
Gradio
FreeBuild interactive web UIs and ML demos effortlessly.
Free · Opens the source repo
What Gradio does
Gradio is a powerful Python library designed for creating interactive web applications and machine learning demos. With this skill, developers can easily build user interfaces for their models, allowing them to showcase functionality in a user-friendly way. The skill provides a comprehensive overview of the core API, essential patterns, and practical examples to help users get started quickly.
The Gradio skill is particularly useful for those looking to create or edit Gradio applications, components, event listeners, layouts, or chatbots. It supports various interface types, including simple function wrappers and more complex layouts using the Blocks API. This flexibility allows developers to tailor their applications to specific use cases, whether they're building a straightforward input-output interface or a more intricate layout with multiple interactive components.
In addition to the core functionality, the skill includes detailed guides on various topics, such as controlling layouts, using custom CSS and JavaScript, and streaming inputs and outputs. These resources are invaluable for developers aiming to enhance their applications with additional features or customization. The skill also covers specific component signatures, like Textbox, Number, Slider, and Checkbox, which are essential for building interactive UIs.
Overall, Gradio is an excellent choice for developers and designers who want to create engaging web interfaces for machine learning applications. Its straightforward API and extensive documentation make it accessible for both beginners and experienced users alike.
When to use it
Use this skill when you need to create or edit Gradio applications, particularly for machine learning demos or interactive UIs.
When not to use it
This skill may not be suitable for projects that require extensive custom web development beyond the capabilities of Gradio's API.
What you can build with it
Creating a Simple Chatbot
Use Gradio to quickly set up a chatbot interface that responds to user inputs, showcasing your model's conversational capabilities.
Building a Data Visualization Tool
Leverage Gradio to create an interactive web app that visualizes data outputs from your machine learning models.
Prototyping Machine Learning Models
Rapidly prototype your ML models with Gradio's intuitive interface, allowing for easy testing and demonstration of functionality.
How to install Gradio
View source1. Install with the skills CLI
npx skills add huggingface/skills/huggingface-gradio --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by huggingfaceGradio
Gradio is a Python library for building interactive web UIs and ML demos. This skill covers the core API, patterns, and examples.
Guides
Detailed guides on specific topics (read these when relevant):
- Quickstart
- The Interface Class
- Blocks and Event Listeners
- Controlling Layout
- More Blocks Features
- Custom CSS and JS
- Streaming Outputs
- Streaming Inputs
- Sharing Your App
- Custom HTML Components
- Getting Started with the Python Client
- Getting Started with the JS Client
Core Patterns
Interface (high-level): wraps a function with input/output components.
import gradio as gr
def greet(name):
return f"Hello {name}!"
gr.Interface(fn=greet, inputs="text", outputs="text").launch()
Blocks (low-level): flexible layout with explicit event wiring.
import gradio as gr
with gr.Blocks() as demo:
name = gr.Textbox(label="Name")
output = gr.Textbox(label="Greeting")
btn = gr.Button("Greet")
btn.click(fn=lambda n: f"Hello {n}!", inputs=name, outputs=output)
demo.launch()
ChatInterface: high-level wrapper for chatbot UIs.
import gradio as gr
def respond(message, history):
return f"You said: {message}"
gr.ChatInterface(fn=respond).launch()
Key Component Signatures
Textbox(value: str | I18nData | Callable | None = None, type: Literal['text', 'password', 'email'] = "text", lines: int = 1, max_lines: int | None = None, placeholder: str | I18nData | None = None, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, autofocus: bool = False, autoscroll: bool = True, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", text_align: Literal['left', 'right'] | None = None, rtl: bool = False, buttons: list[Literal['copy'] | Button] | None = None, max_length: int | None = None, submit_btn: str | bool | None = False, stop_btn: str | bool | None = False, html_attributes: InputHTMLAttributes | None = None)
Creates a textarea for user to enter string input or display string output..
Number(value: float | Callable | None = None, label: str | I18nData | None = None, placeholder: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", buttons: list[Button] | None = None, precision: int | None = None, minimum: float | None = None, maximum: float | None = None, step: float = 1)
Creates a numeric field for user to enter numbers as input or display numeric output..
Slider(minimum: float = 0, maximum: float = 100, value: float | Callable | None = None, step: float | None = None, precision: int | None = None, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", randomize: bool = False, buttons: list[Literal['reset']] | None = None)
Creates a slider that ranges from {minimum} to {maximum} with a step size of {step}..
Checkbox(value: bool | Callable = False, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", buttons: list[Button] | None = None)
Creates a checkbox that can be set to True or False.
