Components
Markdown

New to Gradio? Start here: Getting Started

To install Gradio from main, run the following command:

pip install https://gradio-builds.s3.amazonaws.com/9285dd9eb842ee05bd8a0fd4f0f9143788096bbc/gradio-5.9.1-py3-none-any.whl

*Note: Setting share=True in launch() will not work.

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Markdown

gradio.Markdown(···)

import gradio as gr with gr.Blocks() as demo: with gr.Group(): gr.Markdown(value="This _example_ was **written** in [Markdown](https://en.wikipedia.org/wiki/Markdown)\n") demo.launch()

Description

Used to render arbitrary Markdown output. Can also render latex enclosed by dollar signs. As this component does not accept user input, it is rarely used as an input component.

Behavior

As input component: Passes the `str` of Markdown corresponding to the displayed value.

Your function should accept one of these types:

def predict(
	value: str | None
)
	...

As output component: Expects a valid `str` that can be rendered as Markdown.

Your function should return one of these types:

def predict(···) -> str | None
	...	
	return value

Initialization

value: str | Callable | None

default = None

Value to show in Markdown component. If callable, the function will be called whenever the app loads to set the initial value of the component.

label: str | None

default = None

the label for this component. Is used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component is assigned to.

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

This parameter has no effect.

rtl: bool

default = False

If True, sets the direction of the rendered text to right-to-left. Default is False, which renders text left-to-right.

latex_delimiters: list[dict[str, str | bool]] | None

default = None

A list of dicts of the form {"left": open delimiter (str), "right": close delimiter (str), "display": whether to display in newline (bool)} that will be used to render LaTeX expressions. If not provided, `latex_delimiters` is set to `[{ "left": "$$", "right": "$$", "display": True }]`, so only expressions enclosed in $$ delimiters will be rendered as LaTeX, and in a new line. Pass in an empty list to disable LaTeX rendering. For more information, see the KaTeX documentation.

visible: bool

default = True

If False, component 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 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 | None

default = None

if assigned, will be used to assume identity across a re-render. Components that have the same key across a re-render will have their value preserved.

sanitize_html: bool

default = True

If False, will disable HTML sanitization when converted from markdown. This is not recommended, as it can lead to security vulnerabilities.

line_breaks: bool

default = False

If True, will enable Github-flavored Markdown line breaks in chatbot messages. If False (default), single new lines will be ignored.

header_links: bool

default = False

If True, will automatically create anchors for headings, displaying a link icon on hover.

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. If markdown content exceeds the height, the component will scroll.

max_height: int | str | None

default = None

The maximum height of the component, specified in pixels if a number is passed, or in CSS units if a string is passed. If markdown content exceeds the height, the component will scroll. If markdown content is shorter than the height, the component 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 component, specified in pixels if a number is passed, or in CSS units if a string is passed. If markdown content exceeds the height, the component will expand to fit the content. Will not have any effect if `height` is set and is larger than `min_height`.

show_copy_button: bool

default = False

If True, includes a copy button to copy the text in the Markdown component. Default is False.

container: bool

default = False

If True, the Markdown component will be displayed in a container. Default is False.

Shortcuts

Class	Interface String Shortcut	Initialization
`gradio.Markdown`	"markdown"	Uses default values

Demos

import gradio as gr def welcome(name): return f"Welcome to Gradio, {name}!" with gr.Blocks() as demo: gr.Markdown( """ # Hello World! Start typing below to see the output. """) inp = gr.Textbox(placeholder="What is your name?") out = gr.Textbox() inp.change(welcome, inp, out) if __name__ == "__main__": demo.launch()

import gradio as gr

def welcome(name):
    return f"Welcome to Gradio, {name}!"

