HighlightedText

import gradio as gr

def ner(text):
    # Returns list of (token, label) tuples
    return [
        ("The", None),
        ("Eiffel", "LOC"),
        ("Tower", "LOC"),
        ("is", None),
        ("in", None),
        ("Paris", "LOC")
    ]

gr.Interface(
    fn=ner,
    inputs=gr.Textbox(),
    outputs=gr.HighlightedText()
).launch()

import gradio as gr

def ner_demo(text):
    # Simulated NER output
    entities = [
        ("Apple", "ORG"),
        (" announced the ", None),
        ("iPhone", "PRODUCT"),
        (" in ", None),
        ("2007", "DATE")
    ]
    return entities

gr.Interface(
    fn=ner_demo,
    inputs=gr.Textbox(),
    outputs=gr.HighlightedText(
        color_map={
            "ORG": "#FFD700",
            "PRODUCT": "#90EE90",
            "DATE": "#87CEEB"
        },
        show_legend=True
    )
).launch()

import gradio as gr

def sentiment(text):
    # Returns (text, confidence) tuples
    words = text.split()
    return [(w, 0.9 if i % 2 == 0 else 0.3) for i, w in enumerate(words)]

gr.Interface(
    fn=sentiment,
    inputs=gr.Textbox(),
    outputs=gr.HighlightedText()
).launch()

import gradio as gr

def ner_hf_format(text):
    return {
        "text": "Apple is a technology company",
        "entities": [
            {"entity": "ORG", "start": 0, "end": 5},
            {"entity": "TYPE", "start": 13, "end": 23}
        ]
    }

gr.Interface(
    fn=ner_hf_format,
    inputs=gr.Button("Analyze"),
    outputs=gr.HighlightedText()
).launch()