import os

import numpy as np
import ffmpeg
from fairseq import checkpoint_utils


def get_index_path_from_model(sid):
    return next(
        (
            f
            for f in [
                os.path.join(root, name)
                for root, dirs, files in os.walk(os.getenv("index_root"), topdown=False)
                for name in files
                if name.endswith(".index") and "trained" not in name
            ]
            if sid.split(".")[0] in f
        ),
        "",
    )


def load_hubert(config):
    models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
        ["assets/hubert/hubert_base.pt"],
        suffix="",
    )
    hubert_model = models[0]
    hubert_model = hubert_model.to(config.device)
    if config.is_half:
        hubert_model = hubert_model.half()
    else:
        hubert_model = hubert_model.float()
    return hubert_model.eval()


def load_audio(file, sr):
    try:
        # https://github.com/openai/whisper/blob/main/whisper/audio.py#L26
        # This launches a subprocess to decode audio while down-mixing and resampling as necessary.
        # Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
        file = (
            file.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
        )  # 防止小白拷路径头尾带了空格和"和回车
        out, _ = (
            ffmpeg.input(file, threads=0)
            .output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr)
            .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True)
        )
    except Exception as e:
        raise RuntimeError(f"Failed to load audio: {e}")

    return np.frombuffer(out, np.float32).flatten()