hugging-face-gradio

Build or edit Gradio apps, layouts, components, and chat interfaces in Python for ML demos and UI prototypes. USE WHEN a user wants a Gradio demo or Python ML interface for a model or agent.

설치로 이동

저장소: Sheshiyer/skill-clusters
최근 소스 활동: 2026년 6월 5일 17:21
감지된 SKILL.md 언어: 영어
스타: 0
포크: 1

설치 방법

기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.

npx skills add https://github.com/Sheshiyer/skill-clusters --skill hugging-face-gradio

명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.

로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.

소스 파일 검토

설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.

파일 탐색기

2 개 파일

SKILL.md

소스 지침 · 읽기 전용 미리보기

검색으로 돌아가기 설치로 돌아가기

import gradio as gr

def greet(name):
    return f"Hello {name}!"

gr.Interface(fn=greet, inputs="text", outputs="text").launch()

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()

import gradio as gr

def respond(message, history):
    return f"You said: {message}"

gr.ChatInterface(fn=respond).launch()

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()

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

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

gradio info <space_id_or_url>

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": ""
#   }
# }

gradio predict <space_id_or_url> <endpoint> <json_payload>

# 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"}

name	hugging-face-gradio
description	Build or edit Gradio apps, layouts, components, and chat interfaces in Python for ML demos and UI prototypes. USE WHEN a user wants a Gradio demo or Python ML interface for a model or agent.
cluster	ai-agents-meta
version	1.0.0
origin	antigravity-awesome-skills (MIT)
source	https://github.com/huggingface/skills/tree/main/skills/huggingface-gradio
risk	unknown

name	hugging-face-gradio
description	Build or edit Gradio apps, layouts, components, and chat interfaces in Python for ML demos and UI prototypes. USE WHEN a user wants a Gradio demo or Python ML interface for a model or agent.
cluster	ai-agents-meta
version	1.0.0
origin	antigravity-awesome-skills (MIT)
source	https://github.com/huggingface/skills/tree/main/skills/huggingface-gradio
risk	unknown

hugging-face-gradio

설치 방법

소스 파일 검토

Gradio

When to Use

Guides

Gradio

When to Use

Guides

Core Patterns

Key Component Signatures

Custom HTML Components

Event Listeners

Prediction CLI

`gradio info` — Discover endpoints and parameters

`gradio predict` — Send predictions

Additional Reference

Limitations

hugging-face-gradio

소스 정보

설치 방법

소스 파일 검토

이 저장소의 다른 Skills

이 저장소의 다른 Skills

Gradio

When to Use

Guides

Gradio

When to Use

Guides

Core Patterns

Key Component Signatures

Custom HTML Components

Event Listeners

Prediction CLI

gradio info — Discover endpoints and parameters

gradio predict — Send predictions

Additional Reference

Limitations

`gradio info` — Discover endpoints and parameters

`gradio predict` — Send predictions