from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity

def answer_question(question, docs):
    """
    Basit semantic search ile en uygun dokümanı seçer
    """
    try:
        vectorizer = TfidfVectorizer()
        X = vectorizer.fit_transform(docs + [question])
        similarities = cosine_similarity(X[-1], X[:-1])
        best_idx = similarities.argmax()
        return docs[best_idx]
    except Exception as e:
        return f"Cevap üretilemedi: {e}"