update:流式优化暂不稳定,先回滚到早期代码

This commit is contained in:
hrz
2025-08-30 22:59:21 +08:00
parent b4f4995ff9
commit eaade698fb
19 changed files with 1116 additions and 369 deletions
+4
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@@ -59,6 +59,10 @@ log:
delete_audio: true
# 没有语音输入多久后断开连接(秒),默认2分钟,即120秒
close_connection_no_voice_time: 120
# TTS请求超时时间(秒)
tts_timeout: 10
# 开启唤醒词加速
enable_wakeup_words_response_cache: true
# 开场是否回复唤醒词
enable_greeting: true
# 说完话是否开启提示音
+111 -1
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@@ -1,13 +1,33 @@
import time
import json
import random
import asyncio
from core.utils.dialogue import Message
from core.utils.util import audio_to_data
from core.handle.sendAudioHandle import sendAudioMessage, send_stt_message
from core.utils.util import remove_punctuation_and_length, opus_datas_to_wav_bytes
from core.providers.tts.dto.dto import ContentType, SentenceType
from core.providers.tools.device_mcp import (
MCPClient,
send_mcp_initialize_message,
send_mcp_tools_list_request,
)
from core.utils.wakeup_word import WakeupWordsConfig
TAG = __name__
WAKEUP_CONFIG = {
"refresh_time": 5,
"words": ["你好", "你好啊", "嘿,你好", ""],
}
# 创建全局的唤醒词配置管理器
wakeup_words_config = WakeupWordsConfig()
# 用于防止并发调用wakeupWordsResponse的锁
_wakeup_response_lock = asyncio.Lock()
async def handleHelloMessage(conn, msg_json):
"""处理hello消息"""
audio_params = msg_json.get("audio_params")
@@ -28,4 +48,94 @@ async def handleHelloMessage(conn, msg_json):
# 发送mcp消息,获取tools列表
asyncio.create_task(send_mcp_tools_list_request(conn))
await conn.websocket.send(json.dumps(conn.welcome_msg))
await conn.websocket.send(json.dumps(conn.welcome_msg))
async def checkWakeupWords(conn, text):
enable_wakeup_words_response_cache = conn.config[
"enable_wakeup_words_response_cache"
]
if not enable_wakeup_words_response_cache or not conn.tts:
return False
_, filtered_text = remove_punctuation_and_length(text)
if filtered_text not in conn.config.get("wakeup_words"):
return False
conn.just_woken_up = True
await send_stt_message(conn, text)
# 获取当前音色
voice = getattr(conn.tts, "voice", "default")
if not voice:
voice = "default"
# 获取唤醒词回复配置
response = wakeup_words_config.get_wakeup_response(voice)
if not response or not response.get("file_path"):
response = {
"voice": "default",
"file_path": "config/assets/wakeup_words.wav",
"time": 0,
"text": "哈啰啊,我是小智啦,声音好听的台湾女孩一枚,超开心认识你耶,最近在忙啥,别忘了给我来点有趣的料哦,我超爱听八卦的啦",
}
# 播放唤醒词回复
conn.client_abort = False
opus_packets, _ = audio_to_data(response.get("file_path"))
conn.logger.bind(tag=TAG).info(f"播放唤醒词回复: {response.get('text')}")
await sendAudioMessage(conn, SentenceType.FIRST, opus_packets, response.get("text"))
await sendAudioMessage(conn, SentenceType.LAST, [], None)
# 补充对话
conn.dialogue.put(Message(role="assistant", content=response.get("text")))
# 检查是否需要更新唤醒词回复
if time.time() - response.get("time", 0) > WAKEUP_CONFIG["refresh_time"]:
if not _wakeup_response_lock.locked():
asyncio.create_task(wakeupWordsResponse(conn))
return True
async def wakeupWordsResponse(conn):
if not conn.tts or not conn.llm or not conn.llm.response_no_stream:
return
try:
# 尝试获取锁,如果获取不到就返回
if not await _wakeup_response_lock.acquire():
return
# 生成唤醒词回复
wakeup_word = random.choice(WAKEUP_CONFIG["words"])
question = (
"此刻用户正在和你说```"
+ wakeup_word
+ "```。\n请你根据以上用户的内容进行20-30字回复。要符合系统设置的角色情感和态度,不要像机器人一样说话。\n"
+ "请勿对这条内容本身进行任何解释和回应,请勿返回表情符号,仅返回对用户的内容的回复。"
)
result = conn.llm.response_no_stream(conn.config["prompt"], question)
if not result or len(result) == 0:
return
# 生成TTS音频
tts_result = await asyncio.to_thread(conn.tts.to_tts, result)
if not tts_result:
return
# 获取当前音色
voice = getattr(conn.tts, "voice", "default")
wav_bytes = opus_datas_to_wav_bytes(tts_result, sample_rate=16000)
file_path = wakeup_words_config.generate_file_path(voice)
with open(file_path, "wb") as f:
f.write(wav_bytes)
# 更新配置
wakeup_words_config.update_wakeup_response(voice, file_path, result)
finally:
# 确保在任何情况下都释放锁
if _wakeup_response_lock.locked():
_wakeup_response_lock.release()
@@ -1,11 +1,12 @@
import json
import uuid
import asyncio
from core.utils.dialogue import Message
from core.providers.tts.dto.dto import ContentType
from plugins_func.register import Action, ActionResponse
import uuid
from core.handle.sendAudioHandle import send_stt_message
from core.handle.helloHandle import checkWakeupWords
from core.utils.util import remove_punctuation_and_length
from core.providers.tts.dto.dto import ContentType
from core.utils.dialogue import Message
from plugins_func.register import Action, ActionResponse
from core.providers.tts.dto.dto import TTSMessageDTO, SentenceType
TAG = __name__
@@ -23,9 +24,12 @@ async def handle_user_intent(conn, text):
pass
# 检查是否有明确的退出命令
_, filtered_text = remove_punctuation_and_length(text)
filtered_text = remove_punctuation_and_length(text)[1]
if await check_direct_exit(conn, filtered_text):
return True
# 检查是否是唤醒词
if await checkWakeupWords(conn, filtered_text):
return True
if conn.intent_type == "function_call":
# 使用支持function calling的聊天方法,不再进行意图分析
@@ -1,21 +1,28 @@
import time
import json
from core.handle.abortHandle import handleAbortMessage
from core.handle.sendAudioHandle import send_stt_message
from core.handle.intentHandler import handle_user_intent
from core.utils.output_counter import check_device_output_limit
from core.utils.util import play_audio_frames, play_audio_response
from core.handle.sendAudioHandle import send_stt_message, SentenceType
from core.handle.abortHandle import handleAbortMessage
import time
import asyncio
import json
from core.handle.sendAudioHandle import SentenceType
from core.utils.util import audio_to_data
TAG = __name__
async def handleAudioMessage(conn, audio):
# 检查是否在唤醒处理锁定期内
if getattr(conn, 'wakeup_processing_lock', 0) > time.monotonic():
return
# 当前片段是否有人说话
have_voice = conn.vad.is_vad(conn, audio)
# 如果设备刚刚被唤醒,短暂忽略VAD检测
if have_voice and hasattr(conn, "just_woken_up") and conn.just_woken_up:
have_voice = False
# 设置一个短暂延迟后恢复VAD检测
conn.asr_audio.clear()
if not hasattr(conn, "vad_resume_task") or conn.vad_resume_task.done():
conn.vad_resume_task = asyncio.create_task(resume_vad_detection(conn))
return
if have_voice:
if conn.client_is_speaking:
await handleAbortMessage(conn)
@@ -24,11 +31,18 @@ async def handleAudioMessage(conn, audio):
# 接收音频
await conn.asr.receive_audio(conn, audio, have_voice)
async def resume_vad_detection(conn):
# 等待2秒后恢复VAD检测
await asyncio.sleep(1)
conn.just_woken_up = False
async def startToChat(conn, text):
# 检查输入是否是JSON格式(包含说话人信息)
speaker_name = None
actual_text = text
try:
# 尝试解析JSON格式的输入
if text.strip().startswith('{') and text.strip().endswith('}'):
@@ -37,13 +51,13 @@ async def startToChat(conn, text):
speaker_name = data['speaker']
actual_text = data['content']
conn.logger.bind(tag=TAG).info(f"解析到说话人信息: {speaker_name}")
# 直接使用JSON格式的文本,不解析
actual_text = text
except (json.JSONDecodeError, KeyError):
# 如果解析失败,继续使用原始文本
pass
# 保存说话人信息到连接对象
if speaker_name:
conn.current_speaker = speaker_name
@@ -107,7 +121,8 @@ async def max_out_size(conn):
text = "不好意思,我现在有点事情要忙,明天这个时候我们再聊,约好了哦!明天不见不散,拜拜!"
