fix: 唤醒机制

This commit is contained in:
Sakura-RanChen
2025-09-02 11:18:04 +08:00
parent b4f4995ff9
commit c428a9ddee
15 changed files with 848 additions and 145 deletions
+4
View File
@@ -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
+117 -1
View File
@@ -1,5 +1,13 @@
import time
import json
import random
import asyncio
from core.utils.dialogue import Message
from core.utils.util import audio_to_data_stream
from core.providers.tts.dto.dto import SentenceType
from core.utils.wakeup_word import WakeupWordsConfig
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.tools.device_mcp import (
MCPClient,
send_mcp_initialize_message,
@@ -8,6 +16,18 @@ from core.providers.tools.device_mcp import (
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 +48,100 @@ 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",
}
# 获取音频数据
opus_packets = []
def handle_audio_frame(frame_data):
opus_packets.append(frame_data)
audio_to_data_stream(response.get("file_path"), is_opus=True, callback=handle_audio_frame)
# 播放唤醒词回复
conn.client_abort = False
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()
@@ -3,6 +3,7 @@ import uuid
import asyncio
from core.utils.dialogue import Message
from core.providers.tts.dto.dto import ContentType
from core.handle.helloHandle import checkWakeupWords
from plugins_func.register import Action, ActionResponse
from core.handle.sendAudioHandle import send_stt_message
from core.utils.util import remove_punctuation_and_length
@@ -27,6 +28,10 @@ async def handle_user_intent(conn, text):
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
return False
@@ -1,5 +1,6 @@
import time
import json
import asyncio
from core.handle.abortHandle import handleAbortMessage
from core.handle.intentHandler import handle_user_intent
from core.utils.output_counter import check_device_output_limit
@@ -10,12 +11,16 @@ 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)
@@ -24,6 +29,11 @@ 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
@@ -30,13 +30,14 @@ async def sendAudioMessage(conn, sentenceType, audios, text):
# 播放音频
async def sendAudio(conn, audios, pre_buffer=False):
async def sendAudio(conn, audios, pre_buffer=False, frame_duration=60):
"""
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
frame_duration: 帧时长(毫秒),匹配 Opus 编码
"""
if audios is None or len(audios) == 0:
return
@@ -60,7 +61,6 @@ async def sendAudio(conn, audios, pre_buffer=False):
"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
@@ -77,6 +77,35 @@ async def sendAudio(conn, audios, pre_buffer=False):
# 更新流控状态
flow_control["packet_count"] += 1
flow_control["last_send_time"] = time.perf_counter()
else:
# 流控参数优化
start_time = time.perf_counter()
play_position = 0
# 执行预缓冲
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:]
# 播放剩余音频帧
for opus_packet in remaining_audios:
if conn.client_abort:
break
# 重置没有声音的状态
conn.last_activity_time = time.time() * 1000
# 计算预期发送时间
expected_time = start_time + (play_position / 1000)
current_time = time.perf_counter()
delay = expected_time - current_time
if delay > 0:
await asyncio.sleep(delay)
await conn.websocket.send(opus_packet)
play_position += frame_duration
async def send_tts_message(conn, state, text=None):
+11 -4
View File
@@ -3,8 +3,9 @@ import asyncio
from core.utils.util import filter_sensitive_info
from core.handle.abortHandle import handleAbortMessage
from core.handle.helloHandle import handleHelloMessage
from core.handle.receiveAudioHandle import handleAudioMessage
from core.handle.reportHandle import enqueue_asr_report
from core.providers.tools.device_mcp import handle_mcp_message
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
@@ -55,10 +56,16 @@ 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 and enable_greeting:
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:
+55 -85
View File
@@ -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()
@@ -102,10 +90,27 @@ class ASRProviderBase(ABC):
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)
# 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)
# 声纹识别任务(公共逻辑)
# 定义声纹识别任务
def run_voiceprint():
if not wav_data:
return None
@@ -124,83 +129,48 @@ 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
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, _ = 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}")
@@ -478,3 +478,142 @@ 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)):
self.opus_encoder.encode_pcm_to_opus_stream(
msg,
end_of_stream=False,
callback=lambda opus: audio_data.append(opus)
)
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 []
+67 -6
View File
@@ -1,21 +1,22 @@
import os
import re
import queue
import time
import uuid
import queue
import asyncio
import threading
from typing import Callable, Any
import traceback
from core.utils import p3
import time
from datetime import datetime
from core.utils import textUtils
from typing import Callable, Any
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.tts import MarkdownCleaner
from core.utils.output_counter import add_device_output
from core.handle.reportHandle import enqueue_tts_report
from core.handle.sendAudioHandle import sendAudioMessage
from core.utils.util import audio_bytes_to_data_stream, audio_to_data_stream
from core.providers.tts.dto.dto import (
TTSMessageDTO,
SentenceType,
@@ -23,8 +24,6 @@ from core.providers.tts.dto.dto import (
