welcomecenterbot/nlp/replying.py
2024-02-12 17:39:58 +03:00

60 lines
1.5 KiB
Python

# "👍", "👎", "❤", "🔥", "🥰", "👏", "😁",
# "🤔", "🤯", "😱", "🤬", "😢", "🎉", "🤩",
# "🤮", "💩", "🙏", "👌", "🕊", "🤡", "🥱",
# "🥴", "😍", "🐳", "❤‍🔥", "🌚", "🌭", "💯",
# "🤣", "⚡", "🍌", "🏆", "💔", "🤨", "😐",
# "🍓", "🍾", "💋", "🖕", "😈", "😴", "😭",
# "🤓", "👻", "👨‍💻", "👀", "🎃", "🙈", "😇",
# "😨", "🤝", "✍", "🤗", "🫡", "🎅", "🎄",
# "☃", "💅", "🤪", "🗿", "🆒", "💘", "🙉",
# "🦄", "😘", "💊", "🙊", "😎", "👾", "🤷‍♂",
# "🤷", "🤷‍♀", "😡"
toxic_reactions = {
"071": "🕊",
"073": "👀",
"075": "🙈",
"077": "🙊",
"079": "🙏",
"081": "🤔",
"083": "😐",
"085": "🤨",
"087": "🥴",
"089": "🤯",
"091": "😢",
"093": "😭",
"095": "😨",
"097": "😱",
"099": "🤬"
}
grads = list(toxic_reactions.keys())
grads.sort()
grads.reverse()
abusive_reactions = {
"085": "🫡",
"088": "💅",
"091": "🤷‍♀",
"094": "👾",
"097": "👻",
"099": "😈"
}
abusive_grads = list(abusive_reactions.keys())
abusive_grads.sort()
abusive_grads.reverse()
def get_toxic_reply(tx):
percentage = tx * 100
for key in grads:
if percentage > int(key):
return toxic_reactions[key]
def get_abusive_reply(tx):
percentage = tx * 100
for key in abusive_grads:
if percentage > int(key):
return abusive_reactions[key]