await send_stt_message(conn, text)
file_path = "config/assets/max_output_size.wav"
play_audio_response(conn, {"text": text, "file_path": file_path})
opus_packets, _ = audio_to_data(file_path)
conn.tts.tts_audio_queue.put((SentenceType.LAST, opus_packets, text))
conn.close_after_chat = True
@@ -125,15 +140,16 @@ async def check_bind_device(conn):
# 播放提示音
music_path = "config/assets/bind_code.wav"
conn.tts.tts_audio_queue.put((SentenceType.FIRST, [], text))
play_audio_frames(conn, music_path)
opus_packets, _ = audio_to_data(music_path)
conn.tts.tts_audio_queue.put((SentenceType.FIRST, opus_packets, text))
# 逐个播放数字
for i in range(6): # 确保只播放6位数字
try:
digit = conn.bind_code[i]
num_path = f"config/assets/bind_code/{digit}.wav"
play_audio_frames(conn, num_path)
num_packets, _ = audio_to_data(num_path)
conn.tts.tts_audio_queue.put((SentenceType.MIDDLE, num_packets, None))
except Exception as e:
conn.logger.bind(tag=TAG).error(f"播放数字音频失败: {e}")
continue
@@ -142,4 +158,5 @@ async def check_bind_device(conn):
text = f"没有找到该设备的版本信息,请正确配置 OTA地址,然后重新编译固件。"
await send_stt_message(conn, text)
music_path = "config/assets/bind_not_found.wav"
play_audio_response(conn, {"text": text, "file_path": music_path})
opus_packets, _ = audio_to_data(music_path)
conn.tts.tts_audio_queue.put((SentenceType.LAST, opus_packets, text))
@@ -1,25 +1,25 @@
import json
import time
import asyncio
from core.utils import textUtils
import time
from core.providers.tts.dto.dto import SentenceType
from core.utils import textUtils
TAG = __name__
async def sendAudioMessage(conn, sentenceType, audios, text):
# 发送句子开始消息
conn.logger.bind(tag=TAG).info(f"发送音频消息: {sentenceType}, {text}")
pre_buffer = False
if conn.tts.tts_audio_first_sentence:
conn.logger.bind(tag=TAG).info(f"发送第一段语音: {text}")
conn.tts.tts_audio_first_sentence = False
await send_tts_message(conn, "start", None)
pre_buffer = True
if sentenceType == SentenceType.FIRST:
await send_tts_message(conn, "sentence_start", text)
await send_tts_message(conn, "sentence_start", text)
await sendAudio(conn, audios)
# 发送句子开始消息
if sentenceType is not SentenceType.MIDDLE:
conn.logger.bind(tag=TAG).info(f"发送音频消息: {sentenceType}, {text}")
await sendAudio(conn, audios, pre_buffer)
# 发送结束消息(如果是最后一个文本)
if conn.llm_finish_task and sentenceType == SentenceType.LAST:
@@ -30,59 +30,45 @@ async def sendAudioMessage(conn, sentenceType, audios, text):
# 播放音频
async def sendAudio(conn, audios, pre_buffer=False):
"""
发送单个opus包,支持流控
Args:
conn: 连接对象
opus_packet: 单个opus数据包
pre_buffer: 快速发送音频
"""
async def sendAudio(conn, audios, pre_buffer=True):
if audios is None or len(audios) == 0:
return
# 流控参数优化
frame_duration = 60 # 帧时长(毫秒),匹配 Opus 编码
start_time = time.perf_counter()
play_position = 0
if isinstance(audios, bytes):
# 仅当第一句话时执行预缓冲
if pre_buffer:
pre_buffer_frames = min(3, len(audios))
for i in range(pre_buffer_frames):
await conn.websocket.send(audios[i])
remaining_audios = audios[pre_buffer_frames:]
else:
remaining_audios = audios
# 播放剩余音频帧
for opus_packet in remaining_audios:
if conn.client_abort:
return
# 短音频直接发送(例如:提示音)
if pre_buffer:
await conn.websocket.send(audios)
return
break
# 重置没有声音的状态
conn.last_activity_time = time.time() * 1000
# 获取或初始化流控状态
if not hasattr(conn, "audio_flow_control"):
conn.audio_flow_control = {
"last_send_time": 0,
"packet_count": 0,
"start_time": time.perf_counter(),
}
frame_duration=60
flow_control = conn.audio_flow_control
current_time = time.perf_counter()
# 计算预期发送时间
expected_time = flow_control["start_time"] + (
flow_control["packet_count"] * frame_duration / 1000
)
expected_time = start_time + (play_position / 1000)
current_time = time.perf_counter()
delay = expected_time - current_time
if delay > 0:
await asyncio.sleep(delay)
# 发送数据包
await conn.websocket.send(audios)
await conn.websocket.send(opus_packet)
# 更新流控状态
flow_control["packet_count"] += 1
flow_control["last_send_time"] = time.perf_counter()
play_position += frame_duration
async def send_tts_message(conn, state, text=None):
"""发送 TTS 状态消息"""
if text is None and state == "sentence_start":
return
message = {"type": "tts", "state": state, "session_id": conn.session_id}
if text is not None:
message["text"] = textUtils.check_emoji(text)
@@ -95,12 +81,8 @@ async def send_tts_message(conn, state, text=None):
stop_tts_notify_voice = conn.config.get(
"stop_tts_notify_voice", "config/assets/tts_notify.mp3"
)
conn.tts.audio_to_opus_data_stream(
stop_tts_notify_voice,
callback=lambda audio_data: asyncio.run_coroutine_threadsafe(
sendAudio(conn, audio_data, True), conn.loop
),
)
audios, _ = conn.tts.audio_to_opus_data(stop_tts_notify_voice)
await sendAudio(conn, audios)
# 清除服务端讲话状态
conn.clearSpeakStatus()
@@ -109,17 +91,18 @@ async def send_tts_message(conn, state, text=None):
async def send_stt_message(conn, text):
"""发送 STT 状态消息"""
end_prompt_str = conn.config.get("end_prompt", {}).get("prompt")
if end_prompt_str and end_prompt_str == text:
await send_tts_message(conn, "start")
return
"""发送 STT 状态消息"""
# 解析JSON格式,提取实际的用户说话内容
display_text = text
try:
# 尝试解析JSON格式
if text.strip().startswith("{") and text.strip().endswith("}"):
if text.strip().startswith('{') and text.strip().endswith('}'):
parsed_data = json.loads(text)
if isinstance(parsed_data, dict) and "content" in parsed_data:
# 如果是包含说话人信息的JSON格式,只显示content部分
+21 -8
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@@ -1,12 +1,14 @@
import json
import asyncio
from core.utils.util import filter_sensitive_info
import time
from core.handle.abortHandle import handleAbortMessage
from core.handle.helloHandle import handleHelloMessage
from core.handle.receiveAudioHandle import handleAudioMessage
from core.providers.tools.device_mcp import handle_mcp_message
from core.utils.util import remove_punctuation_and_length, filter_sensitive_info
from core.handle.receiveAudioHandle import startToChat, handleAudioMessage
from core.handle.sendAudioHandle import send_stt_message, send_tts_message
from core.providers.tools.device_iot import handleIotDescriptors, handleIotStatus
from core.handle.reportHandle import enqueue_asr_report
import asyncio
TAG = __name__
@@ -44,9 +46,14 @@ async def handleTextMessage(conn, message):
conn.client_have_voice = False
conn.asr_audio.clear()
if "text" in msg_json:
original_text = msg_json["text"] # 保留设备上传的文本
conn.last_activity_time = time.time() * 1000
original_text = msg_json["text"] # 保留原始文本
filtered_len, filtered_text = remove_punctuation_and_length(
original_text
)
# 识别是否是唤醒词
is_wakeup_words = original_text in conn.config.get("wakeup_words")
is_wakeup_words = filtered_text in conn.config.get("wakeup_words")
# 是否开启唤醒词回复
enable_greeting = conn.config.get("enable_greeting", True)
@@ -55,10 +62,16 @@ async def handleTextMessage(conn, message):
await send_stt_message(conn, original_text)
await send_tts_message(conn, "stop", None)
conn.client_is_speaking = False
elif is_wakeup_words:
conn.just_woken_up = True
# 上报纯文字数据(复用ASR上报功能,但不提供音频数据)
enqueue_asr_report(conn, "嘿,你好呀", [])
await startToChat(conn, "嘿,你好呀")
else:
# 检测到唤醒词,开始等待后续进行声纹识别
conn.wakeup_mode = True
conn.logger.bind(tag=TAG).info(f"检测到唤醒词~")
# 上报纯文字数据(复用ASR上报功能,但不提供音频数据)
enqueue_asr_report(conn, original_text, [])
# 否则需要LLM对文字内容进行答复
await startToChat(conn, original_text)
elif msg_json["type"] == "iot":
conn.logger.bind(tag=TAG).info(f"收到iot消息:{message}")
if "descriptors" in msg_json:
+63 -89
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@@ -1,18 +1,18 @@
import os
import io
import wave
import uuid
import json
import time
import queue
import asyncio
import traceback
import threading
import opuslib_next
import json
import io
import time
import concurrent.futures
from abc import ABC, abstractmethod
from config.logger import setup_logging
from typing import Optional, Tuple, List
from typing import Optional, Tuple, List, Dict, Any
