n_change = gr.Number(0, label="Number of change events", step=1) n_input =
gr.Number(0, label="Number of input events", step=1) im.upload(lambda x: x +
1, outputs=n_upload, inputs=n_upload) im.change(lambda x: x + 1,
outputs=n_change, inputs=n_change) im.input(lambda x: x + 1, outputs=n_input,
inputs=n_input) im.change(predict, outputs=im_preview, inputs=im,
show_progress="hidden") if __name__ == "__main__": demo.launch()
import gradio as gr
import time
def sleep(im):
time.sleep(5)
return [im["background"], im["layers"][0], im["layers"][1], im["composite"]]
def predict(im):
return im["composite"]
with gr.Blocks() as demo:
with gr.Row():
im = gr.ImageEditor(
type="numpy",
crop_size="1:1",
)
im_preview = gr.Image()
n_upload = gr.Number(0, label="Number of upload events", step=1)
n_change = gr.Number(0, label="Number of change events", step=1)
n_input = gr.Number(0, label="Number of input events", step=1)
im.upload(lambda x: x + 1, outputs=n_upload, inputs=n_upload)
im.change(lambda x: x + 1, outputs=n_change, inputs=n_change)
im.input(lambda x: x + 1, outputs=n_input, inputs=n_input)
im.change(predict, outputs=im_preview, inputs=im, show_progress="hidden")
if __name__ == "__main__":
demo.launch()
|
Demos
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
Description
Event listeners allow you to respond to user interactions with the UI
components you've defined in a Gradio Blocks app. When a user interacts with
an element, such as changing a slider value or uploading an image, a function
is called.
Supported Event Listeners
The ImageEditor component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`ImageEditor.clear(fn, ···)` | This listener is triggered when the user clears the ImageEditor using the clear button for the component.
`ImageEditor.change(fn, ···)` | Triggered when the value of the ImageEditor changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.
`ImageEditor.input(fn, ···)` | This listener is triggered when the user changes the value of the ImageEditor.
`ImageEditor.select(fn, ···)` | Event listener for when the user selects or deselects the ImageEditor. Uses event data gradio.SelectData to carry `value` referring to the label of the ImageEditor, and `selected` to refer to state of the ImageEditor. See EventData documentation on how to use this event data
`ImageEditor.upload(fn, ···)` | This listener is triggered when the user uploads a file into the ImageEditor.
`ImageEditor.apply(fn, ···)` | This listener is triggered when the user applies changes to the ImageEditor through an integrated UI action.
Event Parameters
Parameters ▼
fn: Callable | None | Literal['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each ele
|
Event Listeners
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https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
ten a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "mi
|
Event Listeners
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of
|
Event Listeners
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
ne
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this ev
|
Event Listeners
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
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/imageeditor
|
Gradio - Imageeditor Docs
|
Helper Classes
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
|
gradio.Brush(···)
Description
A dataclass for specifying options for the brush tool in the ImageEditor
component. An instance of this class can be passed to the `brush` parameter of
`gr.ImageEditor`.
Initialization
Parameters ▼
default_size: int | Literal['auto']
default `= "auto"`
The default radius, in pixels, of the brush tool. Defaults to "auto" in which
case the radius is automatically determined based on the size of the image
(generally 1/50th of smaller dimension).
colors: list[str | tuple[str, float]] | str | tuple[str, float] | None
default `= None`
A list of colors to make available to the user when using the brush. Defaults
to a list of 5 colors.
default_color: str | tuple[str, float] | None
default `= None`
The default color of the brush. Defaults to the first color in the `colors`
list.
color_mode: Literal['fixed', 'defaults']
default `= "defaults"`
If set to "fixed", user can only select from among the colors in `colors`. If
"defaults", the colors in `colors` are provided as a default palette, but the
user can also select any color using a color picker.
|
Brush
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
gradio.Eraser(···)
Description
A dataclass for specifying options for the eraser tool in the ImageEditor
component. An instance of this class can be passed to the `eraser` parameter
of `gr.ImageEditor`.
