"""Model architecture registry and factory."""

from typing import Dict, Type, Optional
import torch
from taoTrain.core import BaseModel
from taoTrain.config import ModelConfig


# Global registry for model architectures
_ARCHITECTURE_REGISTRY: Dict[str, Type[BaseModel]] = {}


def register_architecture(name: str):
    """Decorator to register a custom model architecture."""
    def decorator(cls: Type[BaseModel]):
        if name in _ARCHITECTURE_REGISTRY:
            raise ValueError(f"Architecture '{name}' is already registered")
        _ARCHITECTURE_REGISTRY[name] = cls
        return cls
    return decorator


def get_registered_architectures() -> Dict[str, Type[BaseModel]]:
    """Get all registered architectures."""
    return _ARCHITECTURE_REGISTRY.copy()


def get_model(
    config: ModelConfig,
    device: Optional[torch.device] = None,
) -> BaseModel:
    """
    Create a model instance from config.
    
    Args:
        config: ModelConfig instance
        device: Device to create model on (defaults to CPU)
    
    Returns:
        Model instance
    """
    if device is None:
        device = torch.device('cpu')
    
    # Handle both enum and string values
    arch_type = config.architecture_type
    if isinstance(arch_type, str):
        arch_name = arch_type
    else:
        arch_name = arch_type.value
    
    if arch_name not in _ARCHITECTURE_REGISTRY:
        raise ValueError(
            f"Unknown architecture: {arch_name}. "
            f"Available: {list(_ARCHITECTURE_REGISTRY.keys())}"
        )
    
    model_class = _ARCHITECTURE_REGISTRY[arch_name]
    model = model_class(config).to(device)
    
    return model


def register_builtin_architectures():
    """Register all built-in architectures."""
    # Import here to register (avoid circular imports)
    from . import transformer  # noqa: F401
    from . import taonet  # noqa: F401
    from . import taonet_ssm  # noqa: F401


# Auto-register built-in architectures when module is imported
register_builtin_architectures()