116 lines
3.3 KiB
Python
116 lines
3.3 KiB
Python
from argparse import ArgumentParser
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from random import randint, choice
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from torch import float16
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from transformers import AutoTokenizer, AutoModelForCausalLM
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parser = ArgumentParser()
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parser.add_argument('-b', '--backend', choices=['mastodon', 'misskey', 'matrix', 'none'], default='mastodon',
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help='fediverse server type')
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parser.add_argument('-i', '--instance', help='Mastodon instance hosting the bot')
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parser.add_argument('-t', '--token', help='Mastodon application access token')
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parser.add_argument('-n', '--input', help='initial input text')
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parser.add_argument('-d', '--data', default='data',
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help='data for automatic input generation')
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parser.add_argument('-m', '--model', default='model',
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help='path to load saved model')
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args = parser.parse_args()
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tokenizer = AutoTokenizer.from_pretrained('gpt2-medium')
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model = AutoModelForCausalLM.from_pretrained(args.model, low_cpu_mem_usage=True).to('cuda')
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if args.input is None:
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# Create random input
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if randint(0, 1) == 0:
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args.input = choice([
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'I am',
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'My life is',
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'Computers are',
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'This is',
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'My',
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'I\'ve',
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'No one',
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'I love',
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'I will die of',
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'I',
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'The',
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'Anime',
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'I\'m going to die',
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'Hello',
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'@ta180m@exozy.me',
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'Life',
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'My favorite',
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'I\'m not',
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'I hate',
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'I think',
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'In my opinion',
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'Breaking news:',
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'Have I ever told you that',
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'I read on the news that',
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'I never knew that',
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'My dream is',
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'It\'s terrible that'
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])
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else:
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with open(args.data, 'r') as f:
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# Get a line with at least two words
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lines = f.readlines()
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line = choice(lines).split()
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while len(line) < 2:
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line = choice(lines).split()
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# Remove mentions
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if line[0].count('@') > 1:
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line[0] = '@'.join(line[0].split('@')[0:2])
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if line[1].count('@') > 1:
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line[1] = '@'.join(line[1].split('@')[0:2])
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args.input = line[0] + ' ' + line[1]
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# Run the input through the model
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print(args.input)
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inputs = tokenizer.encode(args.input, return_tensors='pt').to('cuda')
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output = tokenizer.decode(model.generate(
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inputs, max_length=150, do_sample=True, top_p=0.9)[0])
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print(output)
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# Prepare the post
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output = output.split('\n')
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post = output[0]
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if len(post) < 200 and len(output) > 1:
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post = output[0] + '\n' + output[1]
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post = post[:500]
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# Post it!
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if args.backend == 'mastodon':
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from mastodon import Mastodon
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mastodon = Mastodon(
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access_token=args.token,
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api_base_url=args.instance
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)
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mastodon.status_post(post)
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elif args.backend == 'misskey':
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from Misskey import Misskey
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misskey = Misskey(args.instance, i=args.token)
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misskey.notes_create(post)
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elif args.backend == 'matrix':
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import simplematrixbotlib as botlib
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creds = botlib.Creds(args.instance, 'ebooks', args.token)
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bot = botlib.Bot(creds)
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@bot.listener.on_startup
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async def room_joined(room_id):
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await bot.api.send_text_message(room_id=room_id, message=post)
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bot.run()
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