Initialization
Parameters ▼
default_size: int | Literal['auto']
default `= "auto"`
The default radius, in pixels, of the eraser tool. Defaults to "auto" in which
case the radius is automatically determined based on the size of the image
(generally 1/50th of smaller dimension).
|
Eraser
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
gradio.LayerOptions(···)
Description
A dataclass for specifying options for the layer tool in the ImageEditor
component. An instance of this class can be passed to the `layers` parameter
of `gr.ImageEditor`.
Initialization
Parameters ▼
allow_additional_layers: bool
default `= True`
If True, users can add additional layers to the image. If False, the add layer
button will not be shown.
layers: list[str] | None
default `= None`
A list of layers to make available to the user when using the layer tool. One
layer must be provided, if the length of the list is 0 then a layer will be
generated automatically.
disabled: bool
default `= False`
|
Layer Options
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
gradio.WebcamOptions(···)
Description
A dataclass for specifying options for the webcam tool in the ImageEditor
component. An instance of this class can be passed to the `webcam_options`
parameter of `gr.ImageEditor`.
Initialization
Parameters ▼
mirror: bool
default `= True`
If True, the webcam will be mirrored.
constraints: dict[str, Any] | None
default `= None`
A dictionary of constraints for the webcam.
|
Webcam Options
|
https://gradio.app/docs/gradio/imageeditor
|
Gradio - Imageeditor Docs
|
Displays a classification label, along with confidence scores of top
categories, if provided. As this component does not accept user input, it is
rarely used as an input component.
|
Description
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
**As input component** : Depending on the value, passes the label as a `str | int | float`, or the labels and confidences as a `dict[str, float]`.
Your function should accept one of these types:
def predict(
value: dict[str, float] | str | int | float | None
)
...
**As output component** : Expects a `dict[str, float]` of classes and confidences, or `str` with just the class or an `int | float` for regression outputs, or a `str` path to a .json file containing a json dictionary in one of the preceding formats.
Your function should return one of these types:
def predict(···) -> dict[str, float] | str | int | float | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
Parameters ▼
value: dict[str, float] | str | float | Callable | None
default `= None`
Default value to show in the component. If a str or number is provided, simply
displays the string or number. If a {Dict[str, float]} of classes and
confidences is provided, displays the top class on top and the
`num_top_classes` below, along with their confidence bars. If a function is
provided, the function will be called each time the app loads to set the
initial value of this component.
num_top_classes: int | None
default `= None`
number of most confident classes to show.
label: str | I18nData | None
default `= None`
the label for this component. Appears above the component and is also used as
the header if there are a table of examples for this component. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
every: Timer | float | None
default `= None`
Continously calls `value` to recalculate it if `value` is a function (has no
effect otherwise). Can provide a Timer whose tick resets `value`, or a float
that provides the regular interval for the reset Timer.
inputs: Component | list[Component] | set[Component] | None
default `= None`
Components that are used as inputs to calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
show_label: bool | None
default `= None`
if True, will display label.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
scale: int | None
default `= None`
relative size compared to adjacent Components. For example if Components A and
B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide
as B. Should be an integer. scale applies in Rows, and to top-level Components
in Blocks where fill_he
|
Initialization
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
if Components A and
B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide
as B. Should be an integer. scale applies in Rows, and to top-level Components
in Blocks where fill_height=True.
min_width: int
default `= 160`
minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrower than
min_width, the min_width parameter will be respected first.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional list of strings that are assigned as the classes of this component
in the HTML DOM. Can be used for targeting CSS styles.
render: bool
default `= True`
If False, component will not render be rendered in the Blocks context. Should
be used if the intention is to assign event listeners now but render the
component later.