from core.handle.receiveAudioHandle import startToChat
from core.handle.reportHandle import enqueue_asr_report
from core.utils.util import remove_punctuation_and_length
@@ -53,10 +53,6 @@ class ASRProviderBase(ABC):
# 接收音频
async def receive_audio(self, conn, audio, audio_have_voice):
# 检查是否在唤醒处理锁定期内
if getattr(conn, 'wakeup_processing_lock', 0) > time.monotonic():
return
if conn.client_listen_mode == "auto" or conn.client_listen_mode == "realtime":
have_voice = audio_have_voice
else:
@@ -66,14 +62,6 @@ class ASRProviderBase(ABC):
if not have_voice and not conn.client_have_voice:
conn.asr_audio = conn.asr_audio[-10:]
return
# 检查是否处于唤醒模式
if getattr(conn, 'wakeup_mode', False) and len(conn.asr_audio) >= 10:
asr_audio_task = conn.asr_audio.copy()
conn.reset_vad_states()
conn.asr_audio.clear()
await self.handle_voice_stop(conn, asr_audio_task)
if conn.client_voice_stop:
asr_audio_task = conn.asr_audio.copy()
@@ -99,13 +87,32 @@ class ASRProviderBase(ABC):
# 预先准备WAV数据
wav_data = None
# 使用连接的声纹识别提供者
if conn.voiceprint_provider and combined_pcm_data:
wav_data = self._pcm_to_wav(combined_pcm_data)
# 检查是否处于唤醒模式
wakeup_mode = getattr(conn, 'wakeup_mode', False)
# 声纹识别任务(公共逻辑)
# 定义ASR任务
def run_asr():
start_time = time.monotonic()
try:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
try:
result = loop.run_until_complete(
self.speech_to_text(asr_audio_task, conn.session_id, conn.audio_format)
)
end_time = time.monotonic()
logger.bind(tag=TAG).info(f"ASR耗时: {end_time - start_time:.3f}s")
return result
finally:
loop.close()
except Exception as e:
end_time = time.monotonic()
logger.bind(tag=TAG).error(f"ASR失败: {e}")
return ("", None)
# 定义声纹识别任务
def run_voiceprint():
if not wav_data:
return None
@@ -124,83 +131,50 @@ class ASRProviderBase(ABC):
logger.bind(tag=TAG).error(f"声纹识别失败: {e}")
return None
if wakeup_mode and conn.voiceprint_provider and wav_data:
conn.wakeup_mode = False
# 设置处理锁,防止后续音频片段重复处理
conn.wakeup_processing_lock = time.monotonic() + 3 # 3秒锁定期
# 使用线程池执行器并行运行
parallel_start_time = time.monotonic()
with concurrent.futures.ThreadPoolExecutor(max_workers=2) as thread_executor:
asr_future = thread_executor.submit(run_asr)
# 唤醒模式:只执行声纹识别
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as thread_executor:
if conn.voiceprint_provider and wav_data:
voiceprint_future = thread_executor.submit(run_voiceprint)
# 等待两个线程都完成
asr_result = asr_future.result(timeout=15)
voiceprint_result = voiceprint_future.result(timeout=15)
speaker_name = voiceprint_result
results = {"asr": asr_result, "voiceprint": voiceprint_result}
else:
asr_result = asr_future.result(timeout=15)
results = {"asr": asr_result, "voiceprint": None}
# 处理结果
raw_text, file_path = results.get("asr", ("", None))
speaker_name = results.get("voiceprint", None)
# 记录识别结果
if raw_text:
logger.bind(tag=TAG).info(f"识别文本: {raw_text}")
if speaker_name:
logger.bind(tag=TAG).info(f"识别说话人: {speaker_name}")
fixed_text = "嘿,你好啊"
enhanced_text = self._build_enhanced_text(fixed_text, speaker_name)
# 性能监控
total_time = time.monotonic() - total_start_time
logger.bind(tag=TAG).info(f"总处理耗时: {total_time:.3f}s")
# 检查文本长度
text_len, _ = remove_punctuation_and_length(raw_text)
self.stop_ws_connection()
if text_len > 0:
# 构建包含说话人信息的JSON字符串
enhanced_text = self._build_enhanced_text(raw_text, speaker_name)
# 性能监控
total_time = time.monotonic() - total_start_time
logger.bind(tag=TAG).info(f"唤醒模式总处理耗时: {total_time:.3f}s")
# 使用自定义模块进行上报
await startToChat(conn, enhanced_text)
enqueue_asr_report(conn, enhanced_text, asr_audio_task)
else:
# 正常模式:执行声纹识别和ASR
def run_asr():
start_time = time.monotonic()
try:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
try:
result = loop.run_until_complete(
self.speech_to_text(asr_audio_task, conn.session_id, conn.audio_format)
)
end_time = time.monotonic()
logger.bind(tag=TAG).info(f"ASR耗时: {end_time - start_time:.3f}s")
return result
finally:
loop.close()
except Exception as e:
end_time = time.monotonic()
logger.bind(tag=TAG).error(f"ASR失败: {e}")
return ("", None)
# 使用线程池执行器并行运行
with concurrent.futures.ThreadPoolExecutor(max_workers=2) as thread_executor:
asr_future = thread_executor.submit(run_asr)
if conn.voiceprint_provider and wav_data:
voiceprint_future = thread_executor.submit(run_voiceprint)
asr_result = asr_future.result(timeout=15)
voiceprint_result = voiceprint_future.result(timeout=15)
results = {"asr": asr_result, "voiceprint": voiceprint_result}
else:
asr_result = asr_future.result(timeout=15)
results = {"asr": asr_result, "voiceprint": None}
# 处理结果
raw_text, _ = results.get("asr", ("", None))
speaker_name = results.get("voiceprint", None)
if raw_text:
logger.bind(tag=TAG).info(f"识别文本: {raw_text}")
if speaker_name:
logger.bind(tag=TAG).info(f"识别说话人: {speaker_name}")
# 性能监控
total_time = time.monotonic() - total_start_time
logger.bind(tag=TAG).info(f"总处理耗时: {total_time:.3f}s")
# 检查文本长度
text_len, _ = remove_punctuation_and_length(raw_text)
self.stop_ws_connection()
if text_len > 0:
enhanced_text = self._build_enhanced_text(raw_text, speaker_name)
await startToChat(conn, enhanced_text)
enqueue_asr_report(conn, enhanced_text, asr_audio_task)
except Exception as e:
logger.bind(tag=TAG).error(f"处理语音停止失败: {e}")
@@ -268,7 +268,11 @@ class TTSProvider(TTSProviderBase):
)
if message.content_file and os.path.exists(message.content_file):
# 先处理文件音频数据
self._process_audio_file_stream(message.content_file, callback=lambda audio_data: self.handle_audio_file(audio_data, message.content_detail))
file_audio = self._process_audio_file(message.content_file)
self.before_stop_play_files.append(
(file_audio, message.content_detail)
)
if message.sentence_type == SentenceType.LAST:
try:
logger.bind(tag=TAG).info("开始结束TTS会话...")
@@ -418,6 +422,9 @@ class TTSProvider(TTSProviderBase):
async def _start_monitor_tts_response(self):
"""监听TTS响应"""
opus_datas_cache = []
is_first_sentence = True
first_sentence_segment_count = 0 # 添加计数器
try:
session_finished = False # 标记会话是否正常结束
while not self.conn.stop_event.is_set():
@@ -438,16 +445,28 @@ class TTSProvider(TTSProviderBase):
self.tts_audio_queue.put(
(SentenceType.FIRST, [], None)
)
elif event_name == "SentenceBegin":
opus_datas_cache = []
elif event_name == "SentenceEnd":
# 发送缓存的数据
if self.conn.tts_MessageText:
logger.bind(tag=TAG).info(
f"句子语音生成成功: {self.conn.tts_MessageText}"
)
self.tts_audio_queue.put(
(SentenceType.FIRST, [], self.conn.tts_MessageText)
)
self.conn.tts_MessageText = None
if (
not is_first_sentence
or first_sentence_segment_count > 10
):
# 发送缓存的数据
if self.conn.tts_MessageText:
logger.bind(tag=TAG).info(
f"句子语音生成成功: {self.conn.tts_MessageText}"
)
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, self.conn.tts_MessageText)
)
self.conn.tts_MessageText = None
else:
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, None)
)
# 第一句话结束后,将标志设置为False
is_first_sentence = False
elif event_name == "SynthesisCompleted":
logger.bind(tag=TAG).debug(f"会话结束~~")
self._process_before_stop_play_files()
@@ -458,7 +477,22 @@ class TTSProvider(TTSProviderBase):
# 二进制消息(音频数据)
elif isinstance(msg, (bytes, bytearray)):
logger.bind(tag=TAG).debug(f"推送数据到队列里面~~")
self.opus_encoder.encode_pcm_to_opus_stream(msg, False, self.handle_opus)
opus_datas = self.opus_encoder.encode_pcm_to_opus(msg, False)
logger.bind(tag=TAG).debug(
f"推送数据到队列里面帧数~~{len(opus_datas)}"
)
if is_first_sentence:
first_sentence_segment_count += 1
if first_sentence_segment_count <= 6:
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas, None)
)
else:
opus_datas_cache.extend(opus_datas)
else:
# 后续句子缓存
opus_datas_cache.extend(opus_datas)
except websockets.ConnectionClosed:
logger.bind(tag=TAG).warning("WebSocket连接已关闭")
break
@@ -478,3 +512,142 @@ class TTSProvider(TTSProviderBase):
finally:
self._monitor_task = None
def to_tts(self, text: str) -> list:
"""非流式TTS处理,用于测试及保存音频文件的场景"""
try:
