"""
models/__init__.py
──────────────────
Factory that maps the loader name string (from ModelConfig.loader)
to the actual class, so pipeline.py never needs to import concrete loaders.
"""

from __future__ import annotations

import torch

from models.base_loader import BaseLoader
from models.background_removal import BiRefNetLoader
from models.depth_estimation import TransformersDepthLoader
from models.reconstruction import (
    Open3DReconstructionLoader,
    GaussianSplatLoader,
    DepthSplatLoader,
)

_LOADER_MAP: dict[str, type[BaseLoader]] = {
    "BiRefNetLoader": BiRefNetLoader,
    "TransformersDepthLoader": TransformersDepthLoader,
    "Open3DReconstructionLoader": Open3DReconstructionLoader,
    "GaussianSplatLoader": GaussianSplatLoader,
    "DepthSplatLoader": DepthSplatLoader,
}


def build_loader(loader_name: str, model_id: str, device: torch.device, **kwargs) -> BaseLoader:
    """Instantiate a loader by name string."""
    cls = _LOADER_MAP.get(loader_name)
    if cls is None:
        raise ValueError(
            f"Unknown loader: {loader_name!r}. "
            f"Available: {list(_LOADER_MAP)}"
        )
    return cls(model_id=model_id, device=device, **kwargs)


__all__ = [
    "BaseLoader",
    "BiRefNetLoader",
    "TransformersDepthLoader",
    "Open3DReconstructionLoader",
    "GaussianSplatLoader",
    "DepthSplatLoader",
    "build_loader",
]