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from __future__ import annotations | |
import logging | |
from llama_index import Prompt | |
from typing import List, Tuple | |
import mdtex2html | |
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...πππ") | |
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[Tuple[str | None, str | None]] | |
) -> List[Tuple[str | None, str | None]]: | |
""" | |
Parameters: | |
y: List of tuples representing the message and response pairs. Each message and response should be a string, which may be in Markdown format. | |
Returns: | |
List of tuples representing the message and response. Each message and response will be a string of HTML. | |
""" | |
if y is None or y == []: | |
return [] | |
user, bot = y[-1] | |
if not detect_converted_mark(user): | |
user = convert_asis(user) | |
if not detect_converted_mark(bot): | |
bot = convert_mdtext(bot) | |
y[-1] = (user, bot) | |
return y | |
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 |