from typing import Dict, Any, Optional, List


def predict_food_insecurity_levels(
    features: List[str],
    target: str = "fci_next_month",
    model_type: str = "lgbm",
    horizon_days: int = 30,
    classification_scheme: str = "ipc"
) -> Dict[str, Any]:
    """
    Predict Food Insecurity Levels (placeholder intent)

    Parameters
    ----------
    features : list[str]
        Feature columns (markets, rainfall, wages, rcsi, fcs, etc.).
    target : str
        Target column to predict (numeric/class labels).
    model_type : str
        e.g., "lgbm", "xgboost", "rf".
    horizon_days : int
        Forecast horizon.
    classification_scheme : str
        e.g., "ipc" for IPC scale mapping (optional).
    """
    return {
        "type": "ml_predict_food_insecurity",
        "model_type": model_type,
        "features_count": len(features),
        "target": target,
        "horizon_days": horizon_days,
        "classification_scheme": classification_scheme,
        "preview": {"will_train": True, "expected_outputs": ["predictions", "feature_importance", "cv_metrics"]},
    }
