import torch
from model.brain import model, optimizer, loss_fn, tokenizer, DEVICE


def train_on_message(text: str):
    model.train()
    tokens = tokenizer.tokenize(text)
    if len(tokens) < 2:
        return

    input_tensor = torch.tensor(tokens[:-1], dtype=torch.long, device=DEVICE).unsqueeze(0)
    target_tensor = torch.tensor(tokens[1:], dtype=torch.long, device=DEVICE).unsqueeze(0)

    output = model(input_tensor)
    loss = loss_fn(output.view(-1, output.size(-1)), target_tensor.view(-1))

    optimizer.zero_grad()
    loss.backward()
    optimizer.step()