Files
xiaozhi-esp32-server/main/xiaozhi-server/core/connection.py
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import os
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import copy
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import json
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import subprocess
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import sys
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import uuid
import time
import queue
import asyncio
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import traceback
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import threading
import websockets
from typing import Dict, Any
from plugins_func.loadplugins import auto_import_modules
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from config.logger import setup_logging
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from core.utils.dialogue import Message, Dialogue
from core.handle.textHandle import handleTextMessage
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from core.utils.util import (
get_string_no_punctuation_or_emoji,
extract_json_from_string,
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initialize_modules,
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check_vad_update,
check_asr_update,
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)
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from concurrent.futures import ThreadPoolExecutor, TimeoutError
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from core.handle.sendAudioHandle import sendAudioMessage
from core.handle.receiveAudioHandle import handleAudioMessage
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from core.handle.functionHandler import FunctionHandler
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from plugins_func.register import Action, ActionResponse
from core.auth import AuthMiddleware, AuthenticationError
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from core.mcp.manager import MCPManager
from config.config_loader import get_private_config_from_api
from config.manage_api_client import DeviceNotFoundException, DeviceBindException
from core.utils.output_counter import add_device_output
from core.handle.reportHandle import enqueue_tts_report, report
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TAG = __name__
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auto_import_modules("plugins_func.functions")
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class TTSException(RuntimeError):
pass
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class ConnectionHandler:
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def __init__(
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self,
config: Dict[str, Any],
_vad,
_asr,
_llm,
_tts,
_memory,
_intent,
server=None,
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):
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self.common_config = config
self.config = copy.deepcopy(config)
self.session_id = str(uuid.uuid4())
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self.logger = setup_logging()
self.server = server # 保存server实例的引用
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self.auth = AuthMiddleware(config)
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self.need_bind = False
self.bind_code = None
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self.read_config_from_api = self.config.get("read_config_from_api", False)
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self.websocket = None
self.headers = None
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self.device_id = None
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self.client_ip = None
self.client_ip_info = {}
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self.prompt = None
self.welcome_msg = None
self.max_output_size = 0
self.chat_history_conf = 0
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# 客户端状态相关
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self.client_abort = False
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self.client_listen_mode = "auto"
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# 线程任务相关
self.loop = asyncio.get_event_loop()
self.stop_event = threading.Event()
self.tts_queue = queue.Queue()
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self.audio_play_queue = queue.Queue()
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self.executor = ThreadPoolExecutor(max_workers=10)
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# 上报线程
self.report_queue = queue.Queue()
self.report_thread = None
# TODO(haotian): 2025/5/12 可以通过修改此处,调节asr的上报和tts的上报
self.report_asr_enable = self.read_config_from_api
self.report_tts_enable = self.read_config_from_api
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# 依赖的组件
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self.vad = None
self.asr = None
self._asr = _asr
self._vad = _vad
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self.llm = _llm
self.tts = _tts
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self.memory = _memory
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self.intent = _intent
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# vad相关变量
self.client_audio_buffer = bytearray()
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self.client_have_voice = False
self.client_have_voice_last_time = 0.0
self.client_no_voice_last_time = 0.0
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self.client_voice_stop = False
# asr相关变量
self.asr_audio = []
self.asr_server_receive = True
# llm相关变量
self.llm_finish_task = False
self.dialogue = Dialogue()
# tts相关变量
self.tts_first_text_index = -1
self.tts_last_text_index = -1
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# iot相关变量
self.iot_descriptors = {}
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self.func_handler = None
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self.cmd_exit = self.config["exit_commands"]
