import joblib
from sentence_transformers import SentenceTransformer

def load_model():
    clf = joblib.load("model/logistic_model.pkl")

    s2v_model = SentenceTransformer(
        "Pachinee/sentence2vec-brd"  # ← Hugging Face Model
    )

    return clf, s2v_model


def predict_label(texts, clf, s2v_model):
    embeddings = s2v_model.encode(list(texts))
    preds = clf.predict(embeddings)
    return ["Clear" if p == 1 else "Unclear" for p in preds]