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from __future__ import annotations |
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import logging |
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from llama_index import Prompt |
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from typing import List, Tuple |
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import mdtex2html |
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from gradio_client import utils as client_utils |
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from modules.presets import * |
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from modules.llama_func import * |
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def compact_text_chunks(self, prompt: Prompt, text_chunks: List[str]) -> List[str]: |
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logging.debug("Compacting text chunks...🚀🚀🚀") |
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combined_str = [c.strip() for c in text_chunks if c.strip()] |
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combined_str = [f"[{index+1}] {c}" for index, c in enumerate(combined_str)] |
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combined_str = "\n\n".join(combined_str) |
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text_splitter = self.get_text_splitter_given_prompt(prompt, 1, padding=1) |
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return text_splitter.split_text(combined_str) |
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def postprocess( |
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self, |
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y: List[List[str | Tuple[str] | Tuple[str, str] | None] | Tuple], |
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) -> List[List[str | Dict | None]]: |
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""" |
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Parameters: |
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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. |
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Returns: |
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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. |
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""" |
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if y is None: |
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return [] |
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processed_messages = [] |
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for message_pair in y: |
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assert isinstance( |
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message_pair, (tuple, list) |
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), f"Expected a list of lists or list of tuples. Received: {message_pair}" |
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assert ( |
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len(message_pair) == 2 |
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), f"Expected a list of lists of length 2 or list of tuples of length 2. Received: {message_pair}" |
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processed_messages.append( |
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[ |
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self._postprocess_chat_messages(message_pair[0], "user"), |
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self._postprocess_chat_messages(message_pair[1], "bot"), |
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] |
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) |
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return processed_messages |
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def postprocess_chat_messages( |
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self, chat_message: str | Tuple | List | None, message_type: str |
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) -> str | Dict | None: |
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if chat_message is None: |
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return None |
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elif isinstance(chat_message, (tuple, list)): |
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filepath = chat_message[0] |
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mime_type = client_utils.get_mimetype(filepath) |
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filepath = self.make_temp_copy_if_needed(filepath) |
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return { |
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"name": filepath, |
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"mime_type": mime_type, |
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"alt_text": chat_message[1] if len(chat_message) > 1 else None, |
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"data": None, |
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"is_file": True, |
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} |
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elif isinstance(chat_message, str): |
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if message_type == "bot": |
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if not detect_converted_mark(chat_message): |
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chat_message = convert_mdtext(chat_message) |
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elif message_type == "user": |
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if not detect_converted_mark(chat_message): |
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chat_message = convert_asis(chat_message) |
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return chat_message |
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else: |
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raise ValueError(f"Invalid message for Chatbot component: {chat_message}") |
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with open("./assets/custom.js", "r", encoding="utf-8") as f, open("./assets/Kelpy-Codos.js", "r", encoding="utf-8") as f2: |
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customJS = f.read() |
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kelpyCodos = f2.read() |
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def reload_javascript(): |
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print("Reloading javascript...") |
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js = f'<script>{customJS}</script><script>{kelpyCodos}</script>' |
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def template_response(*args, **kwargs): |
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res = GradioTemplateResponseOriginal(*args, **kwargs) |
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res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8")) |
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res.init_headers() |
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return res |
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gr.routes.templates.TemplateResponse = template_response |
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GradioTemplateResponseOriginal = gr.routes.templates.TemplateResponse |