# 创建新的事件循环
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
# 生成会话ID
session_id = uuid.uuid4().hex
# 存储音频数据
audio_data = []
async def _generate_audio():
# 刷新Token(如果需要)
if self._is_token_expired():
self._refresh_token()
# 建立WebSocket连接
ws = await websockets.connect(
self.ws_url,
additional_headers={"X-NLS-Token": self.token},
ping_interval=30,
ping_timeout=10,
close_timeout=10,
)
try:
# 发送StartSynthesis请求
start_message_id = str(uuid.uuid4().hex)
start_request = {
"header": {
"message_id": start_message_id,
"task_id": session_id,
"namespace": "FlowingSpeechSynthesizer",
"name": "StartSynthesis",
"appkey": self.appkey,
},
"payload": {
"voice": self.voice,
"format": self.format,
"sample_rate": self.sample_rate,
"volume": self.volume,
"speech_rate": self.speech_rate,
"pitch_rate": self.pitch_rate,
"enable_subtitle": True,
},
}
await ws.send(json.dumps(start_request))
# 等待SynthesisStarted响应
synthesis_started = False
while not synthesis_started:
msg = await ws.recv()
if isinstance(msg, str):
data = json.loads(msg)
header = data.get("header", {})
if header.get("name") == "SynthesisStarted":
synthesis_started = True
logger.bind(tag=TAG).debug("TTS合成已启动")
elif header.get("name") == "TaskFailed":
error_info = data.get("payload", {}).get(
"error_info", {}
)
error_code = error_info.get("error_code")
error_message = error_info.get(
"error_message", "未知错误"
)
raise Exception(
f"启动合成失败: {error_code} - {error_message}"
)
# 发送文本合成请求
filtered_text = MarkdownCleaner.clean_markdown(text)
run_message_id = str(uuid.uuid4().hex)
run_request = {
"header": {
"message_id": run_message_id,
"task_id": session_id,
"namespace": "FlowingSpeechSynthesizer",
"name": "RunSynthesis",
"appkey": self.appkey,
},
"payload": {"text": filtered_text},
}
await ws.send(json.dumps(run_request))
# 发送停止合成请求
stop_message_id = str(uuid.uuid4().hex)
stop_request = {
"header": {
"message_id": stop_message_id,
"task_id": session_id,
"namespace": "FlowingSpeechSynthesizer",
"name": "StopSynthesis",
"appkey": self.appkey,
}
}
await ws.send(json.dumps(stop_request))
# 接收音频数据
synthesis_completed = False
while not synthesis_completed:
msg = await ws.recv()
if isinstance(msg, (bytes, bytearray)):
# 编码为Opus并收集
opus_frames = self.opus_encoder.encode_pcm_to_opus(
msg, False
)
audio_data.extend(opus_frames)
elif isinstance(msg, str):
data = json.loads(msg)
header = data.get("header", {})
event_name = header.get("name")
if event_name == "SynthesisCompleted":
synthesis_completed = True
logger.bind(tag=TAG).debug("TTS合成完成")
elif event_name == "TaskFailed":
error_info = data.get("payload", {}).get(
"error_info", {}
)
error_code = error_info.get("error_code")
error_message = error_info.get(
"error_message", "未知错误"
)
raise Exception(
f"合成失败: {error_code} - {error_message}"
)
finally:
try:
await ws.close()
except:
pass
loop.run_until_complete(_generate_audio())
loop.close()
return audio_data
except Exception as e:
logger.bind(tag=TAG).error(f"生成音频数据失败: {str(e)}")
return []
+61 -79
View File
@@ -4,14 +4,12 @@ import queue
import uuid
import asyncio
import threading
from typing import Callable, Any
from core.utils import p3
import time
from datetime import datetime
from core.utils import textUtils
from abc import ABC, abstractmethod
from config.logger import setup_logging
from core.utils.util import audio_bytes_to_data_stream, audio_to_data_stream
from core.utils.util import audio_to_data, audio_bytes_to_data
from core.utils.tts import MarkdownCleaner
from core.utils.output_counter import add_device_output
from core.handle.reportHandle import enqueue_tts_report
@@ -33,6 +31,7 @@ class TTSProviderBase(ABC):
def __init__(self, config, delete_audio_file):
self.interface_type = InterfaceType.NON_STREAM
self.conn = None
self.tts_timeout = 10
self.delete_audio_file = delete_audio_file
self.audio_file_type = "wav"
self.output_file = config.get("output_dir", "tmp/")
@@ -51,9 +50,11 @@ class TTSProviderBase(ABC):
"",
";",
"",
"~",
)
self.first_sentence_punctuations = (
"",
"",
"~",
"",
",",
@@ -76,14 +77,7 @@ class TTSProviderBase(ABC):
f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}",
)
def handle_opus(self, opus_data: bytes):
logger.bind(tag=TAG).debug(f"推送数据到队列里面帧数~~ {len(opus_data)}")
self.tts_audio_queue.put((SentenceType.MIDDLE, opus_data, None))
def handle_audio_file(self, file_audio: bytes, text):
self.before_stop_play_files.append((file_audio, text))
def to_tts_stream(self, text, opus_handler: Callable[[bytes], None] = None) -> None:
def to_tts(self, text):
text = MarkdownCleaner.clean_markdown(text)
max_repeat_time = 5
if self.delete_audio_file:
@@ -92,14 +86,10 @@ class TTSProviderBase(ABC):
try:
audio_bytes = asyncio.run(self.text_to_speak(text, None))
if audio_bytes:
self.tts_audio_queue.put((SentenceType.FIRST, None, text))
audio_bytes_to_data_stream(
audio_bytes,
file_type=self.audio_file_type,
is_opus=True,
callback=opus_handler,
audio_datas, _ = audio_bytes_to_data(
audio_bytes, file_type=self.audio_file_type, is_opus=True
)
break
return audio_datas
else:
max_repeat_time -= 1
except Exception as e:
@@ -139,8 +129,8 @@ class TTSProviderBase(ABC):
logger.bind(tag=TAG).error(
f"语音生成失败: {text},请检查网络或服务是否正常"
)
self.tts_audio_queue.put((SentenceType.FIRST, None, text))
self._process_audio_file_stream(tmp_file, callback=opus_handler)
return tmp_file
except Exception as e:
logger.bind(tag=TAG).error(f"Failed to generate TTS file: {e}")
return None
@@ -149,17 +139,13 @@ class TTSProviderBase(ABC):
async def text_to_speak(self, text, output_file):
pass
def audio_to_pcm_data_stream(
self, audio_file_path, callback: Callable[[Any], Any] = None
):
def audio_to_pcm_data(self, audio_file_path):
"""音频文件转换为PCM编码"""
return audio_to_data_stream(audio_file_path, is_opus=False, callback=callback)
return audio_to_data(audio_file_path, is_opus=False)
def audio_to_opus_data_stream(
self, audio_file_path, callback: Callable[[Any], Any] = None
):
def audio_to_opus_data(self, audio_file_path):
"""音频文件转换为Opus编码"""
return audio_to_data_stream(audio_file_path, is_opus=True, callback=callback)
return audio_to_data(audio_file_path, is_opus=True)
def tts_one_sentence(
self,
@@ -191,6 +177,7 @@ class TTSProviderBase(ABC):
async def open_audio_channels(self, conn):
self.conn = conn
self.tts_timeout = conn.config.get("tts_timeout", 10)
# tts 消化线程
self.tts_priority_thread = threading.Thread(
target=self.tts_text_priority_thread, daemon=True
@@ -225,16 +212,30 @@ class TTSProviderBase(ABC):
self.tts_text_buff.append(message.content_detail)
segment_text = self._get_segment_text()
if segment_text:
self.to_tts_stream(segment_text, opus_handler=self.handle_opus)
if self.delete_audio_file:
audio_datas = self.to_tts(segment_text)
if audio_datas:
self.tts_audio_queue.put(
(message.sentence_type, audio_datas, segment_text)
)
else:
tts_file = self.to_tts(segment_text)
if tts_file:
audio_datas = self._process_audio_file(tts_file)
self.tts_audio_queue.put(
(message.sentence_type, audio_datas, segment_text)
)
elif ContentType.FILE == message.content_type:
self._process_remaining_text_stream(opus_handler=self.handle_opus)
self._process_remaining_text()
tts_file = message.content_file
if tts_file and os.path.exists(tts_file):
self._process_audio_file_stream(
tts_file, callback=self.handle_opus
audio_datas = self._process_audio_file(tts_file)
self.tts_audio_queue.put(
(message.sentence_type, audio_datas, message.content_detail)
)
if message.sentence_type == SentenceType.LAST:
self._process_remaining_text_stream(opus_handler=self.handle_opus)
self._process_remaining_text()
self.tts_audio_queue.put(
(message.sentence_type, [], message.content_detail)
)
@@ -248,59 +249,29 @@ class TTSProviderBase(ABC):
continue
def _audio_play_priority_thread(self):
# 需要上报的文本和音频列表
enqueue_text = None
enqueue_audio = None
while not self.conn.stop_event.is_set():
text = None
try:
try:
