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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".
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/gradio-app/gradio --skill hf-gradioコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
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 職業分類に基づく
SKILL.md を表示中
| 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.