model_loader.py

from transformers import pipeline

# Liste des modèles de summarization plus légers
MODEL_OPTIONS = [
    "Falconsai/text_summarization",  # Original
    "facebook/bart-large-cnn",       # Alternative 1
    "t5-small",                      # Alternative 2 (léger)
    "mrm8488/bert-mini-finetuned-cnn_daily_mail-summarization"  # Alternative 3
]

summarizer = None  # Global

def load_model_with_fallback():
    for model_name in MODEL_OPTIONS:
        try:
            print(f"Tentative de chargement: {model_name}")
            model = pipeline("summarization", model=model_name)
            print(f"Succès avec: {model_name}")
            return model
        except Exception as e:
            print(f"Échec avec {model_name}: {e}")
            continue
    raise Exception("Aucun modèle n'a pu être chargé")

def get_summarizer():
    global summarizer
    if summarizer is None:
        summarizer = load_model_with_fallback()
    return summarizer