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self.max_cmd_length = 0
for cmd in self.cmd_exit:
if len(cmd) > self.max_cmd_length:
self.max_cmd_length = len(cmd)
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# 是否在聊天结束后关闭连接
self.close_after_chat = False
self.load_function_plugin = False
self.intent_type = "nointent"
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self.timeout_task = None
self.timeout_seconds = (
int(self.config.get("close_connection_no_voice_time", 120)) + 60
) # 在原来第一道关闭的基础上加60秒,进行二道关闭
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self.audio_format = "opus"
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async def handle_connection(self, ws):
try:
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# 获取并验证headers
self.headers = dict(ws.request.headers)
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if self.headers.get("device-id", None) is None:
# 尝试从 URL 的查询参数中获取 device-id
from urllib.parse import parse_qs, urlparse
# 从 WebSocket 请求中获取路径
request_path = ws.request.path
if not request_path:
self.logger.bind(tag=TAG).error("无法获取请求路径")
return
parsed_url = urlparse(request_path)
query_params = parse_qs(parsed_url.query)
if "device-id" in query_params:
self.headers["device-id"] = query_params["device-id"][0]
self.headers["client-id"] = query_params["client-id"][0]
else:
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await ws.send("端口正常,如需测试连接,请使用test_page.html")
await self.close(ws)
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return
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# 获取客户端ip地址
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self.client_ip = ws.remote_address[0]
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self.logger.bind(tag=TAG).info(
f"{self.client_ip} conn - Headers: {self.headers}"
)
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# 进行认证
await self.auth.authenticate(self.headers)
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# 认证通过,继续处理
self.websocket = ws
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self.device_id = self.headers.get("device-id", None)
# 启动超时检查任务
self.timeout_task = asyncio.create_task(self._check_timeout())
self.welcome_msg = self.config["xiaozhi"]
self.welcome_msg["session_id"] = self.session_id
await self.websocket.send(json.dumps(self.welcome_msg))
# 获取差异化配置
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self._initialize_private_config()
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# 异步初始化
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self.executor.submit(self._initialize_components)
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# tts 消化线程
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self.tts_priority_thread = threading.Thread(
target=self._tts_priority_thread, daemon=True
)
self.tts_priority_thread.start()
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# 音频播放 消化线程
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self.audio_play_priority_thread = threading.Thread(
target=self._audio_play_priority_thread, daemon=True
)
self.audio_play_priority_thread.start()
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try:
async for message in self.websocket:
await self._route_message(message)
except websockets.exceptions.ConnectionClosed:
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self.logger.bind(tag=TAG).info("客户端断开连接")
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except AuthenticationError as e:
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self.logger.bind(tag=TAG).error(f"Authentication failed: {str(e)}")
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return
except Exception as e:
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stack_trace = traceback.format_exc()
self.logger.bind(tag=TAG).error(f"Connection error: {str(e)}-{stack_trace}")
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return
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finally:
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await self._save_and_close(ws)
async def _save_and_close(self, ws):
"""保存记忆并关闭连接"""
try:
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if self.memory:
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# 使用线程池异步保存记忆
def save_memory_task():
try:
# 创建新事件循环(避免与主循环冲突)
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
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loop.run_until_complete(
self.memory.save_memory(self.dialogue.dialogue)
)
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except Exception as e:
self.logger.bind(tag=TAG).error(f"保存记忆失败: {e}")
finally:
loop.close()
# 启动线程保存记忆,不等待完成
threading.Thread(target=save_memory_task, daemon=True).start()
except Exception as e:
self.logger.bind(tag=TAG).error(f"保存记忆失败: {e}")
finally:
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# 立即关闭连接,不等待记忆保存完成
await self.close(ws)
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async def reset_timeout(self):
"""重置超时计时器"""
if self.timeout_task:
self.timeout_task.cancel()
self.timeout_task = asyncio.create_task(self._check_timeout())
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async def _route_message(self, message):
"""消息路由"""
# 重置超时计时器
await self.reset_timeout()
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if isinstance(message, str):
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await handleTextMessage(self, message)
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elif isinstance(message, bytes):
await handleAudioMessage(self, message)
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async def handle_restart(self, message):
"""处理服务器重启请求"""
try:
self.logger.bind(tag=TAG).info("收到服务器重启指令,准备执行...")
# 发送确认响应
await self.websocket.send(
json.dumps(
{
"type": "server_response",
"status": "success",
"message": "服务器重启中...",
}
)
)
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# 异步执行重启操作
def restart_server():
"""实际执行重启的方法"""
time.sleep(1)
self.logger.bind(tag=TAG).info("执行服务器重启...")