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
color: str | Non
|
Initialization
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
meters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
color: str | None
default `= None`
The background color of the label (either a valid css color name or
hexadecimal string).
show_heading: bool
default `= True`
If False, the heading will not be displayed if a dictionary of labels and
confidences is provided. The heading will still be visible if the value is a
string or number.
|
Initialization
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.Label` | "label" | Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/label
|
Gradio - Label 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 Label component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`Label.change(fn, ···)` | Triggered when the value of the Label changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.
`Label.select(fn, ···)` | Event listener for when the user selects or deselects the Label. Uses event data gradio.SelectData to carry `value` referring to the label of the Label, and `selected` to refer to state of the Label. See EventData documentation on how to use this event data
Event Parameters
Parameters ▼
fn: Callable | None | Literal['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an emp
|
Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
ontext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | Literal[False]
default `= None`
defines how the endpoint appears in the API docs. Can be a string, None, or
False. If set to a string, the endpoint will be exposed in the API docs with
the given name. If None (default), the name of the function will be used as
the API endpoint. If False, the endpoint will not be exposed in the API docs
and downstream apps (including those that `gr.load` this app) will not be able
to use this event.
api_description: str | None | Literal[False]
default `= None`
Description of the API endpoint. Can be a string, None, or False. If set to a
string, the endpoint will be exposed in the API docs with the given
description. If None, the function's docstring will be used as the API
endpoint description. If False, then no description will be displayed in the
API docs.
scroll_to_output: bool
default `= False`
If True, will scroll to output component on completion
show_progress: Literal['full', 'minimal', 'hidden']
default `= "full"`
how to show the progress animation while event is running: "full" shows a
spinner which covers the output component area as well as a runtime display in
the upper right corner, "minimal" only shows the runtime display, "hidden"
shows no progress animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation 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 queu
|
Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
lt `= True`
If True, will place the request on the queue, if the queue has been enabled.
If False, will not put this event on the queue, even if the queue has been
enabled. If None, will use the queue setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would al
|
Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for js
method are values of 'inputs' and 'outputs', return should be a list of values
for output components.
concurrency_limit: int | None | Literal['default']
default `= "default"`
If set, this is the maximum number of this event that can be running
simultaneously. Can be set to None to mean no concurrency_limit (any number of
this event can be running simultaneously). Set to "default" to use the default
concurrency limit (defined by the `default_concurrency_limit` parameter in
`Blocks.queue()`, which itself is 1 by default).
concurrency_id: str | None
default `= None`
If set, this is the id of the concurrency group. Events with the same
concurrency_id will be limited by the lowest set concurrency_limit.
show_api: bool
default `= True`
whether to show this event in the "view API" page of the Gradio app, or in the
".view_api()" method of the Gradio clients. Unlike setting api_name to False,
setting show_api to False will still allow downstream apps as well as the
Clients to use this event. If fn is None, show_api will automatically be set
to False.
time_limit: int | None
default `= None`
stream_every: float
default `= 0.5`
like_user_message: bool
default `= False`
key: int | str | tuple[int | 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
|
Event Listeners
|
https://gradio.app/docs/gradio/label
|
Gradio - Label Docs
|
ener 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/label
|
Gradio - Label Docs
|
Creates a bar plot component to display data from a pandas DataFrame.
|
Description
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
**As input component** : The data to display in a line plot.
Your function should accept one of these types:
def predict(
value: AltairPlotData
)
...
**As output component** : Expects a pandas DataFrame containing the data to
display in the line plot. The DataFrame should contain at least two columns,
one for the x-axis (corresponding to this component's `x` argument) and one
for the y-axis (corresponding to `y`).
