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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 |