"""
Piper TTS 服务实现 - 本地高效文字转语音
"""
from __future__ import annotations

import os
from pathlib import Path
from typing import Generator, Optional, Tuple
import numpy as np
from loguru import logger

from app.services.tts_service import TTSServiceInterface, TTSAudioChunk
from app.config import settings


class PiperTTSService(TTSServiceInterface):
    """Piper TTS 服务实现"""
    
    def __init__(self):
        self._voice = None
        self._initialized = False
        self._model_path: Optional[Path] = None
        self._config_path: Optional[Path] = None
    
    async def initialize(self) -> bool:
        """加载 Piper 模型"""
        try:
            from piper import PiperVoice
            
            # 查找模型文件
            model_dir = Path(settings.TTS_MODEL_DIR)
            voice_name = settings.TTS_VOICE_NAME
            
            # Piper 模型文件命名: zh_CN-huayan-medium.onnx + .json
            onnx_file = model_dir / f"{voice_name}.onnx"
            json_file = model_dir / f"{voice_name}.onnx.json"
            
            if not onnx_file.exists():
                logger.error(f"Piper 模型文件不存在: {onnx_file}")
                logger.info(f"请下载 Piper 中文模型到 {model_dir}")
                logger.info(f"下载命令: python -m piper.download_voice zh_CN-huayan-medium")
                return False
            
            self._model_path = onnx_file
            self._config_path = json_file
            
            # 加载模型
            logger.info(f"正在加载 Piper 模型: {voice_name}")
            self._voice = PiperVoice.load(str(onnx_file))
            
            logger.info(
                f"Piper TTS 初始化成功: {voice_name}, "
                f"采样率={settings.TTS_SAMPLE_RATE}Hz"
            )
            self._initialized = True
            return True
            
        except ImportError:
            logger.error("piper-tts 未安装，请运行: pip install piper-tts")
            return False
        except Exception as e:
            logger.error(f"Piper TTS 初始化失败: {e}")
            return False
    
    def synthesize(
        self,
        text: str,
        sample_rate: int = 24000,
    ) -> Generator[np.ndarray, None, None]:
        """
        流式合成语音
        
        Args:
            text: 要合成的文本
            sample_rate: 目标采样率
            
        Yields:
            音频块 (numpy array, int16)
        """
        if not self._initialized or self._voice is None:
            raise RuntimeError("TTS 服务未初始化")
        
        try:
            # 勿 list() 化全句：保持生成器迭代以便尽快 yield 首块
            for chunk_data in self._voice.synthesize(text):
                yield chunk_data
                
        except Exception as e:
            logger.error(f"TTS 合成失败: text='{text[:50]}...', 错误={e}")
            raise
    
    def synthesize_complete(
        self,
        text: str,
        sample_rate: int = 24000,
    ) -> Tuple[np.ndarray, int]:
        """
        完整合成语音（一次性返回全部音频）
        
        Args:
            text: 要合成的文本
            sample_rate: 目标采样率
            
        Returns:
            (音频数据, 采样率)
        """
        if not self._initialized or self._voice is None:
            raise RuntimeError("TTS 服务未初始化")
        
        try:
            # 合成完整音频
            audio_parts = []
            for chunk_data in self._voice.synthesize(text):
                audio_parts.append(chunk_data)
            
            # 拼接所有块
            if audio_parts:
                full_audio = np.concatenate(audio_parts)
                return full_audio, sample_rate
            else:
                return np.array([], dtype=np.int16), sample_rate
                
        except Exception as e:
            logger.error(f"TTS 完整合成失败: text='{text[:50]}...', 错误={e}")
            raise
    
    async def shutdown(self):
        """关闭服务"""
        self._voice = None
        self._initialized = False
        logger.info("Piper TTS 服务已关闭")