from transformers import AutoModelForCausalLM, AutoTokenizer

from ai_sentence import load_model

# 生成選擇題
def generate_mcq(word, model_name):
    tokenizer, model = load_model(model_name)

    prompt = f"Write a simple multiple-choice English question for beginners using the word '{word}'. Provide 4 options labeled A, B, C, D, and mark the correct answer."
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(
        **inputs,
        max_new_tokens=50,
        temperature=0.7,
        top_p=0.9
    )
    question = tokenizer.decode(outputs[0], skip_special_tokens=True)

    return question

# 對答案（未來補）
def check_answer(user_answer, correct_answer):
    return user_answer == correct_answer

# 計算分數（未來補）
def calculate_score(total, correct):
    return f"{correct}/{total} 分"