Your function should return one of these types:
def predict(···) -> pd.DataFrame | None
...
return value
|
Behavior
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
Parameters ▼
value: pd.DataFrame | Callable | None
default `= None`
The pandas dataframe containing the data to display in the plot.
x: str | None
default `= None`
Column corresponding to the x axis. Column can be numeric, datetime, or
string/category.
y: str | None
default `= None`
Column corresponding to the y axis. Column must be numeric.
color: str | None
default `= None`
Column corresponding to series, visualized by color. Column must be
string/category.
title: str | None
default `= None`
The title to display on top of the chart.
x_title: str | None
default `= None`
The title given to the x axis. By default, uses the value of the x parameter.
y_title: str | None
default `= None`
The title given to the y axis. By default, uses the value of the y parameter.
color_title: str | None
default `= None`
The title given to the color legend. By default, uses the value of color
parameter.
x_bin: str | float | None
default `= None`
Grouping used to cluster x values. If x column is numeric, should be number to
bin the x values. If x column is datetime, should be string such as "1h",
"15m", "10s", using "s", "m", "h", "d" suffixes.
y_aggregate: Literal['sum', 'mean', 'median', 'min', 'max', 'count'] | None
default `= None`
Aggregation function used to aggregate y values, used if x_bin is provided or
x is a string/category. Must be one of "sum", "mean", "median", "min", "max".
color_map: dict[str, str] | None
default `= None`
Mapping of series to color names or codes. For example, {"success": "green",
"fail": "FF8888"}.
x_lim: list[float] | None
default `= None`
A tuple or list containing the limits for the x-axis, specified as [x_min,
x_max]. If x column is datetime type, x_lim should be timestamps.
y_lim: list[float | None]
default `= None`
A
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
ple or list containing the limits for the x-axis, specified as [x_min,
x_max]. If x column is datetime type, x_lim should be timestamps.
y_lim: list[float | None]
default `= None`
A tuple of list containing the limits for the y-axis, specified as [y_min,
y_max]. To fix only one of these values, set the other to None, e.g. [0, None]
to scale from 0 to the maximum to value.
x_label_angle: float
default `= 0`
The angle of the x-axis labels in degrees offset clockwise.
y_label_angle: float
default `= 0`
The angle of the y-axis labels in degrees offset clockwise.
x_axis_labels_visible: bool | Literal['hidden']
default `= True`
Whether the x-axis labels should be visible. Can be hidden when many x-axis
labels are present.
caption: str | I18nData | None
default `= None`
The (optional) caption to display below the plot.
sort: Literal['x', 'y', '-x', '-y'] | list[str] | None
default `= None`
The sorting order of the x values, if x column is type string/category. Can be
"x", "y", "-x", "-y", or list of strings that represent the order of the
categories.
tooltip: Literal['axis', 'none', 'all'] | list[str]
default `= "axis"`
The tooltip to display when hovering on a point. "axis" shows the values for
the axis columns, "all" shows all column values, and "none" shows no tooltips.
Can also provide a list of strings representing columns to show in the
tooltip, which will be displayed along with axis values.
height: int | None
default `= None`
The height of the plot in pixels.
label: str | I18nData | None
default `= None`
The (optional) label to display on the top left corner of the plot.
show_label: bool | None
default `= None`
Whether the label should be displayed.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
default `= None`
Whether the label should be displayed.
container: bool
default `= True`
If True, will place the component in a container - providing some extra
padding around the border.
scale: int | None
default `= None`
relative size compared to adjacent Components. For example if Components A and
B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide
as B. Should be an integer. scale applies in Rows, and to top-level Components
in Blocks where fill_height=True.
min_width: int
default `= 160`
minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrower than
min_width, the min_width parameter will be respected first.
every: Timer | float | None
default `= None`
Continously calls `value` to recalculate it if `value` is a function (has no
effect otherwise). Can provide a Timer whose tick resets `value`, or a float
that provides the regular interval for the reset Timer.
inputs: Component | list[Component] | Set[Component] | None
default `= None`
Components that are used as inputs to calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
visible: bool | Literal['hidden']
default `= True`
Whether the plot should be visible.
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional list of strings that are 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 re
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
S 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.
show_fullscreen_button: bool
default `= False`
If True, will show a button to make plot visible in fullscreen mode.
show_export_button: bool
default `= False`
If True, will show a button to export and download the current view of the
plot as a PNG image.
