modules/overwrites.py

from __future__ import annotations
import logging

from llama_index import Prompt
from typing import List, Tuple
import mdtex2html
from gradio_client import utils as client_utils

from modules.presets import *
from modules.llama_func import *


def compact_text_chunks(self, prompt: Prompt, text_chunks: List[str]) -> List[str]:
    logging.debug("Compacting text chunks...🚀🚀🚀")
    combined_str = [c.strip() for c in text_chunks if c.strip()]
    combined_str = [f"[{index+1}] {c}" for index, c in enumerate(combined_str)]
    combined_str = "\n\n".join(combined_str)
    # resplit based on self.max_chunk_overlap
    text_splitter = self.get_text_splitter_given_prompt(prompt, 1, padding=1)
    return text_splitter.split_text(combined_str)


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, message_type: str
    ) -> str | Dict | None:
        if chat_message is None:
            return None
        elif isinstance(chat_message, (tuple, list)):
            filepath = chat_message[0]
            mime_type = client_utils.get_mimetype(filepath)
            filepath = self.make_temp_copy_if_needed(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):
            if message_type == "bot":
                if not detect_converted_mark(chat_message):
                    chat_message = convert_mdtext(chat_message)
            elif message_type == "user":
                if not detect_converted_mark(chat_message):
                    chat_message = convert_asis(chat_message)
            return chat_message
        else:
            raise ValueError(f"Invalid message for Chatbot component: {chat_message}")

with open("./assets/custom.js", "r", encoding="utf-8") as f, open("./assets/Kelpy-Codos.js", "r", encoding="utf-8") as f2:
    customJS = f.read()
    kelpyCodos = f2.read()

def reload_javascript():
    print("Reloading javascript...")
    js = f'<script>{customJS}</script><script>{kelpyCodos}</script>'
    def template_response(*args, **kwargs):
        res = GradioTemplateResponseOriginal(*args, **kwargs)
        res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
        res.init_headers()
        return res

    gr.routes.templates.TemplateResponse = template_response

GradioTemplateResponseOriginal = gr.routes.templates.TemplateResponse