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from __future__ import annotations
import logging

from typing import List, Tuple
from gradio_client import utils as client_utils
from gradio import utils
import inspect

from modules.presets import *
from modules.index_func import *


def postprocess(
        self,
        y: List[List[str | Tuple[str] | Tuple[str, str] | None] | Tuple],
    ) -> List[List[str | Dict | None]]:
        """
        Parameters:
            y: List of lists representing the message and response pairs. Each message and response should be a string, which may be in Markdown format.  It can also be a tuple whose first element is a string filepath or URL to an image/video/audio, and second (optional) element is the alt text, in which case the media file is displayed. It can also be None, in which case that message is not displayed.
        Returns:
            List of lists representing the message and response. Each message and response will be a string of HTML, or a dictionary with media information. Or None if the message is not to be displayed.
        """
        if y is None:
            return []
        processed_messages = []
        for message_pair in y:
            assert isinstance(
                message_pair, (tuple, list)
            ), f"Expected a list of lists or list of tuples. Received: {message_pair}"
            assert (
                len(message_pair) == 2
            ), f"Expected a list of lists of length 2 or list of tuples of length 2. Received: {message_pair}"

            processed_messages.append(
                [
                    self._postprocess_chat_messages(message_pair[0], "user"),
                    self._postprocess_chat_messages(message_pair[1], "bot"),
                ]
            )
        return processed_messages

def postprocess_chat_messages(
        self, chat_message: str | tuple | list | None, role: str
    ) -> str | dict | None:
        if chat_message is None:
            return None
        elif isinstance(chat_message, (tuple, list)):
            file_uri = chat_message[0]
            if utils.validate_url(file_uri):
                filepath = file_uri
            else:
                filepath = self.make_temp_copy_if_needed(file_uri)

            mime_type = client_utils.get_mimetype(filepath)
            return {
                "name": filepath,
                "mime_type": mime_type,
                "alt_text": chat_message[1] if len(chat_message) > 1 else None,
                "data": None,  # These last two fields are filled in by the frontend
                "is_file": True,
            }
        elif isinstance(chat_message, str):
            # chat_message = inspect.cleandoc(chat_message)
            # escape html spaces
            # chat_message = chat_message.replace(" ", " ")
            if role == "bot":
                chat_message = convert_bot_before_marked(chat_message)
            elif role == "user":
                chat_message = convert_user_before_marked(chat_message)
            return chat_message
        else:
            raise ValueError(f"Invalid message for Chatbot component: {chat_message}")



def add_classes_to_gradio_component(comp):
    """
    this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others
    code from stable-diffusion-webui <AUTOMATIC1111/stable-diffusion-webui>
    """

    comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])]

    if getattr(comp, 'multiselect', False):
        comp.elem_classes.append('multiselect')


def IOComponent_init(self, *args, **kwargs):
    res = original_IOComponent_init(self, *args, **kwargs)
    add_classes_to_gradio_component(self)

    return res

original_IOComponent_init = gr.components.IOComponent.__init__
gr.components.IOComponent.__init__ = IOComponent_init


def BlockContext_init(self, *args, **kwargs):
    res = original_BlockContext_init(self, *args, **kwargs)
    add_classes_to_gradio_component(self)

    return res

original_BlockContext_init = gr.blocks.BlockContext.__init__
gr.blocks.BlockContext.__init__ = BlockContext_init