Dropdown(choices: Sequence[str | int | float | tuple[str, str | int | float]] | None = None, value: str | int | float | Sequence[str | int | float] | Callable | DefaultValue | None = DefaultValue(), type: Literal['value', 'index'] = "value", multiselect: bool | None = None, allow_custom_value: bool = False, max_choices: int | None = None, filterable: bool = True, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", buttons: list[Button] | None = None)
Creates a dropdown of choices from which a single entry or multiple entries can be selected (as an input component) or displayed (as an output component)..
Radio(choices: Sequence[str | int | float | tuple[str, str | int | float]] | None = None, value: str | int | float | Callable | None = None, type: Literal['value', 'index'] = "value", label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", rtl: bool = False, buttons: list[Button] | None = None)
Creates a set of (string or numeric type) radio buttons of which only one can be selected..
Image(value: str | PIL.Image.Image | np.ndarray | Callable | None = None, format: str = "webp", height: int | str | None = None, width: int | str | None = None, image_mode: Literal['1', 'L', 'P', 'RGB', 'RGBA', 'CMYK', 'YCbCr', 'LAB', 'HSV', 'I', 'F'] | None = "RGB", sources: list[Literal['upload', 'webcam', 'clipboard']] | Literal['upload', 'webcam', 'clipboard'] | None = None, type: Literal['numpy', 'pil', 'filepath'] = "numpy", label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, buttons: list[Literal['download', 'share', 'fullscreen'] | Button] | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, streaming: bool = False, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", webcam_options: WebcamOptions | None = None, placeholder: str | None = None, watermark: WatermarkOptions | None = None)
Creates an image component that can be used to upload images (as an input) or display images (as an output)..
Audio(value: str | Path | tuple[int, np.ndarray] | Callable | None = None, sources: list[Literal['upload', 'microphone']] | Literal['upload', 'microphone'] | None = None, type: Literal['numpy', 'filepath'] = "numpy", label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, streaming: bool = False, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", format: Literal['wav', 'mp3'] | None = None, autoplay: bool = False, editable: bool = True, buttons: list[Literal['download', 'share'] | Button] | None = None, waveform_options: WaveformOptions | dict | None = None, loop: bool = False, recording: bool = False, subtitles: str | Path | list[dict[str, Any]] | None = None, playback_position: float = 0)
Creates an audio component that can be used to upload/record audio (as an input) or display audio (as an output)..
Video(value: str | Path | Callable | None = None, format: str | None = None, sources: list[Literal['upload', 'webcam']] | Literal['upload', 'webcam'] | None = None, height: int | str | None = None, width: int | str | None = None, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", webcam_options: WebcamOptions | None = None, include_audio: bool | None = None, autoplay: bool = False, buttons: list[Literal['download', 'share'] | Button] | None = None, loop: bool = False, streaming: bool = False, watermark: WatermarkOptions | None = None, subtitles: str | Path | list[dict[str, Any]] | None = None, playback_position: float = 0)
Creates a video component that can be used to upload/record videos (as an input) or display videos (as an output).
File(value: str | list[str] | Callable | None = None, file_count: Literal['single', 'multiple', 'directory'] = "single", file_types: list[str] | None = None, type: Literal['filepath', 'binary'] = "filepath", label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, height: int | str | float | None = None, interactive: bool | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", allow_reordering: bool = False, buttons: list[Button] | None = None)
Creates a file component that allows uploading one or more generic files (when used as an input) or displaying generic files or URLs for download (as output).
Chatbot(value: list[MessageDict | Message] | Callable | None = None, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, autoscroll: bool = True, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", height: int | str | None = 400, resizable: bool = False, max_height: int | str | None = None, min_height: int | str | None = None, editable: Literal['user', 'all'] | None = None, latex_delimiters: list[dict[str, str | bool]] | None = None, rtl: bool = False, buttons: list[Literal['share', 'copy', 'copy_all'] | Button] | None = None, watermark: str | None = None, avatar_images: tuple[str | Path | None, str | Path | None] | None = None, sanitize_html: bool = True, render_markdown: bool = True, feedback_options: list[str] | tuple[str, ...] | None = ('Like', 'Dislike'), feedback_value: Sequence[str | None] | None = None, line_breaks: bool = True, layout: Literal['panel', 'bubble'] | None = None, placeholder: str | None = None, examples: list[ExampleMessage] | None = None, allow_file_downloads: <class 'inspect._empty'> = True, group_consecutive_messages: bool = True, allow_tags: list[str] | bool = True, reasoning_tags: list[tuple[str, str]] | None = None, like_user_message: bool = False)
Creates a chatbot that displays user-submitted messages and responses.
