"""
Custom exception types for the Model Manager.

This module defines domain-specific exceptions used across the training
workflow to convey additional context (e.g., flags indicating which steps
completed successfully) without altering control flow semantics.
"""


class ModelTrainingError(Exception):
    """
    Exception raised when the model training workflow fails.

    This exception carries flags indicating whether the model was trained
    and/or saved successfully, enabling the workflow to map errors to
    appropriate experiment statuses.
    """

    def __init__(self, model_trained: bool, model_saved: bool, message: str | None = None):
        """
        Initialize ModelTrainingError with training state flags.

        Args:
            model_trained: True if the training step completed successfully.
            model_saved: True if the model saving step completed successfully.
            message: Optional custom error message. If None, a default message
                including the state flags is generated.
        """
        self.model_trained = model_trained
        self.model_saved = model_saved

        if message is None:
            message = (
                'Model training workflow failed '
                f'(model_trained={model_trained}, model_saved={model_saved})'
            )

        super().__init__(message)