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= "value"`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
|
Initialization
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
Class | Interface String Shortcut | Initialization
---|---|---
`gradio.BarPlot` | "barplot" | Uses default values
|
Shortcuts
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
bar_plot_demo
Open in 🎢 ↗ import pandas as pd from random import randint, random import
gradio as gr temp_sensor_data = pd.DataFrame( { "time":
pd.date_range("2021-01-01", end="2021-01-05", periods=200), "temperature":
[randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],
"humidity": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in
range(200)], "location": ["indoor", "outdoor"] * 100, } ) food_rating_data =
pd.DataFrame( { "cuisine": [["Italian", "Mexican", "Chinese"][i % 3] for i in
range(100)], "rating": [random() * 4 + 0.5 * (i % 3) for i in range(100)],
"price": [randint(10, 50) + 4 * (i % 3) for i in range(100)], "wait":
[random() for i in range(100)], } ) with gr.Blocks() as bar_plots: with
gr.Row(): start = gr.DateTime("2021-01-01 00:00:00", label="Start") end =
gr.DateTime("2021-01-05 00:00:00", label="End") apply_btn = gr.Button("Apply",
scale=0) with gr.Row(): group_by = gr.Radio(["None", "30m", "1h", "4h", "1d"],
value="None", label="Group by") aggregate = gr.Radio(["sum", "mean", "median",
"min", "max"], value="sum", label="Aggregation") temp_by_time = gr.BarPlot(
temp_sensor_data, x="time", y="temperature", ) temp_by_time_location =
gr.BarPlot( temp_sensor_data, x="time", y="temperature", color="location", )
time_graphs = [temp_by_time, temp_by_time_location] group_by.change( lambda
group: [gr.BarPlot(x_bin=None if group == "None" else group)] *
len(time_graphs), group_by, time_graphs ) aggregate.change( lambda aggregate:
[gr.BarPlot(y_aggregate=aggregate)] * len(time_graphs), aggregate, time_graphs
) def rescale(select: gr.SelectData): return select.index rescale_evt =
gr.on([plot.select for plot in time_graphs], rescale, None, [start, end]) for
trigger in [apply_btn.click, rescale_evt.then]: trigger( lambda start, end:
[gr.BarPlot(x_lim=[start, end])] * len(time_graphs), [start, end], time_graphs
) with gr.Row(): price_by_cuisine = gr.BarPlot( food_rating_data, x="cuisine",
y="price", ) with gr.Column(scale=0): gr.Button("Sort $
|
Demos
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
_lim=[start, end])] * len(time_graphs), [start, end], time_graphs
) with gr.Row(): price_by_cuisine = gr.BarPlot( food_rating_data, x="cuisine",
y="price", ) with gr.Column(scale=0): gr.Button("Sort $ > $$$").click(lambda:
gr.BarPlot(sort="y"), None, price_by_cuisine) gr.Button("Sort $$$ >
$").click(lambda: gr.BarPlot(sort="-y"), None, price_by_cuisine)
gr.Button("Sort A > Z").click(lambda: gr.BarPlot(sort=["Chinese", "Italian",
"Mexican"]), None, price_by_cuisine) with gr.Row(): price_by_rating =
gr.BarPlot( food_rating_data, x="rating", y="price", x_bin=1, )
price_by_rating_color = gr.BarPlot( food_rating_data, x="rating", y="price",
color="cuisine", x_bin=1, color_map={"Italian": "red", "Mexican": "green",
"Chinese": "blue"}, ) if __name__ == "__main__": bar_plots.launch()
import pandas as pd
from random import randint, random
import gradio as gr
temp_sensor_data = pd.DataFrame(
{
"time": pd.date_range("2021-01-01", end="2021-01-05", periods=200),
"temperature": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],
"humidity": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],
"location": ["indoor", "outdoor"] * 100,
