"""gr.Markdown() component."""

from __future__ import annotations

import inspect
from typing import Any, Callable

from gradio_client.documentation import document

from gradio.components.base import Component
from gradio.events import Events

from gradio.events import Dependency

@document()
class Markdown(Component):
    """
    Used to render arbitrary Markdown output. Can also render latex enclosed by dollar signs. As this component does not accept user input,
    it is rarely used as an input component.

    Demos: blocks_hello, blocks_kinematics
    Guides: key-features
    """

    EVENTS = [Events.change]

    def __init__(
        self,
        value: str | Callable | None = None,
        *,
        label: str | None = None,
        every: float | None = None,
        show_label: bool | None = None,
        rtl: bool = False,
        latex_delimiters: list[dict[str, str | bool]] | None = None,
        visible: bool = True,
        elem_id: str | None = None,
        elem_classes: list[str] | str | None = None,
        render: bool = True,
        sanitize_html: bool = True,
        line_breaks: bool = False,
        header_links: bool = False,
    ):
        """
        Parameters:
            value: Value to show in Markdown component. If callable, the function will be called whenever the app loads to set the initial value of the component.
            label: The label for this component. Is 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.
            every: 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: This parameter has no effect.
            rtl: If True, sets the direction of the rendered text to right-to-left. Default is False, which renders text left-to-right.
            latex_delimiters: A list of dicts of the form {"left": open delimiter (str), "right": close delimiter (str), "display": whether to display in newline (bool)} that will be used to render LaTeX expressions. If not provided, `latex_delimiters` is set to `[{ "left": "$$", "right": "$$", "display": True }]`, so only expressions enclosed in $$ delimiters will be rendered as LaTeX, and in a new line. Pass in an empty list to disable LaTeX rendering. For more information, see the [KaTeX documentation](https://katex.org/docs/autorender.html).
            visible: If False, component will be hidden.
            elem_id: An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
            elem_classes: An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
            render: If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.
            sanitize_html: If False, will disable HTML sanitization when converted from markdown. This is not recommended, as it can lead to security vulnerabilities.
            line_breaks: If True, will enable Github-flavored Markdown line breaks in chatbot messages. If False (default), single new lines will be ignored.
            header_links: If True, will automatically create anchors for headings, displaying a link icon on hover.
        """
        self.rtl = rtl
        if latex_delimiters is None:
            latex_delimiters = [{"left": "$$", "right": "$$", "display": True}]
        self.latex_delimiters = latex_delimiters
        self.sanitize_html = sanitize_html
        self.line_breaks = line_breaks
        self.header_links = header_links

        super().__init__(
            label=label,
            every=every,
            show_label=show_label,
            visible=visible,
            elem_id=elem_id,
            elem_classes=elem_classes,
            render=render,
            value=value,
        )

    def preprocess(self, payload: str | None) -> str | None:
        """
        Parameters:
            payload: the `str` of Markdown corresponding to the displayed value.
        Returns:
            Passes the `str` of Markdown corresponding to the displayed value.
        """
        return payload

    def postprocess(self, value: str | None) -> str | None:
        """
        Parameters:
            value: Expects a valid `str` that can be rendered as Markdown.
        Returns:
            The same `str` as the input, but with leading and trailing whitespace removed.
        """
        if value is None:
            return None
        unindented_y = inspect.cleandoc(value)
        return unindented_y

    def example_payload(self) -> Any:
        return "# Hello!"

    def example_value(self) -> Any:
        return "# Hello!"

    def api_info(self) -> dict[str, Any]:
        return {"type": "string"}

    
    def change(self,
        fn: Callable | None,
        inputs: Component | Sequence[Component] | set[Component] | None = None,
        outputs: Component | Sequence[Component] | None = None,
        api_name: str | None | Literal[False] = None,
        scroll_to_output: bool = False,
        show_progress: Literal["full", "minimal", "hidden"] = "full",
        queue: bool | None = None,
        batch: bool = False,
        max_batch_size: int = 4,
        preprocess: bool = True,
        postprocess: bool = True,
        cancels: dict[str, Any] | list[dict[str, Any]] | None = None,
        every: float | None = None,
        trigger_mode: Literal["once", "multiple", "always_last"] | None = None,
        js: str | None = None,
        concurrency_limit: int | None | Literal["default"] = "default",
        concurrency_id: str | None = None,
        show_api: bool = True) -> Dependency:
        """
        Parameters:
            fn: the function to call when this event is triggered. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.
            inputs: List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list.
            outputs: List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list.
            api_name: Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name.
            scroll_to_output: If True, will scroll to output component on completion
            show_progress: If True, will show progress animation while pending
            queue: If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app.
            batch: If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component.
            max_batch_size: Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True)
            preprocess: If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component).
            postprocess: If False, will not run postprocessing of component data before returning 'fn' output to the browser.
            cancels: A list of other events to cancel when this listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish.
            every: Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds.
            trigger_mode: If "once" (default for all events except `.change()`) would not allow any submissions while an event is pending. If set to "multiple", unlimited submissions are allowed while pending, and "always_last" (default for `.change()` and `.key_up()` events) would allow a second submission after the pending event is complete.
            js: Optional frontend js method to run before running 'fn'. Input arguments for js method are values of 'inputs' and 'outputs', return should be a list of values for output components.
            concurrency_limit: If set, this is the maximum number of this event that can be running simultaneously. Can be set to None to mean no concurrency_limit (any number of this event can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `Blocks.queue()`, which itself is 1 by default).
            concurrency_id: If set, this is the id of the concurrency group. Events with the same concurrency_id will be limited by the lowest set concurrency_limit.
            show_api: whether to show this event in the "view API" page of the Gradio app, or in the ".view_api()" method of the Gradio clients. Unlike setting api_name to False, setting show_api to False will still allow downstream apps to use this event. If fn is None, show_api will automatically be set to False.
        """
        ...