import torch
import coremltools as ct
import comfy.latent_formats


class CoreMLHunyuanVideoWrapper(torch.nn.Module):
    """Adapts HunyuanVideo Core ML model to ComfyUI's video sampling interface"""
    def __init__(self, model_path, num_frames):
        super().__init__()
        self.coreml_model = ct.models.MLModel(model_path)
        self.num_frames = num_frames

        # Video-specific configuration
        self.latent_format = comfy.latent_formats.SDXL()  # Placeholder
        self.adm_channels = 0

    def forward(self, x, timestep, **kwargs):
        """
        HunyuanVideo forward pass
        x: Video latents (B, C, F, H, W) - 5D tensor
        timestep: Tensor (B,)
        """
        # TODO: Implement Hunyuan-specific packing/unpacking
        raise NotImplementedError("HunyuanVideo ComfyUI integration coming soon! Use CLI for now.")


class CoreMLLuminaWrapper(torch.nn.Module):
    """Adapts Lumina Image 2.0 Core ML model to ComfyUI's sampling interface"""
    def __init__(self, model_path):
        super().__init__()
        self.coreml_model = ct.models.MLModel(model_path)

        # Image-specific configuration
        self.latent_format = comfy.latent_formats.SDXL()  # Placeholder
        self.adm_channels = 0

    def forward(self, x, timestep, **kwargs):
        """
        Lumina Image forward pass
        x: Image latents (B, C, H, W) - 4D tensor
        timestep: Tensor (B,)
        """
        # TODO: Implement Lumina-specific packing/unpacking
        raise NotImplementedError("Lumina Image 2.0 ComfyUI integration coming soon! Use CLI for now.")


class CoreMLLTXVideoWrapper(torch.nn.Module):
    """Adapts LTX-Video Core ML model to ComfyUI's video sampling interface"""
    def __init__(self, model_path, num_frames):
        super().__init__()
        self.coreml_model = ct.models.MLModel(model_path)
        self.num_frames = num_frames
        
        # Video-specific configuration
        self.latent_format = comfy.latent_formats.SDXL()  # Placeholder
        self.adm_channels = 0
        
    def forward(self, x, timestep, **kwargs):
        """
        LTX-Video forward pass
        x: Video latents (B, C, F, H, W) - 5D tensor
        timestep: Tensor (B,)
        """
        # TODO: Implement LTX-specific packing/unpacking
        # For now, placeholder that will error gracefully
        raise NotImplementedError("LTX-Video ComfyUI integration coming soon! Use CLI for now.")


class CoreMLWanVideoWrapper(torch.nn.Module):
    """Adapts Wan Core ML model to ComfyUI's video sampling interface"""
    def __init__(self, model_path, num_frames):
        super().__init__()
        self.coreml_model = ct.models.MLModel(model_path)
        self.num_frames = num_frames
        
        # Video-specific configuration
        self.latent_format = comfy.latent_formats.SDXL()  # Placeholder
        self.adm_channels = 0
        
    def forward(self, x, timestep, **kwargs):
        """
        Wan Video forward pass
        x: Video latents (B, C, F, H, W) - 5D tensor
        timestep: Tensor (B,)
        """
        # TODO: Implement Wan-specific packing/unpacking
        # For now, placeholder that will error gracefully
        raise NotImplementedError("Wan Video ComfyUI integration coming soon! Use CLI for now.")