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subprocess.Popen(
[sys.executable, "app.py"],
stdin=sys.stdin,
stdout=sys.stdout,
stderr=sys.stderr,
start_new_session=True,
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)
os._exit(0)
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# 使用线程执行重启避免阻塞事件循环
threading.Thread(target=restart_server, daemon=True).start()
except Exception as e:
self.logger.bind(tag=TAG).error(f"重启失败: {str(e)}")
await self.websocket.send(
json.dumps(
{
"type": "server_response",
"status": "error",
"message": f"Restart failed: {str(e)}",
}
)
)
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def _initialize_components(self):
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"""初始化组件"""
if self.config.get("prompt") is not None:
self.prompt = self.config["prompt"]
self.change_system_prompt(self.prompt)
self.logger.bind(tag=TAG).info(
f"初始化组件: prompt成功 {self.prompt[:50]}..."
)
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"""初始化本地组件"""
if self.vad is None:
self.vad = self._vad
if self.asr is None:
self.asr = self._asr
"""加载记忆"""
self._initialize_memory()
"""加载意图识别"""
self._initialize_intent()
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"""初始化上报线程"""
self._init_report_threads()
def _init_report_threads(self):
"""初始化ASR和TTS上报线程"""
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if not self.read_config_from_api or self.need_bind:
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return
if self.chat_history_conf == 0:
return
if self.report_thread is None or not self.report_thread.is_alive():
self.report_thread = threading.Thread(
target=self._report_worker, daemon=True
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)
self.report_thread.start()
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self.logger.bind(tag=TAG).info("TTS上报线程已启动")
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def _initialize_private_config(self):
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"""如果是从配置文件获取,则进行二次实例化"""
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if not self.read_config_from_api:
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return
"""从接口获取差异化的配置进行二次实例化,非全量重新实例化"""
try:
begin_time = time.time()
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private_config = get_private_config_from_api(
self.config,
self.headers.get("device-id"),
self.headers.get("client-id", self.headers.get("device-id")),
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)
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private_config["delete_audio"] = bool(self.config.get("delete_audio", True))
self.logger.bind(tag=TAG).info(
f"{time.time() - begin_time} 秒,获取差异化配置成功: {json.dumps(filter_sensitive_info(private_config), ensure_ascii=False)}"
)
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except DeviceNotFoundException as e:
self.need_bind = True
private_config = {}
except DeviceBindException as e:
self.need_bind = True
self.bind_code = e.bind_code
private_config = {}
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except Exception as e:
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self.need_bind = True
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self.logger.bind(tag=TAG).error(f"获取差异化配置失败: {e}")
private_config = {}
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init_llm, init_tts, init_memory, init_intent = (
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False,
False,
False,
False,
)
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init_vad = check_vad_update(self.common_config, private_config)
init_asr = check_asr_update(self.common_config, private_config)
if private_config.get("TTS", None) is not None:
init_tts = True
self.config["TTS"] = private_config["TTS"]
self.config["selected_module"]["TTS"] = private_config["selected_module"][
"TTS"
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]
if private_config.get("LLM", None) is not None:
init_llm = True
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self.config["LLM"] = private_config["LLM"]
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self.config["selected_module"]["LLM"] = private_config["selected_module"][
"LLM"
]
if private_config.get("Memory", None) is not None:
init_memory = True
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self.config["Memory"] = private_config["Memory"]
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self.config["selected_module"]["Memory"] = private_config[
"selected_module"
]["Memory"]
if private_config.get("Intent", None) is not None:
init_intent = True
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self.config["Intent"] = private_config["Intent"]
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self.config["selected_module"]["Intent"] = private_config[
"selected_module"
]["Intent"]
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if private_config.get("prompt", None) is not None:
self.config["prompt"] = private_config["prompt"]
if private_config.get("summaryMemory", None) is not None:
self.config["summaryMemory"] = private_config["summaryMemory"]
if private_config.get("device_max_output_size", None) is not None:
self.max_output_size = int(private_config["device_max_output_size"])
if private_config.get("chat_history_conf", None) is not None:
self.chat_history_conf = int(private_config["chat_history_conf"])
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try:
modules = initialize_modules(
self.logger,
private_config,
init_vad,
init_asr,
init_llm,
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init_tts,
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init_memory,
init_intent,
)
except Exception as e:
self.logger.bind(tag=TAG).error(f"初始化组件失败: {e}")
modules = {}
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if modules.get("tts", None) is not None:
self.tts = modules["tts"]
if modules.get("vad", None) is not None:
self.vad = modules["vad"]
if modules.get("asr", None) is not None:
self.asr = modules["asr"]
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if modules.get("llm", None) is not None:
self.llm = modules["llm"]
