| 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". |
hf-gradio CLI Skill
The hf-gradio CLI gradio CLI includes info and predict commands for interacting with Gradio apps programmatically.
Step 1 - Verify installation
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
Step 2 - Use info to discover endpoints and payload format
gradio 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
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.
Step 3 - Use predict to generate the prediction
gradio 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.
gradio predict gradio/calculator /predict '{"num1": 5, "operation": "multiply", "num2": 3}'
gradio predict black-forest-labs/FLUX.2-dev /infer '{"prompt": "A majestic dragon"}'
gradio predict gradio/image_mod /predict '{"image": {"path": "/path/to/image.png", "meta": {"_type": "gradio.FileData"}}}'
Both commands accept --token for accessing private Spaces.