utils.py

import joblib
import pandas as pd

def load_artifacts():
    """Load the trained pipeline and target encoder."""
    pipeline = joblib.load("models/network_logs_pipeline.joblib")
    target_encoder = joblib.load("models/target_encoder.joblib")
    return pipeline, target_encoder


def predict_intrusion(pipeline, target_encoder, features: dict):
    """

    Predict Scan_Type from input features.

    

    Args:

        pipeline: sklearn pipeline with preprocessing + model

        target_encoder: LabelEncoder for Scan_Type

        features: dict of input features



    Returns:

        str: Predicted Scan_Type

    """
    input_df = pd.DataFrame([features])  # single row DataFrame
    pred_label = pipeline.predict(input_df)[0]
    scan_type = target_encoder.inverse_transform([pred_label])[0]
    return scan_type