File size: 3,200 Bytes
79cf446
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
# Copyright (c) 2023-2024 DeepSeek.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of
# this software and associated documentation files (the "Software"), to deal in
# the Software without restriction, including without limitation the rights to
# use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
# the Software, and to permit persons to whom the Software is furnished to do so,
# subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
# FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
# COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
# IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

from __future__ import annotations

import logging
from typing import List, Tuple

from app_modules.presets import gr
from app_modules.utils import convert_asis, convert_mdtext, detect_converted_mark


def compact_text_chunks(self, 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[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 []
    temp = []
    for x in y:
        user, bot = x
        if not detect_converted_mark(user):
            user = convert_asis(user)
        if not detect_converted_mark(bot):
            bot = convert_mdtext(bot)
        temp.append((user, bot))
    return temp


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