sentence_type, audio_datas, text = self.tts_audio_queue.get(
timeout=0.1
timeout=1
)
except queue.Empty:
if self.conn.stop_event.is_set():
break
continue
if self.conn.client_abort:
logger.bind(tag=TAG).debug("收到打断信号,跳过当前音频数据")
enqueue_text, enqueue_audio = None, []
continue
# 收到下一个文本开始或会话结束时进行上报
if sentence_type is not SentenceType.MIDDLE:
# 重置音频流控状态(新句子开始或者结束)
if hasattr(self.conn, 'audio_flow_control'):
self.conn.audio_flow_control = {
'last_send_time': 0,
'packet_count': 0,
'start_time': time.perf_counter()
}
# 上报TTS数据
if enqueue_text is not None and enqueue_audio is not None:
enqueue_tts_report(self.conn, enqueue_text, enqueue_audio)
enqueue_audio = []
enqueue_text = text
# 收集上报音频数据
if isinstance(audio_datas, bytes) and enqueue_audio is not None:
enqueue_audio.append(audio_datas)
# 发送音频
future = asyncio.run_coroutine_threadsafe(
sendAudioMessage(self.conn, sentence_type, audio_datas, text),
self.conn.loop,
)
future.result()
# 记录输出和报告
if self.conn.max_output_size > 0 and text:
add_device_output(self.conn.headers.get("device-id"), len(text))
enqueue_tts_report(self.conn, text, audio_datas)
except Exception as e:
logger.bind(tag=TAG).error(f"audio_play_priority_thread: {text} {e}")
logger.bind(tag=TAG).error(
f"audio_play_priority priority_thread: {text} {e}"
)
async def start_session(self, session_id):
pass
@@ -352,21 +323,22 @@ class TTSProviderBase(ABC):
else:
return None
def _process_audio_file_stream(
self, tts_file, callback: Callable[[Any], Any]
) -> None:
def _process_audio_file(self, tts_file):
"""处理音频文件并转换为指定格式
Args:
tts_file: 音频文件路径
callback: 文件处理函数
content_detail: 内容详情
Returns:
tuple: (sentence_type, audio_datas, content_detail)
"""
if tts_file.endswith(".p3"):
p3.decode_opus_from_file_stream(tts_file, callback=callback)
audio_datas, _ = p3.decode_opus_from_file(tts_file)
elif self.conn.audio_format == "pcm":
self.audio_to_pcm_data_stream(tts_file, callback=callback)
audio_datas, _ = self.audio_to_pcm_data(tts_file)
else:
self.audio_to_opus_data_stream(tts_file, callback=callback)
audio_datas, _ = self.audio_to_opus_data(tts_file)
if (
self.delete_audio_file
@@ -375,6 +347,7 @@ class TTSProviderBase(ABC):
and tts_file.startswith(self.output_file)
):
os.remove(tts_file)
return audio_datas
def _process_before_stop_play_files(self):
for audio_datas, text in self.before_stop_play_files:
@@ -382,9 +355,7 @@ class TTSProviderBase(ABC):
self.before_stop_play_files.clear()
self.tts_audio_queue.put((SentenceType.LAST, [], None))
def _process_remaining_text_stream(
self, opus_handler: Callable[[bytes], None] = None
):
def _process_remaining_text(self):
"""处理剩余的文本并生成语音
Returns:
@@ -395,7 +366,18 @@ class TTSProviderBase(ABC):
if remaining_text:
segment_text = textUtils.get_string_no_punctuation_or_emoji(remaining_text)
if segment_text:
self.to_tts_stream(segment_text, opus_handler=opus_handler)
if self.delete_audio_file:
audio_datas = self.to_tts(segment_text)
if audio_datas:
self.tts_audio_queue.put(
(SentenceType.MIDDLE, audio_datas, segment_text)
)
else:
tts_file = self.to_tts(segment_text)
audio_datas = self._process_audio_file(tts_file)
self.tts_audio_queue.put(
(SentenceType.MIDDLE, audio_datas, segment_text)
)
self.processed_chars += len(full_text)
return True
return False
@@ -4,7 +4,6 @@ import json
import queue
import asyncio
import traceback
from typing import Callable, Any
import websockets
from core.utils.tts import MarkdownCleaner
from config.logger import setup_logging
@@ -267,7 +266,11 @@ class TTSProvider(TTSProviderBase):
)
if message.content_file and os.path.exists(message.content_file):
# 先处理文件音频数据
self._process_audio_file_stream(message.content_file, callback=lambda audio_data: self.handle_audio_file(audio_data, message.content_detail))
file_audio = self._process_audio_file(message.content_file)
self.before_stop_play_files.append(
(file_audio, message.content_detail)
)
if message.sentence_type == SentenceType.LAST:
try:
logger.bind(tag=TAG).info("开始结束TTS会话...")
@@ -425,6 +428,9 @@ class TTSProvider(TTSProviderBase):
async def _start_monitor_tts_response(self):
"""监听TTS响应"""
opus_datas_cache = []
is_first_sentence = True
first_sentence_segment_count = 0 # 添加计数器
try:
session_finished = False # 标记会话是否正常结束
while not self.conn.stop_event.is_set():
@@ -445,14 +451,37 @@ class TTSProvider(TTSProviderBase):
self.tts_audio_queue.put(
(SentenceType.FIRST, [], self.tts_text)
)
opus_datas_cache = []
first_sentence_segment_count = 0 # 重置计数器
elif (
res.optional.event == EVENT_TTSResponse
and res.header.message_type == AUDIO_ONLY_RESPONSE
):
logger.bind(tag=TAG).debug(f"推送数据到队列里面~~")
self.wav_to_opus_data_audio_raw_stream(res.payload, callback=self.handle_opus)
opus_datas = self.wav_to_opus_data_audio_raw(res.payload)
logger.bind(tag=TAG).debug(
f"推送数据到队列里面帧数~~{len(opus_datas)}"
)
if is_first_sentence:
first_sentence_segment_count += 1
if first_sentence_segment_count <= 6:
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas, None)
)
else:
opus_datas_cache.extend(opus_datas)
else:
# 后续句子缓存
opus_datas_cache.extend(opus_datas)
elif res.optional.event == EVENT_TTSSentenceEnd:
logger.bind(tag=TAG).info(f"句子语音生成成功:{self.tts_text}")
if not is_first_sentence or first_sentence_segment_count > 10:
# 发送缓存的数据
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, None)
)
# 第一句话结束后,将标志设置为False
is_first_sentence = False
elif res.optional.event == EVENT_SessionFinished:
logger.bind(tag=TAG).debug(f"会话结束~~")
self._process_before_stop_play_files()
@@ -626,5 +655,110 @@ class TTSProvider(TTSProviderBase):
)
)
def wav_to_opus_data_audio_raw_stream(self, raw_data_var, is_end=False, callback: Callable[[Any], Any]=None):
return self.opus_encoder.encode_pcm_to_opus_stream(raw_data_var, is_end, callback=callback)
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
def to_tts(self, text: str) -> list:
"""非流式生成音频数据,用于生成音频及测试场景
Args:
text: 要转换的文本
Returns:
list: 音频数据列表
"""
try:
# 创建事件循环
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
# 生成会话ID
session_id = uuid.uuid4().__str__().replace("-", "")
# 存储音频数据
audio_data = []
async def _generate_audio():
# 创建新的WebSocket连接
ws_header = {
"X-Api-App-Key": self.appId,
"X-Api-Access-Key": self.access_token,
"X-Api-Resource-Id": self.resource_id,
"X-Api-Connect-Id": uuid.uuid4(),
}
ws = await websockets.connect(
self.ws_url, additional_headers=ws_header, max_size=1000000000
)
try:
# 启动会话
header = Header(
message_type=FULL_CLIENT_REQUEST,
message_type_specific_flags=MsgTypeFlagWithEvent,
serial_method=JSON,
).as_bytes()
optional = Optional(
event=EVENT_StartSession, sessionId=session_id
).as_bytes()
payload = self.get_payload_bytes(
event=EVENT_StartSession, speaker=self.voice
)
await self.send_event(ws, header, optional, payload)
# 发送文本
header = Header(
message_type=FULL_CLIENT_REQUEST,
message_type_specific_flags=MsgTypeFlagWithEvent,
serial_method=JSON,
).as_bytes()
optional = Optional(
event=EVENT_TaskRequest, sessionId=session_id
).as_bytes()
payload = self.get_payload_bytes(
event=EVENT_TaskRequest, text=text, speaker=self.voice
)
await self.send_event(ws, header, optional, payload)
# 发送结束会话请求
header = Header(
message_type=FULL_CLIENT_REQUEST,
message_type_specific_flags=MsgTypeFlagWithEvent,
serial_method=JSON,
).as_bytes()
optional = Optional(
event=EVENT_FinishSession, sessionId=session_id
).as_bytes()
payload = str.encode("{}")
await self.send_event(ws, header, optional, payload)
# 接收音频数据
while True:
msg = await ws.recv()
res = self.parser_response(msg)
if (
res.optional.event == EVENT_TTSResponse
and res.header.message_type == AUDIO_ONLY_RESPONSE
):
opus_datas = self.wav_to_opus_data_audio_raw(res.payload)
audio_data.extend(opus_datas)
elif res.optional.event == EVENT_SessionFinished:
break
finally:
# 清理资源
try:
await ws.close()
except:
pass
# 运行异步任务
loop.run_until_complete(_generate_audio())
loop.close()
