import logging
import asyncio
import re
import time
from typing import Optional

import service.pyav as pyav
import torch
from funasr import AutoModel

logger = logging.getLogger(__name__)
asr_model: Optional[AutoModel] = None
is_model_ready = False


def get_asr_model():
    """获取模型实例的接口"""
    global asr_model
    return asr_model


def check_ready():
    """检查模型是否加载完成"""
    global is_model_ready
    return is_model_ready


async def init_funasr():
    """异步初始化函数"""
    global asr_model, is_model_ready

    if is_model_ready:
        return

    logger.info("⏳ [ASR] 开始异步加载 funasr 模型...")
    start_time = time.time()

    try:
        # 使用 run_in_executor 避免阻塞主事件循环
        loop = asyncio.get_event_loop()

        # 定义具体的加载逻辑
        def load():
            return AutoModel(
                model="paraformer-zh",
                vad_model="fsmn-vad",
                vad_kwargs={"max_single_segment_time": 30000},
                punc_model="ct-punc",
                device="cuda:0" if torch.cuda.is_available() else "cpu",
                disable_update=True
            )

        asr_model = await loop.run_in_executor(None, load)
        is_model_ready = True
        logger.info(f"✅ [ASR] 模型加载成功！耗时 {(time.time() - start_time):.2f}s")
    except Exception as e:
        logger.error(f"❌ [ASR] 模型加载失败: {e}")
        is_model_ready = False


def get_text(audio_path):
    start_time = time.time()
    logger.info("⏳ 开始进行音频识别...")
    result = asr_model.generate(input=[audio_path], cache={}, batch_size_s=300)
    logger.info(f"✅ 音频识别完成, 耗时 {(time.time() - start_time):.2f}秒")

    # 清理文本中的空字符
    text = result[0]['text'].replace(" ", "")
    timestamps = result[0]['timestamp']
    return {
        'text': text,
        'timestamps': timestamps
    }


def generate_srt(audio_path, srt_path):
    result = get_text(audio_path)
    text = result['text']
    timestamp_list = result['timestamps']

    # 使用正则表达式将文本按标点切分为一个 list，保留标点
    text_list = re.split(r"([。！？；，])", text)
    srt_list = pyav.get_precise_srt(text_list, timestamp_list)
    pyav.save_srt_file(srt_list, srt_path)