import asyncio import gc import io import threading import traceback import uuid from concurrent.futures import ThreadPoolExecutor import torch import torchaudio from config.logger import setup_logging import os import numpy as np import opuslib_next from pydub import AudioSegment from abc import ABC, abstractmethod from core.utils import textUtils from core.opus import opus_encoder_utils import queue from core.providers.tts.dto.dto import MsgType, TTSMessageDTO, SentenceType TAG = __name__ logger = setup_logging() class TTSProviderBase(ABC): def __init__(self, config, delete_audio_file): self.config = config self.delete_audio_file = delete_audio_file self.output_file = config.get("output_dir") self.tts_text_queue = queue.Queue() self.tts_audio_queue = queue.Queue() self.enable_two_way = False self.stop_event = threading.Event() self.opus_encoder = opus_encoder_utils.OpusEncoderUtils(sample_rate=16000, channels=1, frame_size_ms=60) self.tts_text_buff = [] self.punctuations = ( "。", "？", "！", "；", "：", ".", "?", "!", ";", ":", " ", ",", "，", ) self.tts_request = False self.tts_stop_request = False self.processed_chars = 0 self.stream = False self.last_to_opus_raw = b"" # 启动tts_text_queue监听线程 # 线程任务相关 self.loop = asyncio.get_event_loop() self.process_tasks_loop = asyncio.get_event_loop() self.max_workers = self.config.get("TTS_SET", {}).get("MAX_WORKERS", 3) self.active_tasks = set() # 追踪当前运行的任务 self.executor = ThreadPoolExecutor(max_workers=self.max_workers) async def open_audio_channels(self): # 启动tts_text_queue监听线程 tts_priority = threading.Thread( target=self._tts_text_priority_thread, daemon=True ) tts_priority.start() async def close(self): self.stop_event def _get_segment_text(self): # 合并当前全部文本并处理未分割部分 full_text = "".join(self.tts_text_buff) current_text = full_text[self.processed_chars:] # 从未处理的位置开始 last_punct_pos = -1 for punct in self.punctuations: pos = current_text.rfind(punct) if (pos != -1 and last_punct_pos == -1) or ( pos != -1 and pos < last_punct_pos ): last_punct_pos = pos if last_punct_pos != -1: segment_text_raw = current_text[: last_punct_pos + 1] segment_text = textUtils.get_string_no_punctuation_or_emoji( segment_text_raw ) self.processed_chars += len(segment_text_raw) # 更新已处理字符位置 return segment_text elif self.tts_stop_request and current_text: segment_text = current_text return segment_text else: return None async def process_generator(self, generator): async for tts_data in generator: self.tts_audio_queue.put(tts_data) def _tts_text_priority_thread(self): logger.bind(tag=TAG).info("开始监听tts文本") if self.enable_two_way: self._enable_two_way_tts() else: self._no_enable_two_way_tts() async def start_session(self, session_id): pass async def finish_session(self, session_id): pass def tts_one_sentence(self, conn, text, u_id=None): if not u_id: if conn.u_id: u_id = conn.u_id else: u_id = str(uuid.uuid4()).replace("-", "") conn.u_id = u_id self.tts_text_queue.put( TTSMessageDTO(u_id=u_id, msg_type=MsgType.START_TTS_REQUEST, content="") ) self.tts_text_queue.put( TTSMessageDTO(u_id=u_id, msg_type=MsgType.TTS_TEXT_REQUEST, content=text) ) self.tts_text_queue.put( TTSMessageDTO(u_id=u_id, msg_type=MsgType.STOP_TTS_REQUEST, content="") ) def _enable_two_way_tts(self): while not self.stop_event.is_set(): try: ttsMessageDTO = self.tts_text_queue.get() msg_type = ttsMessageDTO.msg_type if msg_type == MsgType.START_TTS_REQUEST: # 开始传输tts文本 self.tts_request = True self.tts_stop_request = False self.u_id = ttsMessageDTO.u_id # 开启session future = asyncio.run_coroutine_threadsafe( self.start_session(ttsMessageDTO.u_id), loop=self.loop ) future.result() # await self.start_session(ttsMessageDTO.u_id) elif self.tts_request and msg_type == MsgType.TTS_TEXT_REQUEST: future = asyncio.run_coroutine_threadsafe( self.text_to_speak( u_id=ttsMessageDTO.u_id, text=ttsMessageDTO.content ), loop=self.loop, ) future.result() elif msg_type == MsgType.STOP_TTS_REQUEST: self.tts_request = False self.tts_stop_request = True future = asyncio.run_coroutine_threadsafe( self.finish_session(ttsMessageDTO.u_id), loop=self.loop ) future.result() except Exception as e: logger.bind(tag=TAG).error(f"Failed to process TTS text: {e}") # 报错了。