# -*- coding: utf-8 -*-
"""Centralized device detection utility.

This module keeps the historic device helpers while delegating hardware
probing to ``app.core.accelerator``.
"""

from app.core.accelerator import get_accelerator_info


def detect_device(configured: str = "auto") -> str:
    """Resolve a device configuration string to a concrete PyTorch device.

    Priority for ``"auto"``: configured accelerator > detected GPU > CPU.

    Args:
        configured: Value from ``settings.DEVICE`` or caller override.
            Accepted: ``"auto"``, ``"cpu"``, ``"cuda:0"``, ``"npu:0"``, etc.

    Returns:
        A device string ready for ``torch.device()`` / FunASR / ModelScope.
    """
    device = configured.strip().lower()

    if device == "auto":
        return get_accelerator_info().device

    # Normalize bare "cuda" to "cuda:0"
    if device == "cuda":
        return "cuda:0"

    if device == "mps":
        return "cpu"

    return device


def is_cuda() -> bool:
    """True when the active runtime exposes a CUDA-compatible device."""
    info = get_accelerator_info()
    return info.available and info.device.startswith("cuda")


def has_gpu() -> bool:
    """True when a supported accelerator is available."""
    return get_accelerator_info().is_gpu


def get_vram_gb() -> float:
    """Return usable accelerator memory in GB."""
    return get_accelerator_info().total_memory_gb