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Python library for easily interacting with trained machine learning models

Project description


tags: [gradio-custom-component, Slider] title: gradio_categoricalslider short_description: colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py

gradio_categoricalslider

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Python library for easily interacting with trained machine learning models

Installation

pip install gradio_categoricalslider

Usage

import gradio as gr
from gradio_categoricalslider import CategoricalSlider


demo = gr.Interface(
    lambda x: x,
    # interactive version of your component
    CategoricalSlider(categories=[("A", 1), ("B", 2), ("C", 3)]),
    None,  # static version of your component
    # examples=[[example]],  # uncomment this line to view the "example version" of your component
)


if __name__ == "__main__":
    demo.launch()

CategoricalSlider

Initialization

name type default description
categories
list[tuple[str, Any]]
[] List of tuples containing category and value.
value
float | Callable | None
None default value. If callable, the function will be called whenever the app loads to set the initial value of the component. Ignored if randomized=True.
label
str | None
None The label for this component. Appears above the component and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component is assigned to.
info
str | None
None additional component description.
every
float | None
None If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.
show_label
bool | None
None if True, will display label.
container
bool
True If True, will place the component in a container - providing some extra padding around the border.
scale
int | None
None relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.
min_width
int
160 minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.
interactive
bool | None
True if True, slider will be adjustable; if False, adjusting will be disabled. If not provided, this is inferred based on whether the component is used as an input or output.
visible
bool
True If False, component will be hidden.
elem_id
str | None
None An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
elem_classes
list[str] | str | None
None An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
render
bool
True If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.
key
int | str | None
None if assigned, will be used to assume identity across a re-render. Components that have the same key across a re-render will have their value preserved.
randomize
bool
False If True, the value of the slider when the app loads is taken uniformly at random from the list of categories.

Events

name description
change Triggered when the value of the CategoricalSlider changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See .input() for a listener that is only triggered by user input.
input This listener is triggered when the user changes the value of the CategoricalSlider.
release This listener is triggered when the user releases the mouse on this CategoricalSlider.

User function

The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).

  • When used as an Input, the component only impacts the input signature of the user function.
  • When used as an output, the component only impacts the return signature of the user function.

The code snippet below is accurate in cases where the component is used as both an input and an output.

  • As output: Is passed, passes slider category as a str into the function.
  • As input: Should return, expects a float or None returned from function and sets slider value to it as long as it is within the category values.
def predict(
    value: str
) -> float | None:
    return value

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