}
)
food_rating_data = pd.DataFrame(
{
"cuisine": [["Italian", "Mexican", "Chinese"][i % 3] for i in range(100)],
"rating": [random() * 4 + 0.5 * (i % 3) for i in range(100)],
"price": [randint(10, 50) + 4 * (i % 3) for i in range(100)],
"wait": [random() for i in range(100)],
}
)
with gr.Blocks() as bar_plots:
with gr.Row():
start = gr.DateTime("2021-01-01 00:00:00", label="Start")
end = gr.DateTime("2021-01-05 00:00:00", label="End")
apply_btn = gr.Button("Apply", scale=0)
with gr.Row():
group_by = gr.Radio(["None", "30m", "1h", "4h", "1d"], value="None", label="Gro
|
Demos
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
021-01-05 00:00:00", label="End")
apply_btn = gr.Button("Apply", scale=0)
with gr.Row():
group_by = gr.Radio(["None", "30m", "1h", "4h", "1d"], value="None", label="Group by")
aggregate = gr.Radio(["sum", "mean", "median", "min", "max"], value="sum", label="Aggregation")
temp_by_time = gr.BarPlot(
temp_sensor_data,
x="time",
y="temperature",
)
temp_by_time_location = gr.BarPlot(
temp_sensor_data,
x="time",
y="temperature",
color="location",
)
time_graphs = [temp_by_time, temp_by_time_location]
group_by.change(
lambda group: [gr.BarPlot(x_bin=None if group == "None" else group)] * len(time_graphs),
group_by,
time_graphs
)
aggregate.change(
lambda aggregate: [gr.BarPlot(y_aggregate=aggregate)] * len(time_graphs),
aggregate,
time_graphs
)
def rescale(select: gr.SelectData):
return select.index
rescale_evt = gr.on([plot.select for plot in time_graphs], rescale, None, [start, end])
for trigger in [apply_btn.click, rescale_evt.then]:
trigger(
lambda start, end: [gr.BarPlot(x_lim=[start, end])] * len(time_graphs), [start, end], time_graphs
)
with gr.Row():
price_by_cuisine = gr.BarPlot(
food_rating_data,
x="cuisine",
y="price",
)
with gr.Column(scale=0):
gr.Button("Sort $ > $$$").click(lambda: gr.BarPlot(sort="y"), None, price_by_cuisine)
gr.Button("Sort $$$ > $").click(lambda: gr.BarPlot(sort="-y"), None, price_by_cuisine)
gr.Button("Sort A > Z").click(lambda: gr.BarPlot(sort=["Chinese", "Italian", "Mexican"]), None, price_by_cuisine)
with gr.Row():
|
Demos
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
sort="-y"), None, price_by_cuisine)
gr.Button("Sort A > Z").click(lambda: gr.BarPlot(sort=["Chinese", "Italian", "Mexican"]), None, price_by_cuisine)
with gr.Row():
price_by_rating = gr.BarPlot(
food_rating_data,
x="rating",
y="price",
x_bin=1,
)
price_by_rating_color = gr.BarPlot(
food_rating_data,
x="rating",
y="price",
color="cuisine",
x_bin=1,
color_map={"Italian": "red", "Mexican": "green", "Chinese": "blue"},
)
if __name__ == "__main__":
bar_plots.launch()
|
Demos
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
Description
Event listeners allow you to respond to user interactions with the UI
components you've defined in a Gradio Blocks app. When a user interacts with
an element, such as changing a slider value or uploading an image, a function
is called.
Supported Event Listeners
The BarPlot component supports the following event listeners. Each event
listener takes the same parameters, which are listed in the Event Parameters
table below.
Listener | Description
---|---
`BarPlot.select(fn, ···)` | Event listener for when the user selects or deselects the NativePlot. Uses event data gradio.SelectData to carry `value` referring to the label of the NativePlot, and `selected` to refer to state of the NativePlot. See EventData documentation on how to use this event data
`BarPlot.double_click(fn, ···)` | Triggered when the NativePlot is double clicked.