with gr.Blocks() as demo:
    gr.Markdown(
    """
    # Hello World!
    Start typing below to see the output.
    """)
    inp = gr.Textbox(placeholder="What is your name?")
    out = gr.Textbox()
    inp.change(welcome, inp, out)

if __name__ == "__main__":
    demo.launch()

import pandas as pd import numpy as np import gradio as gr def plot(v, a): g = 9.81 theta = a / 180 * 3.14 tmax = ((2 * v) * np.sin(theta)) / g timemat = tmax * np.linspace(0, 1, 40) x = (v * timemat) * np.cos(theta) y = ((v * timemat) * np.sin(theta)) - ((0.5 * g) * (timemat**2)) df = pd.DataFrame({"x": x, "y": y}) return df demo = gr.Blocks() with demo: gr.Markdown( r"Let's do some kinematics! Choose the speed and angle to see the trajectory. Remember that the range $R = v_0^2 \cdot \frac{\sin(2\theta)}{g}$" ) with gr.Row(): speed = gr.Slider(1, 30, 25, label="Speed") angle = gr.Slider(0, 90, 45, label="Angle") output = gr.LinePlot( x="x", y="y", overlay_point=True, tooltip=["x", "y"], x_lim=[0, 100], y_lim=[0, 60], width=350, height=300, ) btn = gr.Button(value="Run") btn.click(plot, [speed, angle], output) if __name__ == "__main__": demo.launch()

import pandas as pd
import numpy as np

import gradio as gr

def plot(v, a):
    g = 9.81
    theta = a / 180 * 3.14
    tmax = ((2 * v) * np.sin(theta)) / g
    timemat = tmax * np.linspace(0, 1, 40)

    x = (v * timemat) * np.cos(theta)
    y = ((v * timemat) * np.sin(theta)) - ((0.5 * g) * (timemat**2))
    df = pd.DataFrame({"x": x, "y": y})
    return df

demo = gr.Blocks()

with demo:
    gr.Markdown(
        r"Let's do some kinematics! Choose the speed and angle to see the trajectory. Remember that the range $R = v_0^2 \cdot \frac{\sin(2\theta)}{g}$"
    )

    with gr.Row():
        speed = gr.Slider(1, 30, 25, label="Speed")
        angle = gr.Slider(0, 90, 45, label="Angle")
    output = gr.LinePlot(
        x="x",
        y="y",
        overlay_point=True,
        tooltip=["x", "y"],
        x_lim=[0, 100],
        y_lim=[0, 60],
        width=350,
        height=300,
    )
    btn = gr.Button(value="Run")
    btn.click(plot, [speed, angle], output)

if __name__ == "__main__":
    demo.launch()

Event Listeners

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 Markdown component supports the following event listeners. Each event listener takes the same parameters, which are listed in the Event Parameters table below.

Listener	Description
`Markdown.change(fn, ···)`	Triggered when the value of the Markdown 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.
`Markdown.copy(fn, ···)`	This listener is triggered when the user copies content from the Markdown. Uses event data gradio.CopyData to carry information about the copied content. See EventData documentation on how to use this event data

Event Parameters

fn: Callable | None | Literal['decorator']

default = "decorator"

the function to call when this event is triggered. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.

inputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None

default = None

List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list.

outputs: Component | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None

default = None

List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list.

api_name: str | None | Literal[False]

default = None

defines how the endpoint appears in the API docs. Can be a string, None, or False. If set to a string, the endpoint will be exposed in the API docs with the given name. If None (default), the name of the function will be used as the API endpoint. If False, the endpoint will not be exposed in the API docs and downstream apps (including those that `gr.load` this app) will not be able to use this event.

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

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 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 | 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

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LoginButton

Model3D

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Markdown

Description

Used to render arbitrary Markdown output. Can also render latex enclosed by dollar signs. As this component does not accept user input, it is rarely used as an input component.

Behavior

As input component: Passes the str of Markdown corresponding to the displayed value.

Your function should accept one of these types:

As output component: Expects a valid str that can be rendered as Markdown.

Your function should return one of these types:

Initialization

Shortcuts

Demos

Event Listeners

Description

Supported Event Listeners

Event Parameters

As input component: Passes the `str` of Markdown corresponding to the displayed value.

As output component: Expects a valid `str` that can be rendered as Markdown.