Skill: LLM Fine-Tuning with TRL
by Hugging Face
Fine-tune language and vision models with TRL or Unsloth — supervised, preference, and reinforcement training methods.
Build Gradio web UIs and ML demos in Python with the current API — components, layouts, events, and chat interfaces.
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---
name: huggingface-gradio
description: Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.
---
# Gradio
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](https://www.gradio.app/guides/quickstart)
- [The Interface Class](https://www.gradio.app/guides/the-interface-class)
- [Blocks and Event Listeners](https://www.gradio.app/guides/blocks-and-event-listeners)
- [Controlling Layout](https://www.gradio.app/guides/controlling-layout)
- [More Blocks Features](https://www.gradio.app/guides/more-blocks-features)
- [Custom CSS and JS](https://www.gradio.app/guides/custom-CSS-and-JS)
- [Streaming Outputs](https://www.gradio.app/guides/streaming-outputs)
- [Streaming Inputs](https://www.gradio.app/guides/streaming-inputs)
- [Sharing Your App](https://www.gradio.app/guides/sharing-your-app)
- [Custom HTML Components](https://www.gradio.app/guides/custom-HTML-components)
- [Getting Started with the Python Client](https://www.gradio.app/guides/getting-started-with-the-python-client)
- [Getting Started with the JS Client](https://www.gradio.app/guides/getting-started-with-the-js-client)
## Core Patterns
**Interface** (high-level): wraps a function with input/output components.
```python
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.
```python
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.
```python
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](https://www.gradio.app/guides/custom-HTML-components).
Here's an example that shows how to create and use these kinds of components:
```python
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:
```python
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
```bash
gradio info <space_id_or_url>
```
Returns a JSON payload describing all endpoints, their parameters (with types and defaults), and return values.
```bash
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
```bash
gradio predict <space_id_or_url> <endpoint> <json_payload>
```
Returns a JSON object with named output keys.
```bash
# 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](examples.md) — complete working apps
Gradio is the fastest way to put a UI on a Python function, and its API has changed enough across major versions that models routinely produce code for a Gradio that no longer exists.
This official skill covers the current API: the component library and when to use each, layout with Blocks, rows, columns, and tabs, event listeners and state, streaming outputs, and the ChatInterface patterns that most LLM demos are built on.
It also covers the practical details that decide whether a demo is usable — file handling, queuing under load, authentication, and theming — plus deployment to Hugging Face Spaces. Published by Hugging Face.
by Hugging Face
Fine-tune language and vision models with TRL or Unsloth — supervised, preference, and reinforcement training methods.
by Hugging Face
Deploy and maintain applications on Hugging Face Spaces — SDK choice, GPU hardware, model loading, and debugging.
by Hugging Face
Choose and run the right local model with llama.cpp and GGUF — quantisation, hardware fit, and local serving.
by Hugging Face
Hugging Face's official CLI skill — download, upload, and manage models, datasets, Spaces, and Jobs from the terminal.