forked from KayFaraday/pleroma-ebooks
60 lines
1.8 KiB
Python
Executable File
60 lines
1.8 KiB
Python
Executable File
#!/usr/bin/env python3
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# This Source Code Form is subject to the terms of the Mozilla Public
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# License, v. 2.0. If a copy of the MPL was not distributed with this
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# file, You can obtain one at http://mozilla.org/MPL/2.0/.
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import markovify
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import json
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import re, random, multiprocessing, time, sqlite3, shutil, os
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def make_sentence(output):
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class nlt_fixed(markovify.NewlineText):
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def test_sentence_input(self, sentence):
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return True #all sentences are valid <3
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# with open("corpus.txt", encoding="utf-8") as fp:
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# model = nlt_fixed(fp.read())
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shutil.copyfile("toots.db", "toots-copy.db")
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db = sqlite3.connect("toots-copy.db")
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db.text_factory=str
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c = db.cursor()
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toots = c.execute("SELECT content FROM `toots`").fetchall()
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toots_str = ""
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for toot in toots:
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toots_str += "\n{}".format(toot[0])
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model = nlt_fixed(toots_str)
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toots_str = None
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db.close()
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os.remove("toots-copy.db")
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sentence = None
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while sentence is None or re.match("^@\u202B", sentence):
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sentence = model.make_short_sentence(500, tries=10000)
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output.send(sentence)
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def make_toot(force_markov = False, args = None):
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return make_toot_markov()
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def make_toot_markov(query = None):
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tries = 0
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toot = None
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while toot == None and tries < 25:
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pin, pout = multiprocessing.Pipe(False)
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p = multiprocessing.Process(target = make_sentence, args = [pout])
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p.start()
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p.join(10)
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if p.is_alive():
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p.terminate()
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p.join()
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toot = None
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tries = tries + 1
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else:
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toot = pin.recv()
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if toot == None:
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toot = "Mistress @lynnesbian@fedi.lynnesbian.space, I was unable to generate a toot using the markov method! This probably means that my corpus wasn't big enough... I need them to be big, Mistress, otherwise I won't work... Can you, um, help me with that, somehow?"
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return {
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"toot":toot,
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"media":None
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}
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