from typing import Any, List, Tuple

import numpy as np


def forecast_recursive(
    model: Any,
    scaler: Any,
    window: np.ndarray,
    horizon: int,
) -> Tuple[List[float], bool]:
    values = np.asarray(window, dtype=float).reshape(-1, 1)
    scaled_window = scaler.transform(values)
    scaled_predictions = []

    for _ in range(horizon):
        model_input = scaled_window.reshape(1, len(scaled_window), 1)
        prediction = model.predict(model_input, verbose=0)
        prediction_value = float(np.asarray(prediction).reshape(-1)[0])
        scaled_predictions.append(prediction_value)
        scaled_window = np.vstack([scaled_window[1:], [[prediction_value]]])

    predicted_values = scaler.inverse_transform(
        np.asarray(scaled_predictions, dtype=float).reshape(-1, 1)
    ).reshape(-1)
    data_min = float(np.asarray(scaler.data_min_).reshape(-1)[0])
    data_max = float(np.asarray(scaler.data_max_).reshape(-1)[0])
    out_of_range = bool(np.any((predicted_values < data_min) | (predicted_values > data_max)))
    prices = [max(0.0, float(np.round(value, 6))) for value in predicted_values]
    return prices, out_of_range