Button(value: str | I18nData | Callable = "Run", every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, variant: Literal['primary', 'secondary', 'stop', 'huggingface'] = "secondary", size: Literal['sm', 'md', 'lg'] = "lg", icon: str | Path | None = None, link: str | None = None, link_target: Literal['_self', '_blank', '_parent', '_top'] = "_self", visible: bool | Literal['hidden'] = True, interactive: bool = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", scale: int | None = None, min_width: int | None = None)
Creates a button that can be assigned arbitrary .click() events.
Markdown(value: str | I18nData | Callable | None = None, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, rtl: bool = False, latex_delimiters: list[dict[str, str | bool]] | None = None, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", sanitize_html: bool = True, line_breaks: bool = False, header_links: bool = False, height: int | str | None = None, max_height: int | str | None = None, min_height: int | str | None = None, buttons: list[Literal['copy']] | None = None, container: bool = False, padding: bool = False)
Used to render arbitrary Markdown output.
HTML(value: Any | Callable | None = None, label: str | I18nData | None = None, html_template: str = "${value}", css_template: str = "", js_on_load: str | None = "element.addEventListener('click', function() { trigger('click') });", apply_default_css: bool = True, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool = False, visible: bool | Literal['hidden'] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = "value", min_height: int | None = None, max_height: int | None = None, container: bool = False, padding: bool = False, autoscroll: bool = False, buttons: list[Button] | None = None, server_functions: list[Callable] | None = None, props: Any)
Creates a component with arbitrary HTML.
Custom HTML Components
If a task requires significant customization of an existing component or a component that doesn't exist in Gradio, you can create one with gr.HTML. It supports html_template (with ${} JS expressions and {{}} Handlebars syntax), css_template for scoped styles, and js_on_load for interactivity — where props.value updates the component value and trigger('event_name') fires Gradio events. For reuse, subclass gr.HTML and define api_info() for API/MCP support. See the full guide.
Here's an example that shows how to create and use these kinds of components:
import gradio as gr
class StarRating(gr.HTML):
def __init__(self, label, value=0, **kwargs):
html_template = """
<h2>${label} rating:</h2>
${Array.from({length: 5}, (_, i) => `<img class='${i < value ? '' : 'faded'}' src='https://upload.wikimedia.org/wikipedia/commons/d/df/Award-star-gold-3d.svg'>`).join('')}
"""
css_template = """
img { height: 50px; display: inline-block; cursor: pointer; }
.faded { filter: grayscale(100%); opacity: 0.3; }
"""
js_on_load = """
const imgs = element.querySelectorAll('img');
imgs.forEach((img, index) => {
img.addEventListener('click', () => {
props.value = index + 1;
});
});
"""
super().__init__(value=value, label=label, html_template=html_template, css_template=css_template, js_on_load=js_on_load, **kwargs)
def api_info(self):
return {"type": "integer", "minimum": 0, "maximum": 5}
with gr.Blocks() as demo:
gr.Markdown("# Restaurant Review")
food_rating = StarRating(label="Food", value=3)
service_rating = StarRating(label="Service", value=3)
ambience_rating = StarRating(label="Ambience", value=3)
average_btn = gr.Button("Calculate Average Rating")
rating_output = StarRating(label="Average", value=3)
def calculate_average(food, service, ambience):
return round((food + service + ambience) / 3)
average_btn.click(
fn=calculate_average,
inputs=[food_rating, service_rating, ambience_rating],
outputs=rating_output
)
demo.launch()
Event Listeners
All event listeners share the same signature:
component.event_name(
fn: Callable | None | Literal["decorator"] = "decorator",
inputs: Component | Sequence[Component] | set[Component] | None = None,
outputs: Component | Sequence[Component] | set[Component] | None = None,
api_name: str | None = None,
api_description: str | None | Literal[False] = None,
scroll_to_output: bool = False,
show_progress: Literal["full", "minimal", "hidden"] = "full",
show_progress_on: Component | Sequence[Component] | None = None,
queue: bool = True,
batch: bool = False,
max_batch_size: int = 4,
preprocess: bool = True,
postprocess: bool = True,
cancels: dict[str, Any] | list[dict[str, Any]] | None = None,
trigger_mode: Literal["once", "multiple", "always_last"] | None = None,
js: str | Literal[True] | None = None,
concurrency_limit: int | None | Literal["default"] = "default",
concurrency_id: str | None = None,
