"""
VisionManager - Main class for managing vision-based interactions with AI systems.
"""

class VisionManager:
    """
    Main class for managing vision-based AI interactions.
    
    This class serves as the primary interface for text-to-image, image-to-image,
    text-to-video, and image-to-video capabilities.
    """
    
    def __init__(self, debug_mode=False):
        """
        Initialize the VisionManager.
        
        Args:
            debug_mode (bool): Whether to enable debug logging.
        """
        self.debug_mode = debug_mode
        self._processing = False
        
        if self.debug_mode:
            print("VisionManager initialized in debug mode")
    
    def text_to_image(self, prompt, callback=None):
        """
        Generate an image from a text prompt.
        
        Args:
            prompt (str): The text prompt to generate an image from.
            callback (callable, optional): Function to call with the generated image.
            
        Returns:
            Image object or None if processing asynchronously.
        """
        self._processing = True
        if self.debug_mode:
            print(f"Processing text-to-image: {prompt}")
        
        # Placeholder for actual implementation
        # In the future, this will connect to image generation models
        
        self._processing = False
        return None
    
    def image_to_image(self, image, prompt=None, callback=None):
        """
        Transform an image based on optional text prompt.
        
        Args:
            image: The input image to transform.
            prompt (str, optional): Text guidance for the transformation.
            callback (callable, optional): Function to call with the generated image.
            
        Returns:
            Image object or None if processing asynchronously.
        """
        self._processing = True
        if self.debug_mode:
            print(f"Processing image-to-image with prompt: {prompt}")
        
        # Placeholder for actual implementation
        
        self._processing = False
        return None
    
    def text_to_video(self, prompt, duration=5.0, callback=None):
        """
        Generate a video from a text prompt.
        
        Args:
            prompt (str): The text prompt to generate a video from.
            duration (float): Length of video in seconds.
            callback (callable, optional): Function to call with the generated video.
            
        Returns:
            Video object or None if processing asynchronously.
        """
        self._processing = True
        if self.debug_mode:
            print(f"Processing text-to-video: {prompt}, duration: {duration}s")
        
        # Placeholder for actual implementation
        
        self._processing = False
        return None
    
    def image_to_video(self, image, prompt=None, duration=5.0, callback=None):
        """
        Generate a video from an image, optionally guided by text.
        
        Args:
            image: The input image to animate.
            prompt (str, optional): Text guidance for the animation.
            duration (float): Length of video in seconds.
            callback (callable, optional): Function to call with the generated video.
            
        Returns:
            Video object or None if processing asynchronously.
        """
        self._processing = True
        if self.debug_mode:
            print(f"Processing image-to-video with prompt: {prompt}, duration: {duration}s")
        
        # Placeholder for actual implementation
        
        self._processing = False
        return None
    
    def is_processing(self):
        """
        Check if the manager is currently processing a request.
        
        Returns:
            bool: True if processing, False otherwise.
        """
        return self._processing
    
    def stop_processing(self):
        """
        Attempt to stop any ongoing processing.
        
        Returns:
            bool: True if successfully stopped, False otherwise.
        """
        if not self._processing:
            return True
        
        # Placeholder for actual implementation
        self._processing = False
        return True
    
    def cleanup(self):
        """
        Release any resources held by the manager.
        """
        if self.debug_mode:
            print("Cleaning up VisionManager resources")
        
        # Stop any ongoing processing
        self.stop_processing()
        
        # Placeholder for additional cleanup logic 