mirror of
https://gitlab.com/vylion/velascobot.git
synced 2025-04-19 21:46:35 +02:00
1d1bd6034e
- It now saves the dictionary of vocabulary directly into the file. No need to deal with the full list of messages. - This also means that the amount of elements kept in memory has been reduced, since there is no need to keep a list with all the words one after another,apart from the dictionary. - Modularized some constants, like the frequency of saves if the frequency of speaking is too large, or the stop words that mark the start and end of a message.
61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
#!/usr/bin/env python3
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from markov import *
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class Chatlog(object):
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def __init__(self, ident, chattype, title, text=None, freq=None):
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self.id = str(ident)
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self.type = chattype
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self.title = title
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if freq is None:
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if "group" in chattype:
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freq = 15
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#elif chattype is "private":
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else:
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freq = 2
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self.freq = freq
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if text is not None:
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self.count = len(text)
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else:
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self.count = 0
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self.gen = Markov(text)
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def set_title(self, title):
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self.title = title
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def set_freq(self, freq):
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if not freq > 0:
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raise ValueError('Tried to set 0 or negative freq value.')
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elif freq > 100000:
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freq = 100000
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self.freq = freq
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return self.freq
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def add_msg(self, message):
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self.gen.add_text(message + " !kvl")
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self.count += 1
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def speak(self):
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return self.gen.generate_markov_text()
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def get_count(self):
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return self.count
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def to_txt(self):
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lines = [self.id]
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lines.append(self.type)
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lines.append(self.title)
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lines.append(str(self.freq))
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lines.append("dict:")
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txt = '\n'.join(lines)
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return txt + '\n' + self.gen.to_json()
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def from_txt(text):
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lines = text.splitlines()
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if(lines[4] == "dict:"):
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new_log = Chatlog(lines[0], lines[1], lines[2], None, int(lines[3]))
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cache = '\n'.join(lines[5:])
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new_log.gen = Markov.from_json(cache)
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return new_log
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else:
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return Chatlog(lines[0], lines[1], lines[2], lines[4:], int(lines[3]))
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