from argparse import ArgumentParser

from mastodon import Mastodon
from transformers import AutoTokenizer, AutoModelForCausalLM


parser = ArgumentParser()
parser.add_argument('-t', '--token', help='Mastodon application access token')
parser.add_argument('-i', '--input', help='initial input text for prediction')
parser.add_argument('-m', '--model', default='model',
                    help='path to load saved model')
args = parser.parse_args()


tokenizer = AutoTokenizer.from_pretrained('distilgpt2')
model = AutoModelForCausalLM.from_pretrained(args.model)


# Run the input through the model
inputs = tokenizer.encode(args.input, return_tensors="pt")
output = tokenizer.decode(model.generate(
    inputs, do_sample=True, max_length=25, top_p=0.9, temperature=0.8)[0])
print(output)


# Post it to Mastodon
mastodon = Mastodon(
    access_token=args.token,
    api_base_url='https://social.exozy.me/'
)
mastodon.status_post(output)