if modules.get("intent", None) is not None:
self.intent = modules["intent"]
if modules.get("memory", None) is not None:
self.memory = modules["memory"]
def _initialize_memory(self):
"""初始化记忆模块"""
self.memory.init_memory(
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role_id=self.device_id,
llm=self.llm,
summary_memory=self.config.get("summaryMemory", None),
save_to_file=not self.read_config_from_api,
)
def _initialize_intent(self):
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self.intent_type = self.config["Intent"][
self.config["selected_module"]["Intent"]
]["type"]
if self.intent_type == "function_call" or self.intent_type == "intent_llm":
self.load_function_plugin = True
"""初始化意图识别模块"""
# 获取意图识别配置
intent_config = self.config["Intent"]
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intent_type = self.config["Intent"][self.config["selected_module"]["Intent"]][
"type"
]
# 如果使用 nointent,直接返回
if intent_type == "nointent":
return
# 使用 intent_llm 模式
elif intent_type == "intent_llm":
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intent_llm_name = intent_config[self.config["selected_module"]["Intent"]][
"llm"
]
if intent_llm_name and intent_llm_name in self.config["LLM"]:
# 如果配置了专用LLM,则创建独立的LLM实例
from core.utils import llm as llm_utils
intent_llm_config = self.config["LLM"][intent_llm_name]
intent_llm_type = intent_llm_config.get("type", intent_llm_name)
intent_llm = llm_utils.create_instance(
intent_llm_type, intent_llm_config
)
self.logger.bind(tag=TAG).info(
f"为意图识别创建了专用LLM: {intent_llm_name}, 类型: {intent_llm_type}"
)
self.intent.set_llm(intent_llm)
else:
# 否则使用主LLM
self.intent.set_llm(self.llm)
self.logger.bind(tag=TAG).info("使用主LLM作为意图识别模型")
"""加载插件"""
self.func_handler = FunctionHandler(self)
self.mcp_manager = MCPManager(self)
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"""加载MCP工具"""
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asyncio.run_coroutine_threadsafe(
self.mcp_manager.initialize_servers(), self.loop
)
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def change_system_prompt(self, prompt):
self.prompt = prompt
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# 更新系统prompt至上下文
self.dialogue.update_system_message(self.prompt)
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def chat(self, query):
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self.dialogue.put(Message(role="user", content=query))
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response_message = []
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processed_chars = 0 # 跟踪已处理的字符位置
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try:
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# 使用带记忆的对话
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memory_str = None
if self.memory is not None:
future = asyncio.run_coroutine_threadsafe(
self.memory.query_memory(query), self.loop
)
memory_str = future.result()
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self.logger.bind(tag=TAG).debug(f"记忆内容: {memory_str}")
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llm_responses = self.llm.response(
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self.session_id, self.dialogue.get_llm_dialogue_with_memory(memory_str)
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)
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except Exception as e:
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self.logger.bind(tag=TAG).error(f"LLM 处理出错 {query}: {e}")
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return None
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self.llm_finish_task = False
text_index = 0
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for content in llm_responses:
response_message.append(content)
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if self.client_abort:
break
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# 合并当前全部文本并处理未分割部分
full_text = "".join(response_message)
current_text = full_text[processed_chars:] # 从未处理的位置开始
# 查找最后一个有效标点
punctuations = ("。", ".", "", "?", "", "!", "", ";", "")
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last_punct_pos = -1
number_flag = True
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for punct in punctuations:
pos = current_text.rfind(punct)
prev_char = current_text[pos - 1] if pos - 1 >= 0 else ""
# 如果.前面是数字统一判断为小数
if prev_char.isdigit() and punct == ".":
number_flag = False
if pos > last_punct_pos and number_flag:
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last_punct_pos = pos
# 找到分割点则处理
if last_punct_pos != -1:
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segment_text_raw = current_text[: last_punct_pos + 1]
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segment_text = get_string_no_punctuation_or_emoji(segment_text_raw)
if segment_text:
# 强制设置空字符,测试TTS出错返回语音的健壮性
# if text_index % 2 == 0:
# segment_text = " "
text_index += 1
self.recode_first_last_text(segment_text, text_index)
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future = self.executor.submit(
self.speak_and_play, segment_text, text_index
)
self.tts_queue.put((future, text_index))
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processed_chars += len(segment_text_raw) # 更新已处理字符位置
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# 处理最后剩余的文本
full_text = "".join(response_message)
remaining_text = full_text[processed_chars:]
if remaining_text:
segment_text = get_string_no_punctuation_or_emoji(remaining_text)
if segment_text:
text_index += 1
self.recode_first_last_text(segment_text, text_index)
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future = self.executor.submit(
self.speak_and_play, segment_text, text_index
)
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self.tts_queue.put((future, text_index))
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self.llm_finish_task = True
self.dialogue.put(Message(role="assistant", content="".join(response_message)))
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self.logger.bind(tag=TAG).debug(
json.dumps(self.dialogue.get_llm_dialogue(), indent=4, ensure_ascii=False)
