"""
Script de chargement pour le modèle logistic regression
"""
import pickle
import numpy as np
from huggingface_hub import hf_hub_download

def load_logistic_model(repo_id="Carlito-25/sentiment-model-logistic"):
    """Charge le modèle logistic regression depuis Hugging Face"""
    model_path = hf_hub_download(
        repo_id=repo_id,
        filename="model.pkl"
    )
    
    with open(model_path, 'rb') as f:
        model = pickle.load(f)
    
    return model

def predict_sentiment(model, text_features):
    """Prédiction avec le modèle logistic regression"""
    if isinstance(text_features, list):
        text_features = np.array(text_features).reshape(1, -1)
    
    prediction = model.predict(text_features)
    probabilities = model.predict_proba(text_features)
    
    return {
        'prediction': prediction[0],
        'probabilities': probabilities[0].tolist()
    }

# Exemple d'usage
if __name__ == "__main__":
    model = load_logistic_model()
    # Remplace par tes features réelles
    dummy_features = np.random.rand(1, 100)  # Adapte selon tes features
    result = predict_sentiment(model, dummy_features)
    print(result)