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Use Gradio applications via API. Use when the user asks for to generate a prediction from a Gradio app on Hugging Face spaces or public URL. For example, "Generate an image using black-forest-labs/FLUX.2-dev".
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
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/gradio-app/gradio --skill hf-gradio명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Build Gradio web UIs and demos in Python. Use when creating, modifying, debugging, or answering questions about Gradio and its capabilties, components, event listeners, or layouts.
Write comprehensive, behaviour-driven unit tests for Gradio frontend Svelte components using Vitest browser mode, Playwright, and the @self/tootils test utilities.
Build and customise Gradio themes. Use when creating, editing, or publishing Python-based Gradio themes that control colours, typography, spacing, shadows, and dark mode.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | hf-gradio |
| description | Use Gradio applications via API. Use when the user asks for to generate a prediction from a Gradio app on Hugging Face spaces or public URL. For example, "Generate an image using black-forest-labs/FLUX.2-dev". |
The hf-gradio CLI gradio CLI includes info and predict commands for interacting with Gradio apps programmatically.
Verify that either hf-gradio or gradio are installed in the current virtual environment.
If the hf CLI app is installed. The hf-gradio extension can be installed via
hf extensions install gradio-app/hf-gradio
info to discover endpoints and payload formatgradio info <space_id_or_url>
hf-gradio info <space_id_or_url>
hf 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.
predict to generate the predictiongradio predict <space_id_or_url> <endpoint> <json_payload>
hf-gradio predict <space_id_or_url> <endpoint> <json_payload>
hf 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.