)
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return True
def chat_with_function_calling(self, query, tool_call=False):
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self.logger.bind(tag=TAG).debug(f"Chat with function calling start: {query}")
"""Chat with function calling for intent detection using streaming"""
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if not tool_call:
self.dialogue.put(Message(role="user", content=query))
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# Define intent functions
functions = None
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if hasattr(self, "func_handler"):
functions = self.func_handler.get_functions()
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response_message = []
processed_chars = 0 # 跟踪已处理的字符位置
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try:
start_time = time.time()
# 使用带记忆的对话
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memory_str = None
if self.memory is not None:
future = asyncio.run_coroutine_threadsafe(
self.memory.query_memory(query), self.loop
)
memory_str = future.result()
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# self.logger.bind(tag=TAG).info(f"对话记录: {self.dialogue.get_llm_dialogue_with_memory(memory_str)}")
# 使用支持functions的streaming接口
llm_responses = self.llm.response_with_functions(
self.session_id,
self.dialogue.get_llm_dialogue_with_memory(memory_str),
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functions=functions,
)
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except Exception as e:
self.logger.bind(tag=TAG).error(f"LLM 处理出错 {query}: {e}")
return None
self.llm_finish_task = False
text_index = 0
# 处理流式响应
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tool_call_flag = False
function_name = None
function_id = None
function_arguments = ""
content_arguments = ""
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for response in llm_responses:
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content, tools_call = response
if "content" in response:
content = response["content"]
tools_call = None
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if content is not None and len(content) > 0:
content_arguments += content
if not tool_call_flag and content_arguments.startswith("<tool_call>"):
# print("content_arguments", content_arguments)
tool_call_flag = True
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if tools_call is not None:
tool_call_flag = True
if tools_call[0].id is not None:
function_id = tools_call[0].id
if tools_call[0].function.name is not None:
function_name = tools_call[0].function.name
if tools_call[0].function.arguments is not None:
function_arguments += tools_call[0].function.arguments
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if content is not None and len(content) > 0:
if not tool_call_flag:
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response_message.append(content)
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if self.client_abort:
break
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end_time = time.time()
# self.logger.bind(tag=TAG).debug(f"大模型返回时间: {end_time - start_time} 秒, 生成token={content}")
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# 处理文本分段和TTS逻辑
# 合并当前全部文本并处理未分割部分
full_text = "".join(response_message)
current_text = full_text[processed_chars:] # 从未处理的位置开始
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# 查找最后一个有效标点
punctuations = ("。", ".", "", "?", "", "!", "", ";", "")
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last_punct_pos = -1
number_flag = True
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for punct in punctuations:
pos = current_text.rfind(punct)
prev_char = current_text[pos - 1] if pos - 1 >= 0 else ""
# 如果.前面是数字统一判断为小数
if prev_char.isdigit() and punct == ".":
number_flag = False
if pos > last_punct_pos and number_flag:
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last_punct_pos = pos
# 找到分割点则处理
if last_punct_pos != -1:
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segment_text_raw = current_text[: last_punct_pos + 1]
segment_text = get_string_no_punctuation_or_emoji(
segment_text_raw
)
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if segment_text:
text_index += 1
self.recode_first_last_text(segment_text, text_index)
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future = self.executor.submit(
self.speak_and_play, segment_text, text_index
)
self.tts_queue.put((future, text_index))
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# 更新已处理字符位置
processed_chars += len(segment_text_raw)
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# 处理function call
if tool_call_flag:
bHasError = False
if function_id is None:
a = extract_json_from_string(content_arguments)
if a is not None:
try:
content_arguments_json = json.loads(a)
function_name = content_arguments_json["name"]
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function_arguments = json.dumps(
content_arguments_json["arguments"], ensure_ascii=False
)
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function_id = str(uuid.uuid4().hex)
except Exception as e:
bHasError = True
response_message.append(a)
else:
bHasError = True
response_message.append(content_arguments)
if bHasError:
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self.logger.bind(tag=TAG).error(
f"function call error: {content_arguments}"
)
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if not bHasError:
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response_message.clear()
self.logger.bind(tag=TAG).debug(
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f"function_name={function_name}, function_id={function_id}, function_arguments={function_arguments}"
)
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function_call_data = {
"name": function_name,
"id": function_id,
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"arguments": function_arguments,
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}
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# 处理MCP工具调用
if self.mcp_manager.is_mcp_tool(function_name):
