HighlightedText

gradio.HighlightedText(···)

import gradio as gr with gr.Blocks() as demo: gr.HighlightedText( value=[ ("The ", "article"), ("quick ", "adjective"), ("brown ", "adjective"), ("fox ", "noun"), ("jumps ", "verb"), ("over ", "preposition"), ("the ", "article"), ("lazy ", "adjective"), ("dog", "noun"), ], combine_adjacent=True, ) demo.launch()

Description

Displays text that contains spans that are highlighted by category or numerical value.

Behavior

As input component: Passes the value as a list of tuples as a `list[tuple]` into the function. Each `tuple` consists of a `str` substring of the text (so the entire text is included) and `str | float | None` label, which is the category or confidence of that substring.

Your function should accept one of these types:

def predict(
	value: list[tuple[str, str | float | None]] | None
)
	...

As output component: Expects a list of (word, category) tuples, or a dictionary of two keys: "text", and "entities", which itself is a list of dictionaries, each of which have the keys: "entity" (or "entity_group"), "start", and "end"

Your function should return one of these types:

def predict(···) -> list[tuple[str, str | float | None]] | dict | None
	...	
	return value

Initialization

Shortcuts

Class	Interface String Shortcut	Initialization
`gradio.HighlightedText`	"highlightedtext"	Uses default values

Demos

from difflib import Differ import gradio as gr def diff_texts(text1, text2): d = Differ() return [ (token[2:], token[0] if token[0] != " " else None) for token in d.compare(text1, text2) ] demo = gr.Interface( diff_texts, [ gr.Textbox( label="Text 1", info="Initial text", lines=3, value="The quick brown fox jumped over the lazy dogs.", ), gr.Textbox( label="Text 2", info="Text to compare", lines=3, value="The fast brown fox jumps over lazy dogs.", ), ], gr.HighlightedText( label="Diff", combine_adjacent=True, show_legend=True, color_map={"+": "red", "-": "green"}), theme=gr.themes.Base() ) 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 HighlightedText component supports the following event listeners. Each event listener takes the same parameters, which are listed in the Event Parameters table below.

Listener	Description
`HighlightedText.change(fn, ···)`	Triggered when the value of the HighlightedText 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.
`HighlightedText.select(fn, ···)`	Event listener for when the user selects or deselects the HighlightedText. Uses event data gradio.SelectData to carry `value` referring to the label of the HighlightedText, and `selected` to refer to state of the HighlightedText. See EventData documentation on how to use this event data

Event Parameters

Guides

Named Entity Recognition

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HighlightedText

Description

Displays text that contains spans that are highlighted by category or numerical value.

Behavior

As input component: Passes the value as a list of tuples as a list[tuple] into the function. Each tuple consists of a str substring of the text (so the entire text is included) and str | float | None label, which is the category or confidence of that substring.

Your function should accept one of these types:

As output component: Expects a list of (word, category) tuples, or a dictionary of two keys: "text", and "entities", which itself is a list of dictionaries, each of which have the keys: "entity" (or "entity_group"), "start", and "end"

Your function should return one of these types:

Initialization

Shortcuts

Demos

Event Listeners

Description

Supported Event Listeners

Event Parameters

Guides

As input component: Passes the value as a list of tuples as a `list[tuple]` into the function. Each `tuple` consists of a `str` substring of the text (so the entire text is included) and `str | float | None` label, which is the category or confidence of that substring.