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amber-ebooks-archived/create.py

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1.8 KiB
Python
Executable File

#!/usr/bin/env python3
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
import markovify
import json
import re, random, multiprocessing, time, sqlite3, shutil, os
def make_sentence(output):
class nlt_fixed(markovify.NewlineText):
def test_sentence_input(self, sentence):
return True #all sentences are valid <3
# with open("corpus.txt", encoding="utf-8") as fp:
# model = nlt_fixed(fp.read())
shutil.copyfile("toots.db", "toots-copy.db")
db = sqlite3.connect("toots-copy.db")
db.text_factory=str
c = db.cursor()
toots = c.execute("SELECT content FROM `toots`").fetchall()
toots_str = ""
for toot in toots:
toots_str += "\n{}".format(toot[0])
model = nlt_fixed(toots_str)
toots_str = None
db.close()
os.remove("toots-copy.db")
sentence = None
while sentence is None:
sentence = model.make_short_sentence(500, tries=10000)
sentence = re.sub("^@\u202B[^ ]* ", "", sentence)
output.send(sentence)
def make_toot(force_markov = False, args = None):
return make_toot_markov()
def make_toot_markov(query = None):
tries = 0
toot = None
while toot == None and tries < 25:
pin, pout = multiprocessing.Pipe(False)
p = multiprocessing.Process(target = make_sentence, args = [pout])
p.start()
p.join(10)
if p.is_alive():
p.terminate()
p.join()
toot = None
tries = tries + 1
else:
toot = pin.recv()
if toot == None:
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?"
return {
"toot":toot,
"media":None
}