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result = self._handle_mcp_tool_call(function_call_data)
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else:
# 处理系统函数
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result = self.func_handler.handle_llm_function_call(
self, function_call_data
)
self._handle_function_result(result, function_call_data, text_index + 1)
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# 处理最后剩余的文本
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full_text = "".join(response_message)
remaining_text = full_text[processed_chars:]
if remaining_text:
segment_text = get_string_no_punctuation_or_emoji(remaining_text)
if segment_text:
text_index += 1
self.recode_first_last_text(segment_text, text_index)
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future = self.executor.submit(
self.speak_and_play, segment_text, text_index
)
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self.tts_queue.put((future, text_index))
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# 存储对话内容
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if len(response_message) > 0:
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self.dialogue.put(
Message(role="assistant", content="".join(response_message))
)
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self.llm_finish_task = True
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self.logger.bind(tag=TAG).debug(
json.dumps(self.dialogue.get_llm_dialogue(), indent=4, ensure_ascii=False)
)
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return True
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def _handle_mcp_tool_call(self, function_call_data):
function_arguments = function_call_data["arguments"]
function_name = function_call_data["name"]
try:
args_dict = function_arguments
if isinstance(function_arguments, str):
try:
args_dict = json.loads(function_arguments)
except json.JSONDecodeError:
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self.logger.bind(tag=TAG).error(
f"无法解析 function_arguments: {function_arguments}"
)
return ActionResponse(
action=Action.REQLLM, result="参数解析失败", response=""
)
tool_result = asyncio.run_coroutine_threadsafe(
self.mcp_manager.execute_tool(function_name, args_dict), self.loop
).result()
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# meta=None content=[TextContent(type='text', text='北京当前天气:\n温度: 21°C\n天气: 晴\n湿度: 6%\n风向: 西北 风\n风力等级: 5级', annotations=None)] isError=False
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content_text = ""
if tool_result is not None and tool_result.content is not None:
for content in tool_result.content:
content_type = content.type
if content_type == "text":
content_text = content.text
elif content_type == "image":
pass
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if len(content_text) > 0:
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return ActionResponse(
action=Action.REQLLM, result=content_text, response=""
)
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except Exception as e:
self.logger.bind(tag=TAG).error(f"MCP工具调用错误: {e}")
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return ActionResponse(
action=Action.REQLLM, result="工具调用出错", response=""
)
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return ActionResponse(action=Action.REQLLM, result="工具调用出错", response="")
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def _handle_function_result(self, result, function_call_data, text_index):
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if result.action == Action.RESPONSE: # 直接回复前端
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text = result.response
self.recode_first_last_text(text, text_index)
future = self.executor.submit(self.speak_and_play, text, text_index)
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self.tts_queue.put((future, text_index))
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self.dialogue.put(Message(role="assistant", content=text))
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elif result.action == Action.REQLLM: # 调用函数后再请求llm生成回复
text = result.result
if text is not None and len(text) > 0:
function_id = function_call_data["id"]
function_name = function_call_data["name"]
function_arguments = function_call_data["arguments"]
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self.dialogue.put(
Message(
role="assistant",
tool_calls=[
{
"id": function_id,
"function": {
"arguments": function_arguments,
"name": function_name,
},
"type": "function",
"index": 0,
}
],
)
)
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self.dialogue.put(
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Message(
role="tool",
tool_call_id=(
str(uuid.uuid4()) if function_id is None else function_id
),
content=text,
)
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)
self.chat_with_function_calling(text, tool_call=True)
elif result.action == Action.NOTFOUND or result.action == Action.ERROR:
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text = result.result
self.recode_first_last_text(text, text_index)
future = self.executor.submit(self.speak_and_play, text, text_index)
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self.tts_queue.put((future, text_index))
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self.dialogue.put(Message(role="assistant", content=text))
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else:
pass
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def _tts_priority_thread(self):
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while not self.stop_event.is_set():
text = None
try:
try:
item = self.tts_queue.get(timeout=1)
if item is None:
continue
future, text_index = item # 解包获取 Future 和 text_index
except queue.Empty:
if self.stop_event.is_set():
break
continue
if future is None:
continue
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text = None
audio_datas, tts_file = [], None
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try:
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self.logger.bind(tag=TAG).debug("正在处理TTS任务...")