return audio_data
except Exception as e:
logger.bind(tag=TAG).error(f"生成音频数据失败: {str(e)}")
return []
@@ -3,6 +3,8 @@ import queue
import asyncio
import traceback
import aiohttp
import requests
import time
from config.logger import setup_logging
from core.utils.tts import MarkdownCleaner
from core.providers.tts.base import TTSProviderBase
@@ -25,13 +27,15 @@ class TTSProvider(TTSProviderBase):
self.api_url = config.get("api_url", "http://8.138.114.124:11996/tts")
self.audio_format = "pcm"
self.before_stop_play_files = []
self.segment_count = 0
# 创建Opus编码器 需注意接口返回的采样率为24000
self.opus_encoder = opus_encoder_utils.OpusEncoderUtils(
sample_rate=24000, channels=1, frame_size_ms=60
)
# PCM缓冲区
# 文本缓冲区和PCM缓冲区
self.text_buffer = ""
self.pcm_buffer = bytearray()
def tts_text_priority_thread(self):
@@ -44,6 +48,7 @@ class TTSProvider(TTSProviderBase):
self.tts_stop_request = False
self.processed_chars = 0
self.tts_text_buff = []
self.segment_count = 0
self.before_stop_play_files.clear()
elif ContentType.TEXT == message.content_type:
self.tts_text_buff.append(message.content_detail)
@@ -57,11 +62,14 @@ class TTSProvider(TTSProviderBase):
)
if message.content_file and os.path.exists(message.content_file):
# 先处理文件音频数据
self._process_audio_file_stream(message.content_file, callback=lambda audio_data: self.handle_audio_file(audio_data, message.content_detail))
file_audio = self._process_audio_file(message.content_file)
self.before_stop_play_files.append(
(file_audio, message.content_detail)
)
if message.sentence_type == SentenceType.LAST:
# 处理剩余的文本
self._process_remaining_text_stream(True)
self._process_remaining_text(True)
except queue.Empty:
continue
@@ -70,7 +78,7 @@ class TTSProvider(TTSProviderBase):
f"处理TTS文本失败: {str(e)}, 类型: {type(e).__name__}, 堆栈: {traceback.format_exc()}"
)
def _process_remaining_text_stream(self, is_last=False):
def _process_remaining_text(self, is_last=False):
"""处理剩余的文本并生成语音
Returns:
bool: 是否成功处理了文本
@@ -135,6 +143,8 @@ class TTSProvider(TTSProviderBase):
return
self.pcm_buffer.clear()
opus_datas_cache = []
self.tts_audio_queue.put((SentenceType.FIRST, [], text))
# 处理音频流数据
@@ -148,22 +158,41 @@ class TTSProvider(TTSProviderBase):
while len(self.pcm_buffer) >= frame_bytes:
frame = bytes(self.pcm_buffer[:frame_bytes])
del self.pcm_buffer[:frame_bytes]
self.opus_encoder.encode_pcm_to_opus_stream(
frame,
end_of_stream=False,
callback=self.handle_opus
opus = self.opus_encoder.encode_pcm_to_opus(
frame, end_of_stream=False
)
if opus:
if self.segment_count < 10: # 前10个片段直接发送
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus, None)
)
self.segment_count += 1
else:
opus_datas_cache.extend(opus)
# flush 剩余不足一帧的数据
if self.pcm_buffer:
self.opus_encoder.encode_pcm_to_opus_stream(
bytes(self.pcm_buffer),
end_of_stream=True,
callback=self.handle_opus
opus = self.opus_encoder.encode_pcm_to_opus(
bytes(self.pcm_buffer), end_of_stream=True
)
if opus:
if self.segment_count < 10: # 前10个片段直接发送
# 直接发送
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus, None)
)
self.segment_count += 1
else:
# 后续片段缓存
opus_datas_cache.extend(opus)
self.pcm_buffer.clear()
# 如果不是前10个片段,发送缓存的数据
if self.segment_count >= 10 and opus_datas_cache:
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, None)
)
# 如果是最后一段,输出音频获取完毕
if is_last:
self._process_before_stop_play_files()
@@ -177,3 +206,59 @@ class TTSProvider(TTSProviderBase):
await super().close()
if hasattr(self, "opus_encoder"):
self.opus_encoder.close()
def to_tts(self, text: str) -> list:
"""非流式TTS处理,用于测试及保存音频文件的场景
Args:
text: 要转换的文本
Returns:
list: 返回opus编码后的音频数据列表
"""
start_time = time.time()
text = MarkdownCleaner.clean_markdown(text)
payload = {"text": text, "character": self.character}
try:
with requests.post(self.api_url, json=payload, timeout=5) as response:
if response.status_code != 200:
logger.bind(tag=TAG).error(
f"TTS请求失败: {response.status_code}, {response.text}"
)
return []
logger.info(f"TTS请求成功: {text}, 耗时: {time.time() - start_time}")
# 使用opus编码器处理PCM数据
opus_datas = []
pcm_data = response.content
# 计算每帧的字节数
frame_bytes = int(
self.opus_encoder.sample_rate
* self.opus_encoder.channels
* self.opus_encoder.frame_size_ms
/ 1000
* 2
)
# 分帧处理PCM数据
for i in range(0, len(pcm_data), frame_bytes):
frame = pcm_data[i : i + frame_bytes]
if len(frame) < frame_bytes:
# 最后一帧可能不足,用0填充
frame = frame + b"\x00" * (frame_bytes - len(frame))
opus = self.opus_encoder.encode_pcm_to_opus(
frame, end_of_stream=(i + frame_bytes >= len(pcm_data))
)
if opus:
opus_datas.extend(opus)
return opus_datas
except Exception as e:
logger.bind(tag=TAG).error(f"TTS请求异常: {e}")
return []
@@ -1,8 +1,10 @@
import os
import queue
import aiohttp
import asyncio
import traceback
import aiohttp
import requests
import time
from config.logger import setup_logging
from core.utils.tts import MarkdownCleaner
from core.providers.tts.base import TTSProviderBase
@@ -22,15 +24,23 @@ class TTSProvider(TTSProviderBase):
self.api_url = config.get("api_url")
self.audio_format = "pcm"
self.before_stop_play_files = []
self.segment_count = 0 # 添加片段计数器
# 创建Opus编码器
self.opus_encoder = opus_encoder_utils.OpusEncoderUtils(
sample_rate=16000, channels=1, frame_size_ms=60
)
# 添加文本缓冲区
self.text_buffer = ""
# PCM缓冲区
self.pcm_buffer = bytearray()
###################################################################################
# linkerai单流式TTS重写父类的方法--开始
###################################################################################
def tts_text_priority_thread(self):
"""流式文本处理线程"""
while not self.conn.stop_event.is_set():
@@ -41,6 +51,7 @@ class TTSProvider(TTSProviderBase):
self.tts_stop_request = False
self.processed_chars = 0
self.tts_text_buff = []
self.segment_count = 0
self.before_stop_play_files.clear()
elif ContentType.TEXT == message.content_type:
self.tts_text_buff.append(message.content_detail)
@@ -54,10 +65,14 @@ class TTSProvider(TTSProviderBase):
)
if message.content_file and os.path.exists(message.content_file):
# 先处理文件音频数据
self._process_audio_file_stream(message.content_file, callback=lambda audio_data: self.handle_audio_file(audio_data, message.content_detail))
file_audio = self._process_audio_file(message.content_file)
self.before_stop_play_files.append(
(file_audio, message.content_detail)
)
if message.sentence_type == SentenceType.LAST:
# 处理剩余的文本
self._process_remaining_text_stream(True)
self._process_remaining_text(True)
except queue.Empty:
continue
@@ -66,7 +81,7 @@ class TTSProvider(TTSProviderBase):
f"处理TTS文本失败: {str(e)}, 类型: {type(e).__name__}, 堆栈: {traceback.format_exc()}"
)
def _process_remaining_text_stream(self, is_last=False):
def _process_remaining_text(self, is_last=False):
"""处理剩余的文本并生成语音
Returns:
@@ -109,6 +124,10 @@ class TTSProvider(TTSProviderBase):
finally:
return None
###################################################################################
# linkerai单流式TTS重写父类的方法--结束
###################################################################################
async def text_to_speak(self, text, is_last):
"""流式处理TTS音频,每句只推送一次音频列表"""
await self._tts_request(text, is_last)
@@ -157,6 +176,8 @@ class TTSProvider(TTSProviderBase):
return
self.pcm_buffer.clear()
opus_datas_cache = []
self.tts_audio_queue.put((SentenceType.FIRST, [], text))
# 兼容 iter_chunked / iter_chunks / iter_any
@@ -173,21 +194,41 @@ class TTSProvider(TTSProviderBase):
frame = bytes(self.pcm_buffer[:frame_bytes])
del self.pcm_buffer[:frame_bytes]
self.opus_encoder.encode_pcm_to_opus_stream(
frame,
end_of_stream=False,
callback=self.handle_opus
opus = self.opus_encoder.encode_pcm_to_opus(
frame, end_of_stream=False
)
if opus:
if self.segment_count < 10: # 前10个片段直接发送
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus, None)
)
self.segment_count += 1
else:
opus_datas_cache.extend(opus)
# flush 剩余不足一帧的数据
if self.pcm_buffer:
self.opus_encoder.encode_pcm_to_opus_stream(
