import torch
from transpolymer_model.model import TransPolymer
from transpolymer_model.tokenizer import PolymerTokenizer

def load_model_and_tokenizer():
    tokenizer = PolymerTokenizer()
    model = TransPolymer.from_pretrained("pretrained/transpolymer")  # ubah ikut lokasi sebenar
    model.eval()
    return tokenizer, model

def preprocess_input(smiles, temp, mw):
    return f"{smiles} ${temp} ${mw}"

def predict_property(input_seq, model, tokenizer):
    inputs = tokenizer(input_seq, return_tensors="pt")
    with torch.no_grad():
        output = model(**inputs)
    return output.item()