from transformers import pipeline

# Load sentiment-analysis model
def load_model():
    return pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")

# Predict anomaly for each log line
def detect_anomaly(model, logs):
    results = model(logs)
    predictions = []
    for result in results:
        # Treat negative sentiment as Anomaly, positive/neutral as Normal
        if result['label'] == 'NEGATIVE':
            predictions.append("Anomaly")
        else:
            predictions.append("Normal")
    return predictions