api_visibility: Literal["public", "private", "undocumented"] = "public",
time_limit: int | None = None,
stream_every: float = 0.5,
key: int | str | tuple[int | str, ...] | None = None,
validator: Callable | None = None,
) -> Dependency
Supported events per component:
- AnnotatedImage: select
- Audio: stream, change, clear, play, pause, stop, pause, start_recording, pause_recording, stop_recording, upload, input
- BarPlot: select, double_click
- BrowserState: change
- Button: click
- Chatbot: change, select, like, retry, undo, example_select, option_select, clear, copy, edit
- Checkbox: change, input, select
- CheckboxGroup: change, input, select
- ClearButton: click
- Code: change, input, focus, blur
- ColorPicker: change, input, submit, focus, blur
- Dataframe: change, input, select, edit
- Dataset: click, select
- DateTime: change, submit
- DeepLinkButton: click
- Dialogue: change, input, submit
- DownloadButton: click
- Dropdown: change, input, select, focus, blur, key_up
- DuplicateButton: click
- File: change, select, clear, upload, delete, download
- FileExplorer: change, input, select
- Gallery: select, upload, change, delete, preview_close, preview_open
- HTML: change, input, click, double_click, submit, stop, edit, clear, play, pause, end, start_recording, pause_recording, stop_recording, focus, blur, upload, release, select, stream, like, example_select, option_select, load, key_up, apply, delete, tick, undo, retry, expand, collapse, download, copy
- HighlightedText: change, select
- Image: clear, change, stream, select, upload, input
- ImageEditor: clear, change, input, select, upload, apply
- ImageSlider: clear, change, stream, select, upload, input
- JSON: change
- Label: change, select
- LinePlot: select, double_click
- LoginButton: click
- Markdown: change, copy
- Model3D: change, upload, edit, clear
- MultimodalTextbox: change, input, select, submit, focus, blur, stop
- Navbar: change
- Number: change, input, submit, focus, blur
- ParamViewer: change, upload
- Plot: change
- Radio: select, change, input
- ScatterPlot: select, double_click
- SimpleImage: clear, change, upload
- Slider: change, input, release
- State: change
- Textbox: change, input, select, submit, focus, blur, stop, copy
- Timer: tick
- UploadButton: click, upload
- Video: change, clear, start_recording, stop_recording, stop, play, pause, end, upload, input
Prediction CLI
The gradio CLI includes info and predict commands for interacting with Gradio apps programmatically. These are especially useful for coding agents that need to use Spaces in their workflows.
gradio info — Discover endpoints and parameters
gradio info <space_id_or_url>
Returns a JSON payload describing all endpoints, their parameters (with types and defaults), and return values.
gradio info gradio/calculator
# {
# "/predict": {
# "parameters": [
# {"name": "num1", "required": true, "default": null, "type": {"type": "number"}},
# {"name": "operation", "required": true, "default": null, "type": {"enum": ["add", "subtract", "multiply", "divide"], "type": "string"}},
# {"name": "num2", "required": true, "default": null, "type": {"type": "number"}}
# ],
# "returns": [{"name": "output", "type": {"type": "number"}}],
# "description": ""
# }
# }
File-type parameters show "type": "filepath" with instructions to include "meta": {"_type": "gradio.FileData"} — this signals the file will be uploaded to the remote server.
gradio predict — Send predictions
gradio predict <space_id_or_url> <endpoint> <json_payload>
Returns a JSON object with named output keys.
# Simple numeric prediction
gradio predict gradio/calculator /predict '{"num1": 5, "operation": "multiply", "num2": 3}'
# {"output": 15}
# Image generation
gradio predict black-forest-labs/FLUX.2-dev /infer '{"prompt": "A majestic dragon"}'
# {"Result": "/tmp/gradio/.../image.webp", "Seed": 1117868604}
# File upload (must include meta key)
gradio predict gradio/image_mod /predict '{"image": {"path": "/path/to/image.png", "meta": {"_type": "gradio.FileData"}}}'
# {"output": "/tmp/gradio/.../output.png"}
Both commands accept --token for accessing private Spaces.
Additional Reference
- End-to-End Examples — complete working apps
Frequently asked questions about Gradio
Similar skills
Playwright Component Testing
Test React and Vue components in isolation with Playwright.
Fluent UI Blazor
Integrate Fluent UI components in Blazor applications effortlessly.
Build MCP App
Create interactive UI widgets for MCP servers.
Web Design Reviewer
Identify and fix design issues in websites efficiently.
Markstream Install
Seamlessly integrate Markstream for Markdown rendering.
GSAP & Framer Scroll Animation
Create advanced scroll animations effortlessly.
