checkboxgroup.py

"""gr.CheckboxGroup() component"""

from __future__ import annotations

from typing import Any, Callable, Literal

from gradio_client.documentation import document, set_documentation_group
from gradio_client.serializing import ListStringSerializable

from gradio.components.base import FormComponent, IOComponent, _Keywords
from gradio.deprecation import warn_deprecation, warn_style_method_deprecation
from gradio.events import Changeable, EventListenerMethod, Inputable, Selectable
from gradio.interpretation import NeighborInterpretable

set_documentation_group("component")


@document()
class CheckboxGroup(
    FormComponent,
    Changeable,
    Inputable,
    Selectable,
    IOComponent,
    ListStringSerializable,
    NeighborInterpretable,
):
    """
    Creates a set of checkboxes of which a subset can be checked.
    Preprocessing: passes the list of checked checkboxes as a {List[str]} or their indices as a {List[int]} into the function, depending on `type`.
    Postprocessing: expects a {List[str]}, each element of which becomes a checked checkbox.
    Examples-format: a {List[str]} representing the values to be checked.
    Demos: sentence_builder, titanic_survival
    """

    def __init__(
        self,
        choices: list[str] | None = None,
        *,
        value: list[str] | str | Callable | None = None,
        type: Literal["value", "index"] = "value",
        label: str | None = None,
        info: str | None = None,
        every: float | None = None,
        show_label: bool | None = None,
        container: bool = True,
        scale: int | None = None,
        min_width: int = 160,
        interactive: bool | None = None,
        visible: bool = True,
        elem_id: str | None = None,
        elem_classes: list[str] | str | None = None,
        **kwargs,
    ):
        """
        Parameters:
            choices: list of options to select from.
            value: default selected list of options. If callable, the function will be called whenever the app loads to set the initial value of the component.
            type: Type of value to be returned by component. "value" returns the list of strings of the choices selected, "index" returns the list of indices of the choices selected.
            label: component name in interface.
            info: additional component description.
            every: If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. Queue must be enabled. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.
            show_label: if True, will display label.
            container: If True, will place the component in a container - providing some extra padding around the border.
            scale: relative width compared to adjacent Components in a Row. For example, if Component A has scale=2, and Component B has scale=1, A will be twice as wide as B. Should be an integer.
            min_width: 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: if True, choices in this checkbox group will be checkable; if False, checking will be disabled. If not provided, this is inferred based on whether the component is used as an input or output.
            visible: If False, component will be hidden.
            elem_id: 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: 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.
        """
        self.choices = choices or []
        valid_types = ["value", "index"]
        if type not in valid_types:
            raise ValueError(
                f"Invalid value for parameter `type`: {type}. Please choose from one of: {valid_types}"
            )
        self.type = type
        self.select: EventListenerMethod
        """
        Event listener for when the user selects or deselects within CheckboxGroup.
        Uses event data gradio.SelectData to carry `value` referring to label of selected checkbox, `index` to refer to index, and `selected` to refer to state of checkbox.
        See EventData documentation on how to use this event data.
        """
        IOComponent.__init__(
            self,
            label=label,
            info=info,
            every=every,
            show_label=show_label,
            container=container,
            scale=scale,
            min_width=min_width,
            interactive=interactive,
            visible=visible,
            elem_id=elem_id,
            elem_classes=elem_classes,
            value=value,
            **kwargs,
        )
        NeighborInterpretable.__init__(self)

    def get_config(self):
        return {
            "choices": self.choices,
            "value": self.value,
            **IOComponent.get_config(self),
        }

    def example_inputs(self) -> dict[str, Any]:
        return {
            "raw": self.choices[0] if self.choices else None,
            "serialized": self.choices[0] if self.choices else None,
        }

    @staticmethod
    def update(
        value: list[str]
        | str
        | Literal[_Keywords.NO_VALUE]
        | None = _Keywords.NO_VALUE,
        choices: list[str] | None = None,
        label: str | None = None,
        info: str | None = None,
        show_label: bool | None = None,
        container: bool | None = None,
        scale: int | None = None,
        min_width: int | None = None,
        interactive: bool | None = None,
        visible: bool | None = None,
    ):
        return {
            "choices": choices,
            "label": label,
            "info": info,
            "show_label": show_label,
            "container": container,
            "scale": scale,
            "min_width": min_width,
            "interactive": interactive,
            "visible": visible,
            "value": value,
            "__type__": "update",
        }

    def preprocess(self, x: list[str]) -> list[str] | list[int]:
        """
        Parameters:
            x: list of selected choices
        Returns:
            list of selected choices as strings or indices within choice list
        """
        if self.type == "value":
            return x
        elif self.type == "index":
            return [self.choices.index(choice) for choice in x]
        else:
            raise ValueError(
                f"Unknown type: {self.type}. Please choose from: 'value', 'index'."
            )

    def postprocess(self, y: list[str] | str | None) -> list[str]:
        """
        Any postprocessing needed to be performed on function output.
        Parameters:
            y: List of selected choices. If a single choice is selected, it can be passed in as a string
        Returns:
            List of selected choices
        """
        if y is None:
            return []
        if not isinstance(y, list):
            y = [y]
        return y

    def get_interpretation_neighbors(self, x):
        leave_one_out_sets = []
        for choice in self.choices:
            leave_one_out_set = list(x)
            if choice in leave_one_out_set:
                leave_one_out_set.remove(choice)
            else:
                leave_one_out_set.append(choice)
            leave_one_out_sets.append(leave_one_out_set)
        return leave_one_out_sets, {}

    def get_interpretation_scores(self, x, neighbors, scores, **kwargs):
        """
        Returns:
            For each tuple in the list, the first value represents the interpretation score if the input is False, and the second if the input is True.
        """
        final_scores = []
        for choice, score in zip(self.choices, scores):
            score_set = [score, None] if choice in x else [None, score]
            final_scores.append(score_set)
        return final_scores

    def style(
        self,
        *,
        item_container: bool | None = None,
        container: bool | None = None,
        **kwargs,
    ):
        """
        This method is deprecated. Please set these arguments in the constructor instead.
        """
        warn_style_method_deprecation()
        if item_container is not None:
            warn_deprecation("The `item_container` parameter is deprecated.")
        if container is not None:
            self.container = container
        return self