from rosaplus import ROSAPlus
# import requests

# # Train on Shakespare
# url = "https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt"

# # Download the text
# response = requests.get(url)
# text = response.text
# print("Downloaded text.")


# m2 = ROSAPlus.load("rosa-model.json")
# prompt = "ROMEO:" # Novel text
# max_tokens = 256
# print(prompt + m2.generate(prompt, steps=max_tokens))



with open('tinyshakespeare.txt', "r", encoding='UTF-8') as f:
    text = f.read()

# Initialize model
m = ROSAPlus(max_order=1048576, use_eot=False, seed=0) 
m.train_example(text) # Train ROSA
m.build_lm() # Train fallback predictor

# Prompting
prompt = "ROMEO:" # Novel text
max_tokens = 256

# Eval mode
print(prompt + m.generate(prompt, steps=max_tokens))

# Saving model
m.save("rosa-model.json")
m2 = ROSAPlus.load("rosa-model.json") # Loading model