bytes(self.pcm_buffer),
end_of_stream=True,
callback=self.handle_opus
opus = self.opus_encoder.encode_pcm_to_opus(
bytes(self.pcm_buffer), end_of_stream=True
)
if opus:
if self.segment_count < 10: # 前10个片段直接发送
# 直接发送
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus, None)
)
self.segment_count += 1
else:
# 后续片段缓存
opus_datas_cache.extend(opus)
self.pcm_buffer.clear()
# 如果不是前10个片段,发送缓存的数据
if self.segment_count >= 10 and opus_datas_cache:
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, None)
)
# 如果是最后一段,输出音频获取完毕
if is_last:
self._process_before_stop_play_files()
@@ -195,3 +236,73 @@ class TTSProvider(TTSProviderBase):
except Exception as e:
logger.bind(tag=TAG).error(f"TTS请求异常: {e}")
self.tts_audio_queue.put((SentenceType.LAST, [], None))
def to_tts(self, text: str) -> list:
"""非流式TTS处理,用于测试及保存音频文件的场景
Args:
text: 要转换的文本
Returns:
list: 返回opus编码后的音频数据列表
"""
start_time = time.time()
text = MarkdownCleaner.clean_markdown(text)
params = {
"tts_text": text,
"spk_id": self.voice,
"frame_duration": 60,
"stream": False,
"target_sr": 16000,
"audio_format": self.audio_format,
"instruct_text": "请生成一段自然流畅的语音",
}
headers = {
"Authorization": f"Bearer {self.access_token}",
"Content-Type": "application/json",
}
try:
with requests.get(
self.api_url, params=params, headers=headers, timeout=5
) as response:
if response.status_code != 200:
logger.bind(tag=TAG).error(
f"TTS请求失败: {response.status_code}, {response.text}"
)
return []
logger.info(f"TTS请求成功: {text}, 耗时: {time.time() - start_time}")
# 使用opus编码器处理PCM数据
opus_datas = []
pcm_data = response.content
# 计算每帧的字节数
frame_bytes = int(
self.opus_encoder.sample_rate
* self.opus_encoder.channels
* self.opus_encoder.frame_size_ms
/ 1000
* 2
)
# 分帧处理PCM数据
for i in range(0, len(pcm_data), frame_bytes):
frame = pcm_data[i : i + frame_bytes]
if len(frame) < frame_bytes:
# 最后一帧可能不足,用0填充
frame = frame + b"\x00" * (frame_bytes - len(frame))
opus = self.opus_encoder.encode_pcm_to_opus(
frame, end_of_stream=(i + frame_bytes >= len(pcm_data))
)
if opus:
opus_datas.extend(opus)
return opus_datas
except Exception as e:
logger.bind(tag=TAG).error(f"TTS请求异常: {e}")
return []
@@ -8,7 +8,6 @@ import wave
import websockets
from core.providers.tts.base import TTSProviderBase
from config.logger import setup_logging
from datetime import datetime
TAG = __name__
logger = setup_logging()
@@ -19,12 +18,11 @@ class TTSProvider(TTSProviderBase):
super().__init__(config, delete_audio_file)
self.url = config.get("url", "ws://192.168.1.10:8092/paddlespeech/tts/streaming")
self.protocol = config.get("protocol", "websocket")
if config.get("private_voice"):
self.spk_id = int(config.get("private_voice"))
else:
self.spk_id = int(config.get("spk_id", "0"))
self.spk_id = int(config.get("spk_id", "0"))
sample_rate = config.get("sample_rate", 24000)
self.sample_rate = float(sample_rate) if sample_rate else 24000
@@ -34,21 +32,7 @@ class TTSProvider(TTSProviderBase):
volume = config.get("volume", 1.0)
self.volume = float(volume) if volume else 1.0
self.delete_audio_file = config.get("delete_audio", True)
if not self.delete_audio_file:
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
save_path = config.get("save_path")
if save_path:
if not save_path.endswith('.wav'):
save_path = f"{save_path}_{timestamp}.wav"
else:
other_path = save_path[:-4]
save_path = f"{other_path}_{timestamp}.wav"
self.save_path = save_path
else:
self.save_path = f"./streaming_tts_{timestamp}.wav"
else:
self.save_path = None
self.save_path = config.get("save_path", "./streaming_tts.wav")
async def pcm_to_wav(self, pcm_data: bytes, sample_rate: int = 24000, num_channels: int = 1,
bits_per_sample: int = 16) -> bytes:
@@ -167,12 +151,6 @@ class TTSProvider(TTSProviderBase):
# 接收结束响应避免服务抛出异常
await ws.recv()
# 根据配置决定是否保存文件
if not self.delete_audio_file and self.save_path:
with open(self.save_path, "wb") as f:
f.write(wav_data)
logger.bind(tag=TAG).info(f"音频文件已保存到: {self.save_path}")
# 返回或保存音频数据
if output_file:
with open(output_file, "wb") as file_to_save:
@@ -181,4 +159,4 @@ class TTSProvider(TTSProviderBase):
return wav_data
except Exception as e:
raise Exception(f"Error during TTS WebSocket request: {e} while processing text: {text}")
raise Exception(f"Error during TTS WebSocket request: {e} while processing text: {text}")
@@ -33,7 +33,7 @@ class VADProvider(VADProviderBase):
int(min_silence_duration_ms) if min_silence_duration_ms else 1000
)
# 至少要多少帧才算有语音,增加灵敏度
# 至少要多少帧才算有语音
self.frame_window_threshold = 1
def is_vad(self, conn, opus_packet):
@@ -70,7 +70,9 @@ class VADProvider(VADProviderBase):
# 更新滑动窗口
conn.client_voice_window.append(is_voice)
client_have_voice = (conn.client_voice_window.count(True) >= self.frame_window_threshold)
client_have_voice = (
conn.client_voice_window.count(True) >= self.frame_window_threshold
)
# 如果之前有声音,但本次没有声音,且与上次有声音的时间差已经超过了静默阈值,则认为已经说完一句话
if conn.client_have_voice and not client_have_voice:
@@ -5,8 +5,9 @@ Opus编码工具类
import logging
import traceback
import numpy as np
from typing import Optional, Callable, Any
from typing import List, Optional
from opuslib_next import Encoder
from opuslib_next import constants
@@ -55,14 +56,13 @@ class OpusEncoderUtils:
self.encoder.reset_state()
self.buffer = np.array([], dtype=np.int16)
def encode_pcm_to_opus_stream(self, pcm_data: bytes, end_of_stream: bool, callback: Callable[[Any], Any]):
def encode_pcm_to_opus(self, pcm_data: bytes, end_of_stream: bool) -> List[bytes]:
"""
将PCM数据编码为Opus格式,以流式方式进行处理
将PCM数据编码为Opus格式
Args:
pcm_data: PCM字节数据
end_of_stream: 是否为流的结束,
callback: opus处理方法
end_of_stream: 是否为流的结束
Returns:
Opus数据包列表
@@ -76,6 +76,7 @@ class OpusEncoderUtils:
# 将新数据追加到缓冲区
self.buffer = np.append(self.buffer, new_samples)
opus_packets = []
offset = 0
# 处理所有完整帧
@@ -83,7 +84,7 @@ class OpusEncoderUtils:
frame = self.buffer[offset : offset + self.total_frame_size]
output = self._encode(frame)
if output:
callback(output)
opus_packets.append(output)
offset += self.total_frame_size
# 保留未处理的样本
@@ -97,9 +98,11 @@ class OpusEncoderUtils:
output = self._encode(last_frame)
if output:
callback(output)
opus_packets.append(output)
self.buffer = np.array([], dtype=np.int16)
return opus_packets
def _encode(self, frame: np.ndarray) -> Optional[bytes]:
"""编码一帧音频数据"""
try:
+27 -10
View File
@@ -1,12 +1,15 @@
import io
import struct
from typing import Callable, Any
def decode_opus_from_file(input_file):
"""
从p3文件中解码 Opus 数据,并返回一个 Opus 数据包的列表以及总时长。
"""
opus_datas = []
total_frames = 0
sample_rate = 16000 # 文件采样率
frame_duration_ms = 60 # 帧时长
frame_size = int(sample_rate * frame_duration_ms / 1000)
def decode_opus_from_file_stream(input_file, callback: Callable[[Any], Any]):
"""
从p3文件中解码 Opus 数据,由 callback 处理 Opus 数据包。
"""
with open(input_file, 'rb') as f:
while True:
# 读取头部(4字节):[1字节类型,1字节保留,2字节长度]
@@ -22,13 +25,23 @@ def decode_opus_from_file_stream(input_file, callback: Callable[[Any], Any]):
if len(opus_data) != data_len:
raise ValueError(f"Data length({len(opus_data)}) mismatch({data_len}) in the file.")
callback(opus_data)
opus_datas.append(opus_data)
total_frames += 1
# 计算总时长
total_duration = (total_frames * frame_duration_ms) / 1000.0
return opus_datas, total_duration
def decode_opus_from_bytes_stream(input_bytes, callback: Callable[[Any], Any]):
def decode_opus_from_bytes(input_bytes):
"""
从p3二进制数据中解码 Opus 数据,由 callback 处理 Opus 数据包。
从p3二进制数据中解码 Opus 数据,并返回一个 Opus 数据包的列表以及总时长
"""
import io
opus_datas = []
total_frames = 0
sample_rate = 16000 # 文件采样率
frame_duration_ms = 60 # 帧时长
frame_size = int(sample_rate * frame_duration_ms / 1000)
f = io.BytesIO(input_bytes)
while True:
@@ -39,4 +52,8 @@ def decode_opus_from_bytes_stream(input_bytes, callback: Callable[[Any], Any]):
opus_data = f.read(data_len)
if len(opus_data) != data_len:
raise ValueError(f"Data length({len(opus_data)}) mismatch({data_len}) in the bytes.")