要关闭说话 self.tts_audio_queue.put( TTSMessageDTO( u_id=self.u_id, msg_type=MsgType.STOP_TTS_RESPONSE, content=[], tts_finish_text="", sentence_type=None, ) ) traceback.print_exc() def _no_enable_two_way_tts(self): # 为这个线程创建一个新的事件循环 loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) while not self.stop_event.is_set(): try: ttsMessageDTO = self.tts_text_queue.get() msg_type = ttsMessageDTO.msg_type if not self.enable_two_way: if msg_type == MsgType.START_TTS_REQUEST: # 开始传输tts文本 self.tts_request = True self.tts_stop_request = False self.processed_chars = 0 self.tts_text_buff = [] elif self.tts_request and msg_type == MsgType.TTS_TEXT_REQUEST: self.tts_text_buff.append(ttsMessageDTO.content) elif msg_type == MsgType.STOP_TTS_REQUEST: # 结束传输tts文本,处理最尾巴的数据 self.tts_request = False self.tts_stop_request = True segment_text = self._get_segment_text() if segment_text: # 修改部分：创建协程对象 # 修改部分：创建协程对象 tts_generator = self.text_to_speak( ttsMessageDTO.u_id, segment_text, True if msg_type == MsgType.STOP_TTS_REQUEST else False, ( True if msg_type == MsgType.START_TTS_REQUEST else False ), ) future = asyncio.run_coroutine_threadsafe( self.process_generator(tts_generator), self.loop ) self.active_tasks.add(future) if self.active_tasks: async def wrap_future(future): return await asyncio.wrap_future(future) wrapped_tasks = [ wrap_future(task) for task in self.active_tasks ] done, _ = loop.run_until_complete( asyncio.wait(wrapped_tasks) ) self.active_tasks -= done # 发送合成结束 self.tts_audio_queue.put( TTSMessageDTO( u_id=ttsMessageDTO.u_id, msg_type=MsgType.STOP_TTS_RESPONSE, content=[], tts_finish_text="", sentence_type=SentenceType.SENTENCE_END, ) ) segment_text = self._get_segment_text() if segment_text: # 确保这里得到的是协程对象 tts_generator = self.text_to_speak( ttsMessageDTO.u_id, segment_text, msg_type == MsgType.STOP_TTS_REQUEST, msg_type == MsgType.START_TTS_REQUEST, ) # 提交协程到事件循环 tts_generator_future = asyncio.run_coroutine_threadsafe( self.process_generator(tts_generator), loop ) self.active_tasks.add(tts_generator_future) if len(self.active_tasks) >= self.max_workers: # 等待所有任务完成 try: async def wrap_future(future): return await asyncio.wrap_future(future) wrapped_tasks = [ wrap_future(task) for task in self.active_tasks ] done, _ = loop.run_until_complete( asyncio.wait(wrapped_tasks) ) self.active_tasks -= done except Exception as e: logger.bind(tag=TAG).error( f"Failed to process TTS text: {e}" ) traceback.print_exc() else: pass except Exception as e: logger.bind(tag=TAG).error(f"Failed to process TTS text: {e}") traceback.print_exc() @abstractmethod def generate_filename(self): pass @abstractmethod async def text_to_speak(self, u_id, text, is_last_text=False, is_first_text=False): pass async def text_to_speak_stream(self, text, queue: queue.Queue, text_index=0): raise Exception("该TTS还没有实现stream模式") def audio_to_opus_data(self, audio_file_path): """音频文件转换为Opus编码""" # 获取文件后缀名 file_type = os.path.splitext(audio_file_path)[1] if file_type: file_type = file_type.lstrip(".") audio = AudioSegment.from_file(audio_file_path, format=file_type) # 转换为单声道/16kHz采样率/16位小端编码（确保与编码器匹配） audio = audio.set_channels(1).set_frame_rate(16000).set_sample_width(2) # 音频时长(秒) duration = len(audio) / 1000.0 # 获取原始PCM数据（16位小端） raw_data = audio.raw_data # 初始化Opus编码器 encoder = opuslib_next.Encoder(16000, 1, opuslib_next.APPLICATION_AUDIO) # 编码参数 frame_duration = 60 # 60ms per frame frame_size = int(16000 * frame_duration / 1000) # 960 samples/frame opus_datas = [] # 按帧处理所有音频数据（包括最后一帧可能补零） for i in range(0, len(raw_data), frame_size * 2): # 16bit=2bytes/sample # 获取当前帧的二进制数据 chunk = raw_data[i: i + frame_size * 2] # 如果最后一帧不足，补零 if len(chunk) < frame_size * 2: chunk += b"\x00" * (frame_size * 2 - len(chunk)) # 转换为numpy数组处理 np_frame = np.frombuffer(chunk, dtype=np.int16) # 编码Opus数据 opus_data = encoder.encode(np_frame.tobytes(), frame_size) opus_datas.append(opus_data) return opus_datas, duration def get_audio_from_tts(self, data_bytes, src_rate, to_rate=16000): tts_speech = torch.from_numpy( np.array(np.frombuffer(data_bytes, dtype=np.int16)) ).unsqueeze(dim=0) with io.BytesIO() as bf: torchaudio.save(bf, tts_speech, src_rate, format="wav") audio = AudioSegment.from_file(bf, format="wav") audio = audio.set_channels(1).set_frame_rate(to_rate) return audio def wav_to_opus_data_audio_raw(self, raw_data_var, is_end=False): opus_datas = self.opus_encoder.encode_pcm_to_opus(raw_data_var, is_end) return opus_datas