gradio Interface — wrap any Python function in a working web demo

$ import gradio as gr

def reverse_text(text: str) -> str:
    return text[::-1]

demo = gr.Interface(
    fn=reverse_text,
    inputs=gr.Textbox(label="Your text", placeholder="Type here..."),
    outputs=gr.Textbox(label="Reversed"),
    title="Text Reverser",
    examples=[["Gradio makes ML demos easy"]],
)

demo.launch(prevent_thread_lock=True)

* Running on local URL:  http://127.0.0.1:7861

Rendered UI (read from /config on 6.27.0):
- centered Markdown title "Text Reverser"
- left column: Textbox labeled "Your text" (placeholder "Type here...")
- below it: Clear and Submit buttons
- right column: Textbox labeled "Reversed", below it a Flag button
- bottom: an examples table "Your text | Gradio makes ML demos easy"
Event listener: targets=[Submit.click, Textbox.submit] inputs=[textbox] outputs=[textbox], api_name="/reverse_text"
End-to-end: gradio_client predict("Hello Gradio", api_name="/reverse_text") -> 'oidarG olleH'

Verified on gradio 6.27.0 (Python 3.12). In Gradio 6 the endpoint is named after the function — /gradio_api/info reports "/reverse_text" and no /predict. Submit binds to .click AND Enter (.submit) on the input.

$ import gradio as gr
from PIL import Image
import numpy as np

def classify(img: Image.Image):
    if img is None:
        return {}
    arr = np.asarray(img.convert("L"), dtype=float)
    brightness = arr.mean() / 255.0
    if brightness > 0.6:
        return {"sky": 0.83, "cloud": 0.12, "night": 0.05}
    elif brightness > 0.3:
        return {"forest": 0.61, "meadow": 0.27, "sky": 0.12}
    else:
        return {"night": 0.77, "cave": 0.18, "forest": 0.05}

demo = gr.Interface(
    fn=classify,
    inputs=gr.Image(type="pil", label="Input image"),
    outputs=gr.Label(num_top_classes=3, label="Prediction"),
    title="Scenery Classifier",
    description="Upload a photo, get a (toy) scene label.",
    examples=[["examples/beach.jpg"]],
    cache_examples=False,
)

demo.launch(prevent_thread_lock=True)

* Running on local URL:  http://127.0.0.1:7861

Rendered UI (verified via /config):
- Markdown title, then the description line under it
- left column: Image input with sources: upload, webcam, clipboard
- right column: Label output "Prediction" (num_top_classes=3)
- bottom: examples dataset listing examples/beach.jpg
Event listener: targets=[[Submit, "click"]] inputs=[image] outputs=[label], api_name="/classify" — an Image input gets no Enter (.submit) binding, unlike a Textbox
Function logic verified: bright input -> {'sky': 0.83, 'cloud': 0.12, 'night': 0.05}; dark input -> {'night': 0.77, 'cave': 0.18, 'forest': 0.05}

The dict-of-confidence-scores return value is the contract gr.Label understands; each key renders with a bar. Swap the toy logic for a transformers pipeline and nothing else changes.

$ import gradio as gr
from PIL import Image

def to_grayscale(img: Image.Image, strength: float):
    if img is None:
        return None
    gray = img.convert("L")
    if strength >= 0.99:
        return gray
    return Image.blend(img.convert("RGB"), gray.convert("RGB"), strength)

demo = gr.Interface(
    fn=to_grayscale,
    inputs=[
        gr.Image(type="pil", label="Photo"),
        gr.Slider(0, 1, value=1.0, step=0.05, label="Grayscale strength"),
    ],
    outputs=gr.Image(type="pil", label="Result"),
    title="Grayscale Studio",
    live=True,  # re-runs on every input change, no Submit button
)

demo.launch(prevent_thread_lock=True)

* Running on local URL:  http://127.0.0.1:7861

Rendered UI (verified via /config on 6.27.0):
- left column: Image input "Photo" + Slider "Grayscale strength" (min 0, max 1, step 0.05, default 1.0)
- right column: Image output "Result"
- buttons present: Clear, Flag — NO Submit button anywhere, live=True removed it
Event listener: targets=[[image,'change'], [slider,'change']] inputs=[image, slider] outputs=[image], api_name="/to_grayscale"
Function logic verified: strength 1.0 -> mode L (fully gray); strength 0.5 -> Image.blend gives (147,72,72) for input (200,50,50)

live=True is the difference between a form and an instrument. Great for filters and sliders, expensive for slow models — every slider tick is a queued run.

$ # The Gradio 6 idiom: app-wide settings move to launch()
import gradio as gr

def summarize(text: str, max_words: int):
    words = text.split()
    return " ".join(words[:max_words]) + ("…" if len(words) > max_words else "")

demo = gr.Interface(
    fn=summarize,
    inputs=[gr.Textbox(label="Article", lines=4),
            gr.Slider(3, 30, value=8, step=1, label="Max words")],
    outputs=gr.Textbox(label="Summary"),
    title="Truncating Summarizer",
    flagging_mode="never",       # Gradio 5's allow_flagging= is GONE
)

demo.launch(
    theme=gr.themes.Soft(),                              # moved off the constructor
    css=".gradio-container { max-width: 720px !important; }",  # moved too
    footer_links=["gradio", "settings"],                 # replaces show_api=False
)

* Running on local URL:  http://127.0.0.1:7860

Rendered UI (verified on 6.27.0 via /config):
- theme Soft() applied, container capped at 720px by the injected CSS
- footer shows only the "Built with Gradio" and settings links — no API link
- right column: Textbox "Summary"; Clear + Submit buttons (no Flag: flagging_mode='never')
Event listener: api_name="/summarize"
Function logic verified: summarize("one two three four five six", 4) -> 'one two three four…'; summarize("short text", 8) -> 'short text'

If you write theme=/css= on gr.Interface or gr.Blocks in Gradio 6 you get a deprecation warning telling you to pass them to launch() instead — they still work on the constructor, but launch() is where they belong now.