callback(opus_data)
opus_datas.append(opus_data)
total_frames += 1
total_duration = (total_frames * frame_duration_ms) / 1000.0
return opus_datas, total_duration
+47 -31
View File
@@ -1,17 +1,16 @@
import json
import socket
import subprocess
import re
import os
import json
import copy
import socket
import requests
import subprocess
import numpy as np
import opuslib_next
import wave
from io import BytesIO
from core.utils import p3
import numpy as np
import requests
import opuslib_next
from pydub import AudioSegment
from typing import Callable, Any
from core.providers.tts.dto.dto import SentenceType
import copy
TAG = __name__
emoji_map = {
@@ -212,7 +211,7 @@ def extract_json_from_string(input_string):
return None
def audio_to_data_stream(audio_file_path, is_opus=True, callback: Callable[[Any], Any]=None) -> None:
def audio_to_data(audio_file_path, is_opus=True):
# 获取文件后缀名
file_type = os.path.splitext(audio_file_path)[1]
if file_type:
@@ -225,29 +224,33 @@ def audio_to_data_stream(audio_file_path, is_opus=True, callback: Callable[[Any]
# 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
pcm_to_data_stream(raw_data, is_opus, callback)
return pcm_to_data(raw_data, is_opus), duration
def audio_bytes_to_data_stream(audio_bytes, file_type, is_opus, callback: Callable[[Any], Any]) -> None:
def audio_bytes_to_data(audio_bytes, file_type, is_opus=True):
"""
直接用音频二进制数据转为opus/pcm数据,支持wav、mp3、p3
"""
if file_type == "p3":
# 直接用p3解码
return p3.decode_opus_from_bytes_stream(audio_bytes, callback)
return p3.decode_opus_from_bytes(audio_bytes)
else:
# 其他格式用pydub
audio = AudioSegment.from_file(
BytesIO(audio_bytes), format=file_type, parameters=["-nostdin"]
)
audio = audio.set_channels(1).set_frame_rate(16000).set_sample_width(2)
duration = len(audio) / 1000.0
raw_data = audio.raw_data
pcm_to_data_stream(raw_data, is_opus, callback)
return pcm_to_data(raw_data, is_opus), duration
def pcm_to_data_stream(raw_data, is_opus=True, callback: Callable[[Any], Any] = None):
def pcm_to_data(raw_data, is_opus=True):
# 初始化Opus编码器
encoder = opuslib_next.Encoder(16000, 1, opuslib_next.APPLICATION_AUDIO)
@@ -255,6 +258,7 @@ def pcm_to_data_stream(raw_data, is_opus=True, callback: Callable[[Any], Any] =
frame_duration = 60 # 60ms per frame
frame_size = int(16000 * frame_duration / 1000) # 960 samples/frame
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
@@ -269,28 +273,40 @@ def pcm_to_data_stream(raw_data, is_opus=True, callback: Callable[[Any], Any] =
np_frame = np.frombuffer(chunk, dtype=np.int16)
# 编码Opus数据
frame_data = encoder.encode(np_frame.tobytes(), frame_size)
callback(frame_data)
else:
frame_data = chunk if isinstance(chunk, bytes) else bytes(chunk)
callback(frame_data)
def play_audio_response(conn, response):
"""音频响应处理"""
conn.tts.tts_audio_queue.put((SentenceType.FIRST, [], response.get("text")))
play_audio_frames(conn, response.get("file_path"))
conn.tts.tts_audio_queue.put((SentenceType.LAST, [], None))
datas.append(frame_data)
return datas
def play_audio_frames(conn, file_path):
"""播放音频文件并处理发送帧数据"""
def handle_audio_frame(frame_data):
conn.tts.tts_audio_queue.put((SentenceType.MIDDLE, frame_data, None))
def opus_datas_to_wav_bytes(opus_datas, sample_rate=16000, channels=1):
"""
将opus帧列表解码为wav字节流
"""
decoder = opuslib_next.Decoder(sample_rate, channels)
pcm_datas = []
frame_duration = 60 # ms
frame_size = int(sample_rate * frame_duration / 1000) # 960
for opus_frame in opus_datas:
# 解码为PCM(返回bytes,2字节/采样点)
pcm = decoder.decode(opus_frame, frame_size)
pcm_datas.append(pcm)
pcm_bytes = b"".join(pcm_datas)
# 写入wav字节流
wav_buffer = BytesIO()
with wave.open(wav_buffer, "wb") as wf:
wf.setnchannels(channels)
wf.setsampwidth(2) # 16bit
wf.setframerate(sample_rate)
wf.writeframes(pcm_bytes)
return wav_buffer.getvalue()
audio_to_data_stream(
file_path,
is_opus=True,
callback=handle_audio_frame
)
def check_vad_update(before_config, new_config):
if (
@@ -0,0 +1,140 @@
import os
import re
import yaml
import time
import hashlib
import portalocker
from typing import Dict
class FileLock:
def __init__(self, file, timeout=5):
self.file = file
self.timeout = timeout
self.start_time = None
def __enter__(self):
self.start_time = time.time()
while True:
try:
portalocker.lock(self.file, portalocker.LOCK_EX | portalocker.LOCK_NB)
return self.file
except portalocker.LockException:
if time.time() - self.start_time > self.timeout:
raise TimeoutError("获取文件锁超时")
time.sleep(0.1)
def __exit__(self, exc_type, exc_val, exc_tb):
portalocker.unlock(self.file)
class WakeupWordsConfig:
def __init__(self):
self.config_file = "data/.wakeup_words.yaml"
self.assets_dir = "config/assets/wakeup_words"
self._ensure_directories()
self._config_cache = None
self._last_load_time = 0
self._cache_ttl = 1 # 缓存有效期(秒)
self._lock_timeout = 5 # 文件锁超时时间(秒)
def _ensure_directories(self):
"""确保必要的目录存在"""
os.makedirs(os.path.dirname(self.config_file), exist_ok=True)
os.makedirs(self.assets_dir, exist_ok=True)
def _load_config(self) -> Dict:
"""加载配置文件,使用缓存机制"""
current_time = time.time()
# 如果缓存有效,直接返回缓存
if (
self._config_cache is not None
and current_time - self._last_load_time < self._cache_ttl
):
return self._config_cache
try:
with open(self.config_file, "a+") as f:
with FileLock(f, timeout=self._lock_timeout):
f.seek(0)
content = f.read()
config = yaml.safe_load(content) if content else {}
self._config_cache = config
self._last_load_time = current_time
return config
except (TimeoutError, IOError) as e:
print(f"加载配置文件失败: {e}")
return {}
except Exception as e:
print(f"加载配置文件时发生未知错误: {e}")
return {}
def _save_config(self, config: Dict):
"""保存配置到文件,使用文件锁保护"""
try:
with open(self.config_file, "w") as f:
with FileLock(f, timeout=self._lock_timeout):
yaml.dump(config, f, allow_unicode=True)
self._config_cache = config
self._last_load_time = time.time()
except (TimeoutError, IOError) as e:
print(f"保存配置文件失败: {e}")
raise
except Exception as e:
print(f"保存配置文件时发生未知错误: {e}")
raise
def get_wakeup_response(self, voice: str) -> Dict:
voice = hashlib.md5(voice.encode()).hexdigest()
"""获取唤醒词回复配置"""
config = self._load_config()
if not config or voice not in config:
return None
# 检查文件大小
file_path = config[voice]["file_path"]
if not os.path.exists(file_path) or os.stat(file_path).st_size < (15 * 1024):
return None
return config[voice]
def update_wakeup_response(self, voice: str, file_path: str, text: str):
"""更新唤醒词回复配置"""
try:
# 过滤表情符号
filtered_text = re.sub(r'[\U0001F600-\U0001F64F\U0001F900-\U0001F9FF]', '', text)
config = self._load_config()
voice_hash = hashlib.md5(voice.encode()).hexdigest()
config[voice_hash] = {
"voice": voice,
"file_path": file_path,
"time": time.time(),
"text": filtered_text,
}
self._save_config(config)
except Exception as e:
print(f"更新唤醒词回复配置失败: {e}")
raise
def generate_file_path(self, voice: str) -> str:
"""生成音频文件路径,使用voice的哈希值作为文件名"""
try:
# 生成voice的哈希值
voice_hash = hashlib.md5(voice.encode()).hexdigest()
file_path = os.path.join(self.assets_dir, f"{voice_hash}.wav")
# 如果文件已存在,先删除
if os.path.exists(file_path):
try:
os.remove(file_path)
except Exception as e:
print(f"删除已存在的音频文件失败: {e}")
raise
return file_path
except Exception as e:
print(f"生成音频文件路径失败: {e}")
raise
@@ -212,6 +212,7 @@ async def play_local_music(conn, specific_file=None):
conn.logger.bind(tag=TAG).error(f"选定的音乐文件不存在: {music_path}")
return
text = _get_random_play_prompt(selected_music)
await send_stt_message(conn, text)
conn.dialogue.put(Message(role="assistant", content=text))
if conn.intent_type == "intent_llm":