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tts_timeout = int(self.config.get("tts_timeout", 10))
tts_file, text, _ = future.result(timeout=tts_timeout)
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if text is None or len(text) <= 0:
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self.logger.bind(tag=TAG).error(
f"TTS出错:{text_index}: tts text is empty"
)
elif tts_file is None:
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self.logger.bind(tag=TAG).error(
f"TTS出错: file is empty: {text_index}: {text}"
)
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else:
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self.logger.bind(tag=TAG).debug(
f"TTS生成:文件路径: {tts_file}"
)
if os.path.exists(tts_file):
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if self.audio_format == "pcm":
audio_datas, _ = self.tts.audio_to_pcm_data(tts_file)
else:
audio_datas, _ = self.tts.audio_to_opus_data(tts_file)
# 在这里上报TTS数据
enqueue_tts_report(self, text, audio_datas)
else:
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self.logger.bind(tag=TAG).error(
f"TTS出错:文件不存在{tts_file}"
)
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except TimeoutError:
self.logger.bind(tag=TAG).error("TTS超时")
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except Exception as e:
self.logger.bind(tag=TAG).error(f"TTS出错: {e}")
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if not self.client_abort:
# 如果没有中途打断就发送语音
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self.audio_play_queue.put((audio_datas, text, text_index))
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if (
self.tts.delete_audio_file
and tts_file is not None
and os.path.exists(tts_file)
):
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os.remove(tts_file)
except Exception as e:
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self.logger.bind(tag=TAG).error(f"TTS任务处理错误: {e}")
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self.clearSpeakStatus()
asyncio.run_coroutine_threadsafe(
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self.websocket.send(
json.dumps(
{
"type": "tts",
"state": "stop",
"session_id": self.session_id,
}
)
),
self.loop,
)
self.logger.bind(tag=TAG).error(
f"tts_priority priority_thread: {text} {e}"
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)
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def _audio_play_priority_thread(self):
while not self.stop_event.is_set():
text = None
try:
try:
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audio_datas, text, text_index = self.audio_play_queue.get(timeout=1)
except queue.Empty:
if self.stop_event.is_set():
break
continue
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future = asyncio.run_coroutine_threadsafe(
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sendAudioMessage(self, audio_datas, text, text_index), self.loop
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)
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future.result()
except Exception as e:
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self.logger.bind(tag=TAG).error(
f"audio_play_priority priority_thread: {text} {e}"
)
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def _report_worker(self):
"""聊天记录上报工作线程"""
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while not self.stop_event.is_set():
try:
# 从队列获取数据,设置超时以便定期检查停止事件
item = self.report_queue.get(timeout=1)
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if item is None: # 检测毒丸对象
break
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type, text, audio_data = item
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try:
# 执行上报(传入二进制数据)
report(self, type, text, audio_data)
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except Exception as e:
self.logger.bind(tag=TAG).error(f"聊天记录上报线程异常: {e}")
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finally:
# 标记任务完成
self.report_queue.task_done()
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except queue.Empty:
continue
except Exception as e:
self.logger.bind(tag=TAG).error(f"聊天记录上报工作线程异常: {e}")
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self.logger.bind(tag=TAG).info("聊天记录上报线程已退出")
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def speak_and_play(self, text, text_index=0):
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if text is None or len(text) <= 0:
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self.logger.bind(tag=TAG).info(f"无需tts转换,query为空,{text}")
return None, text, text_index
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tts_file = self.tts.to_tts(text)
if tts_file is None:
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self.logger.bind(tag=TAG).error(f"tts转换失败,{text}")
return None, text, text_index
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self.logger.bind(tag=TAG).debug(f"TTS 文件生成完毕: {tts_file}")
if self.max_output_size > 0:
add_device_output(self.headers.get("device-id"), len(text))
return tts_file, text, text_index
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def clearSpeakStatus(self):
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self.logger.bind(tag=TAG).debug(f"清除服务端讲话状态")
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self.asr_server_receive = True
self.tts_last_text_index = -1
self.tts_first_text_index = -1
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def recode_first_last_text(self, text, text_index=0):
if self.tts_first_text_index == -1:
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self.logger.bind(tag=TAG).info(f"大模型说出第一句话: {text}")
self.tts_first_text_index = text_index
self.tts_last_text_index = text_index
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async def close(self, ws=None):
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"""资源清理方法"""
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# 取消超时任务
if self.timeout_task:
self.timeout_task.cancel()
self.timeout_task = None
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# 清理MCP资源
if hasattr(self, "mcp_manager") and self.mcp_manager:
await self.mcp_manager.cleanup_all()
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# 触发停止事件
if self.stop_event:
self.stop_event.set()
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# 清空任务队列
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self.clear_queues()
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# 关闭WebSocket连接
if ws:
await ws.close()
elif self.websocket:
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await self.websocket.close()
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# 最后关闭线程池(避免阻塞)
if self.executor:
self.executor.shutdown(wait=False)
self.executor = None
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self.logger.bind(tag=TAG).info("连接资源已释放")
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def clear_queues(self):
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"""清空所有任务队列"""
self.logger.bind(tag=TAG).debug(
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f"开始清理: TTS队列大小={self.tts_queue.qsize()}, 音频队列大小={self.audio_play_queue.qsize()}"
)
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# 使用非阻塞方式清空队列
for q in [self.tts_queue, self.audio_play_queue]:
if not q:
continue
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while True:
try:
q.get_nowait()
except queue.Empty:
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break
self.logger.bind(tag=TAG).debug(
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f"清理结束: TTS队列大小={self.tts_queue.qsize()}, 音频队列大小={self.audio_play_queue.qsize()}"
)
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def reset_vad_states(self):
self.client_audio_buffer = bytearray()
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self.client_have_voice = False
self.client_have_voice_last_time = 0
self.client_voice_stop = False
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self.logger.bind(tag=TAG).debug("VAD states reset.")
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def chat_and_close(self, text):
"""Chat with the user and then close the connection"""
try:
# Use the existing chat method
self.chat(text)
# After chat is complete, close the connection
self.close_after_chat = True
except Exception as e:
self.logger.bind(tag=TAG).error(f"Chat and close error: {str(e)}")
async def _check_timeout(self):
"""检查连接超时"""
try:
while not self.stop_event.is_set():
await asyncio.sleep(self.timeout_seconds)
if not self.stop_event.is_set():
self.logger.bind(tag=TAG).info("连接超时,准备关闭")
await self.close(self.websocket)
break
except Exception as e:
self.logger.bind(tag=TAG).error(f"超时检查任务出错: {e}")
def filter_sensitive_info(config: dict) -> dict:
"""
过滤配置中的敏感信息
Args:
config: 原始配置字典
Returns:
过滤后的配置字典
"""
sensitive_keys = [
"api_key",
"personal_access_token",
"access_token",
"token",
"secret",
"access_key_secret",
"secret_key",
]
def _filter_dict(d: dict) -> dict:
filtered = {}
for k, v in d.items():
if any(sensitive in k.lower() for sensitive in sensitive_keys):
filtered[k] = "***"
elif isinstance(v, dict):
filtered[k] = _filter_dict(v)
elif isinstance(v, list):
filtered[k] = [_filter_dict(i) if isinstance(i, dict) else i for i in v]
else:
filtered[k] = v
return filtered
return _filter_dict(copy.deepcopy(config))