Event Parameters
Parameters ▼
fn: Callable | None | Literal['decorator']
default `= "decorator"`
the function to call when this event is triggered. Often a machine learning
model's prediction function. Each parameter of the function corresponds to one
input component, and the function should return a single value or a tuple of
values, with each element in the tuple corresponding to one output component.
inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as inputs. If the function takes no inputs,
this should be an empty list.
outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outputs. If the function returns no
outputs, this should be an empty list.
api_name: str | None | 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
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
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`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each pa
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
setting of the gradio app.
batch: bool
default `= False`
If True, then the function should process a batch of inputs, meaning that it
should accept a list of input values for each parameter. The lists should be
of equal length (and be up to length `max_batch_size`). The function is then
*required* to return a tuple of lists (even if there is only 1 output
component), with each list in the tuple corresponding to one output component.
max_batch_size: int
default `= 4`
Maximum number of inputs to batch together if this is called from the queue
(only relevant if batch=True)
preprocess: bool
default `= True`
If False, will not run preprocessing of component data before running 'fn'
(e.g. leaving it as a base64 string if this method is called with the `Image`
component).
postprocess: bool
default `= True`
If False, will not run postprocessing of component data before returning 'fn'
output to the browser.
cancels: dict[str, Any] | list[dict[str, Any]] | None
default `= None`
A list of other events to cancel when this listener is triggered. For example,
setting cancels=[click_event] will cancel the click_event, where click_event
is the return value of another components .click method. Functions that have
not yet run (or generators that are iterating) will be cancelled, but
functions that are currently running will be allowed to finish.
trigger_mode: Literal['once', 'multiple', 'always_last'] | None
default `= None`
If "once" (default for all events except `.change()`) would not allow any
submissions while an event is pending. If set to "multiple", unlimited
submissions are allowed while pending, and "always_last" (default for
`.change()` and `.key_up()` events) would allow a second submission after the
pending event is complete.
js: str | Literal[True] | None
default `= None`
Optional frontend js method to run before running 'fn'. Input arguments for
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
w 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 function will be executed first with queue=False, and only if it
completes successfully will the main function be called. The vali
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
alidation function to run before the main function. If provided,
this function will be executed first with queue=False, and only if it
completes successfully will the main function be called. The validator
receives the same inputs as the main function and should return a
`gr.validate()` for each input value.
|
Event Listeners
|
https://gradio.app/docs/gradio/barplot
|
Gradio - Barplot Docs
|
The Progress class provides a custom progress tracker that is used in a
function signature. To attach a Progress tracker to a function, simply add a
parameter right after the input parameters that has a default value set to a
`gradio.Progress()` instance. The Progress tracker can then be updated in the
function by calling the Progress object or using the `tqdm` method on an
Iterable.
|
Description
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
import gradio as gr
import time
def my_function(x, progress=gr.Progress()):
progress(0, desc="Starting...")
time.sleep(1)
for i in progress.tqdm(range(100)):
time.sleep(0.1)
return x
gr.Interface(my_function, gr.Textbox(), gr.Textbox()).queue().launch()
|
Example Usage
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
Parameters ▼
track_tqdm: bool
default `= False`
If True, the Progress object will track any tqdm.tqdm iterations with the tqdm
library in the function.
|
Initialization
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
Methods
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
|
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gradio.Progress.__call__(progress, ···)
Description
%20Copyright%202022%20Fontic
|
__call__
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
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)
Updates progress tracker with progress and message text.
Parameters ▼
progress: float | tuple[int, int | None] | None
If float, should be between 0 and 1 representing completion. If Tuple, first
number represents steps completed, and second value represents total steps or
None if unknown. If None, hides progress bar.
desc: str | None
default `= None`
description to display.
total: int | float | None
default `= None`
estimated total
|
__call__
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
None if unknown. If None, hides progress bar.
desc: str | None
default `= None`
description to display.
total: int | float | None
default `= None`
estimated total number of steps.
unit: str
default `= "steps"`
unit of iterations.
|
__call__
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress 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.Progress.tqdm(iterable, ···)
Description
%20Copyright%202022%20Fonticons,
|
tqdm
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
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)
Attaches progress tracker to iterable, like tqdm.