InterfaceType,
)
import traceback
TAG = __name__
logger = setup_logging()
@@ -144,6 +143,68 @@ class TTSProviderBase(ABC):
except Exception as e:
logger.bind(tag=TAG).error(f"Failed to generate TTS file: {e}")
return None
def to_tts(self, text):
text = MarkdownCleaner.clean_markdown(text)
max_repeat_time = 5
if self.delete_audio_file:
# 需要删除文件的直接转为音频数据
while max_repeat_time > 0:
try:
audio_bytes = asyncio.run(self.text_to_speak(text, None))
if audio_bytes:
audio_datas = []
audio_bytes_to_data_stream(
audio_bytes,
file_type=self.audio_file_type,
is_opus=True,
callback=lambda data: audio_datas.append(data)
)
return audio_datas
else:
max_repeat_time -= 1
except Exception as e:
logger.bind(tag=TAG).warning(
f"语音生成失败{5 - max_repeat_time + 1}次: {text},错误: {e}"
)
max_repeat_time -= 1
if max_repeat_time > 0:
logger.bind(tag=TAG).info(
f"语音生成成功: {text},重试{5 - max_repeat_time}"
)
else:
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"
)
return None
else:
tmp_file = self.generate_filename()
try:
while not os.path.exists(tmp_file) and max_repeat_time > 0:
try:
asyncio.run(self.text_to_speak(text, tmp_file))
except Exception as e:
logger.bind(tag=TAG).warning(
f"语音生成失败{5 - max_repeat_time + 1}次: {text},错误: {e}"
)
# 未执行成功,删除文件
if os.path.exists(tmp_file):
os.remove(tmp_file)
max_repeat_time -= 1
if max_repeat_time > 0:
logger.bind(tag=TAG).info(
f"语音生成成功: {text}:{tmp_file},重试{5 - max_repeat_time}"
)
else:
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"
)
return tmp_file
except Exception as e:
logger.bind(tag=TAG).error(f"Failed to generate TTS file: {e}")
return None
@abstractmethod
async def text_to_speak(self, text, output_file):
@@ -628,3 +628,104 @@ 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 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
):
self.wav_to_opus_data_audio_raw_stream(res.payload, callback=lambda opus_frame: audio_data.append(opus_frame))
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 []
@@ -1,8 +1,10 @@
import os
import time
import queue
import asyncio
import traceback
import aiohttp
import asyncio
import requests
import traceback
from config.logger import setup_logging
from core.utils.tts import MarkdownCleaner
from core.providers.tts.base import TTSProviderBase
@@ -177,3 +179,57 @@ 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))
self.opus_encoder.encode_pcm_to_opus_stream(
frame,
end_of_stream=(i + frame_bytes >= len(pcm_data)),
callback=lambda opus: opus_datas.append(opus)
)
return opus_datas
except Exception as e:
logger.bind(tag=TAG).error(f"TTS请求异常: {e}")
return []
@@ -1,7 +1,9 @@
import os
import time
import queue
import aiohttp
import asyncio
import requests
import traceback
from config.logger import setup_logging
from core.utils.tts import MarkdownCleaner
@@ -195,3 +197,71 @@ 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))
self.opus_encoder.encode_pcm_to_opus_stream(
frame,
end_of_stream=(i + frame_bytes >= len(pcm_data)),
callback=lambda opus: opus_datas.append(opus)
)
return opus_datas
except Exception as e:
logger.bind(tag=TAG).error(f"TTS请求异常: {e}")
return []
@@ -1,14 +1,15 @@
import asyncio
import json
import base64
import aiohttp
import numpy as np
import io
import wave
import json
import base64
import asyncio
import websockets
from core.providers.tts.base import TTSProviderBase
from config.logger import setup_logging
import numpy as np
from datetime import datetime
from config.logger import setup_logging
from core.providers.tts.base import TTSProviderBase
TAG = __name__
logger = setup_logging()
@@ -74,43 +75,9 @@ class TTSProvider(TTSProviderBase):
async def text_to_speak(self, text, output_file):
if self.protocol == "websocket":
return await self.text_streaming(text, output_file)
elif self.protocol == "http":
return await self.text(text, output_file)
else:
raise ValueError("Unsupported protocol. Please use 'websocket' or 'http'.")
async def text(self, text, output_file):
request_json = {
"text": text,
"spk_id": self.spk_id,
"speed": self.speed,
"volume": self.volume,
"sample_rate": self.sample_rate,
"save_path": self.save_path
}
try:
async with aiohttp.ClientSession() as session:
async with session.post(self.url, json=request_json) as resp:
if resp.status == 200:
resp_json = await resp.json()
if resp_json.get("success"):
data = resp_json["result"]
audio_bytes = base64.b64decode(data["audio"])
if output_file:
with open(output_file, "wb") as file_to_save:
file_to_save.write(audio_bytes)
else:
return audio_bytes
else:
raise Exception(
f"Error: {resp_json.get('message', 'Unknown error')} while processing text: {text}")
else:
raise Exception(
f"HTTP Error: {resp.status} - {await resp.text()} while processing text: {text}")
except Exception as e:
raise Exception(f"Error during TTS HTTP request: {e} while processing text: {text}")
async def text_streaming(self, text, output_file):
try:
# 使用 websockets 异步连接到 WebSocket 服务器
+28
View File
@@ -2,6 +2,7 @@ import re
import os
import json
import copy
import wave
import socket
import requests
import subprocess
@@ -292,6 +293,33 @@ def play_audio_frames(conn, file_path):
callback=handle_audio_frame
)
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()
def check_vad_update(before_config, new_config):
if (
new_config.get("selected_module") is None
@@ -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