import os
import traceback
import ffmpeg
import numpy as np
import gradio as gr
from tools.i18n.i18n import I18nAuto
import pandas as pd

i18n = I18nAuto(language=os.environ.get("language", "Auto"))


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 = clean_path(file)  # 防止小白拷路径头尾带了空格和"和回车
        if os.path.exists(file) == False:
            raise RuntimeError("You input a wrong audio path that does not exists, please fix it!")
        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:
        traceback.print_exc()
        raise RuntimeError(i18n("音频加载失败"))

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


def clean_path(path_str: str):
    if path_str.endswith(("\\", "/")):
        return clean_path(path_str[0:-1])
    path_str = path_str.replace("/", os.sep).replace("\\", os.sep)
    return path_str.strip(
        " '\n\"\u202a"
    )  # path_str.strip(" ").strip('\'').strip("\n").strip('"').strip(" ").strip("\u202a")


def check_for_existance(file_list: list = None, is_train=False, is_dataset_processing=False):
    files_status = []
    if is_train == True and file_list:
        file_list.append(os.path.join(file_list[0], "2-name2text.txt"))
        file_list.append(os.path.join(file_list[0], "3-bert"))
        file_list.append(os.path.join(file_list[0], "4-cnhubert"))
        file_list.append(os.path.join(file_list[0], "5-wav32k"))
        file_list.append(os.path.join(file_list[0], "6-name2semantic.tsv"))
    for file in file_list:
        if os.path.exists(file):
            files_status.append(True)
        else:
            files_status.append(False)
    if sum(files_status) != len(files_status):
        if is_train:
            for file, status in zip(file_list, files_status):
                if status:
                    pass
                else:
                    gr.Warning(file)
            gr.Warning(i18n("以下文件或文件夹不存在"))
            return False
        elif is_dataset_processing:
            if files_status[0]:
                return True
            elif not files_status[0]:
                gr.Warning(file_list[0])
            elif not files_status[1] and file_list[1]:
                gr.Warning(file_list[1])
            gr.Warning(i18n("以下文件或文件夹不存在"))
            return False
        else:
            if file_list[0]:
                gr.Warning(file_list[0])
                gr.Warning(i18n("以下文件或文件夹不存在"))
            else:
                gr.Warning(i18n("路径不能为空"))
            return False
    return True


def check_details(path_list=None, is_train=False, is_dataset_processing=False):
    if is_dataset_processing:
        list_path, audio_path = path_list
        if not list_path.endswith(".list"):
            gr.Warning(i18n("请填入正确的List路径"))
            return
        if audio_path:
            if not os.path.isdir(audio_path):
                gr.Warning(i18n("请填入正确的音频文件夹路径"))
                return
        with open(list_path, "r", encoding="utf8") as f:
            line = f.readline().strip("\n").split("\n")
        wav_name, _, __, ___ = line[0].split("|")
        wav_name = clean_path(wav_name)
        if audio_path != "" and audio_path != None:
            wav_name = os.path.basename(wav_name)
            wav_path = "%s/%s" % (audio_path, wav_name)
        else:
            wav_path = wav_name
        if os.path.exists(wav_path):
            ...
        else:
            gr.Warning(i18n("路径错误"))
        return
    if is_train:
        path_list.append(os.path.join(path_list[0], "2-name2text.txt"))
        path_list.append(os.path.join(path_list[0], "4-cnhubert"))
        path_list.append(os.path.join(path_list[0], "5-wav32k"))
        path_list.append(os.path.join(path_list[0], "6-name2semantic.tsv"))
        phone_path, hubert_path, wav_path, semantic_path = path_list[1:]
        with open(phone_path, "r", encoding="utf-8") as f:
            if f.read(1):
                ...
            else:
                gr.Warning(i18n("缺少音素数据集"))
        if os.listdir(hubert_path):
            ...
        else:
            gr.Warning(i18n("缺少Hubert数据集"))
        if os.listdir(wav_path):
            ...
        else:
            gr.Warning(i18n("缺少音频数据集"))
        df = pd.read_csv(semantic_path, delimiter="\t", encoding="utf-8")
        if len(df) >= 1:
            ...
        else:
            gr.Warning(i18n("缺少语义数据集"))