initial

.gitignore

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+*.json
+*.py[oc]
+/secrets__.py
+/venv
+/cron.log

chain.py

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+import markovify
+import re
+import spacy
+
+SEPARATOR = r"\s*@@note@@\s*"
+
+nlp = spacy.load("en_core_web_sm")
+
+class Text(markovify.Text):
+    def word_split(self, sentence):
+        ret = []
+
+        for word in nlp(sentence):
+            if word.pos_ == 'PUNCT':
+                continue
+
+            ret.append("::".join((word.orth_, word.pos_)))
+
+        return ret
+
+    def word_join(self, words):
+        sentence = " ".join(word.split("::")[0] for word in words)
+        return sentence
+    
+    def sentence_split(self, text):
+        return re.split(SEPARATOR, text)

generate.py

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+import chain
+import sys
+import requests
+
+import secrets__
+
+model_f = open("model.json")
+model = chain.Text.from_json(model_f.read())
+
+generated = False
+text = None
+
+while not generated:
+    text = model.make_short_sentence(80, tries=900, min_words=3)
+    generated = text is not None
+
+text = text.replace('@','@​').replace('#','#​')
+print(text)
+
+requests.post("https://brain.d.on-t.work/api/notes/create", json={
+    'i': secrets__.TOKEN,
+
+    'visibility': 'home',
+    'noExtractMentions': True,
+    'noExtractHashtags': True,
+
+    'text': text,
+    'cw': 'markov chain generated post'
+})

import-misskey.py

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+import re
+import json
+import sys
+
+print('[+] loading nlp enhanced markov chain')
+import chain
+
+MENTION = re.compile(r'@[a-zA-Z0-9.-_]+(@[a-zA-Z0-9.]+-_)?')
+MFM_BEGIN = re.compile(r'\$\[[a-z0-9.,=]+')
+MFM_END = re.compile(r'\]+')
+HTML = re.compile(r'</?[a-z]+>')
+SPACE = re.compile(r'[ \n]+')
+CONTRACTION = re.compile(r"(\w+)'(\w+)")
+
+print('[+] loading note json')
+export_f = sys.argv[1]
+export = open(export_f)
+export_json = json.load(export)
+
+corpus = []
+
+for note in export_json:
+    if note.get('visibility') not in ['public', 'unlisted']:
+        continue
+
+    if note.get('localOnly'):
+        continue
+
+    if note.get('cw'):
+        continue
+
+    text = note.get('text')
+    if not text:
+        continue
+
+    text = text.lower() 
+    text = re.sub(MENTION, '', text)
+    text = re.sub(MFM_BEGIN, '', text)
+    text = re.sub(MFM_END, '', text)
+    text = re.sub(HTML, '', text)
+    text = re.sub(SPACE, ' ', text)
+    text = re.sub(CONTRACTION, r'\1\2', text)
+    text = text.strip()
+
+    print(f"     - {text}")
+    corpus.append(text)
+
+print('[+] building markov chain')
+model = chain.Text("@@note@@".join(corpus), well_formed=False)
+model_json = model.compile().to_json()
+
+print('[+] exporting')
+export = open(export_f.replace('.json', '.model.json'), 'w')
+export.write(model_json)

readme.txt

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+	pip install -r requirements.txt
+	python -m spacy download en_core_web_sm
+	python import-misskey.py notes-XXXX-XX-XX-XX-XX-XX.json
+	echo "TOKEN=''" > secrets__.py
+	python generate.py 

requirements.txt

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+markovify
+requests
+spacy