Parameters ▼
iterable: Iterable | None
iterable to attach progress tracker to.
desc: str | None
default `= None`
description to display.
total: int | float | None
default `= None`
estimated total number of steps.
unit: str
default `= "steps"`
unit of iterations.
|
tqdm
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
total number of steps.
unit: str
default `= "steps"`
unit of iterations.
|
tqdm
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress 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.Progress.__call__(progress, ···)
Description
%20Copyright%202022%20Fontic
|
__call__
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
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)
Updates progress tracker with progress and message text.
Parameters ▼
progress: float | tuple[int, int | None] | None
If float, should be between 0 and 1 representing completion. If Tuple, first
number represents steps completed, and second value represents total steps or
None if unknown. If None, hides progress bar.
desc: str | None
default `= None`
description to display.
total: int | float | None
default `= None`
estimated total
|
__call__
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
None if unknown. If None, hides progress bar.
desc: str | None
default `= None`
description to display.
total: int | float | None
default `= None`
estimated total number of steps.
unit: str
default `= "steps"`
unit of iterations.
|
__call__
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress 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.Progress.tqdm(iterable, ···)
Description
%20Copyright%202022%20Fonticons,
|
tqdm
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
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)
Attaches progress tracker to iterable, like tqdm.
Parameters ▼
iterable: Iterable | None
iterable to attach progress tracker to.
desc: str | None
default `= None`
description to display.
total: int | float | None
default `= None`
estimated total number of steps.
unit: str
default `= "steps"`
unit of iterations.
|
tqdm
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
total number of steps.
unit: str
default `= "steps"`
unit of iterations.
|
tqdm
|
https://gradio.app/docs/gradio/progress
|
Gradio - Progress Docs
|
Sidebar is a collapsible panel that renders child components on the left
side of the screen within a Blocks layout.
|
Description
|
https://gradio.app/docs/gradio/sidebar
|
Gradio - Sidebar Docs
|
with gr.Blocks() as demo:
with gr.Sidebar():
gr.Textbox()
gr.Button()
|
Example Usage
|
https://gradio.app/docs/gradio/sidebar
|
Gradio - Sidebar Docs
|
Parameters ▼
label: str | I18nData | None
default `= None`
name of the sidebar. Not displayed to the user.
open: bool
default `= True`
if True, sidebar is open by default.
visible: bool | Literal['hidden']
default `= True`
elem_id: str | None
default `= None`
An optional string that is assigned as the id of this component in the HTML
DOM. Can be used for targeting CSS styles.
elem_classes: list[str] | str | None
default `= None`
An optional string or list of strings that are assigned as the class of this
component in the HTML DOM. Can be used for targeting CSS styles.
render: bool
default `= True`
If False, this layout will not be rendered in the Blocks context. Should be
used if the intention is to assign event listeners now but render the
component later.
width: int | str
default `= 320`
The width of the sidebar, specified in pixels if a number is passed, or in CSS
units if a string is passed.
position: Literal['left', 'right']
default `= "left"`
The position of the sidebar in the layout, either "left" or "right". Defaults
to "left".
key: int | str | tuple[int | str, ...] | None
default `= None`
in a gr.render, Components with the same key across re-renders are treated as
the same component, not a new component. Properties set in 'preserved_by_key'
are not reset across a re-render.
preserved_by_key: list[str] | str | None
default `= None`
A list of parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.
|
Initialization
|
https://gradio.app/docs/gradio/sidebar
|
Gradio - Sidebar Docs
|
Methods
|
https://gradio.app/docs/gradio/sidebar
|
Gradio - Sidebar Docs
|
|
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