939 lines
36 KiB
Python
939 lines
36 KiB
Python
import os
|
||
import copy
|
||
import json
|
||
import uuid
|
||
import time
|
||
import queue
|
||
import asyncio
|
||
import traceback
|
||
|
||
import threading
|
||
import websockets
|
||
from typing import Dict, Any
|
||
from plugins_func.loadplugins import auto_import_modules
|
||
from config.logger import setup_logging
|
||
from core.utils.dialogue import Message, Dialogue
|
||
from core.handle.textHandle import handleTextMessage
|
||
from core.utils.util import (
|
||
get_string_no_punctuation_or_emoji,
|
||
extract_json_from_string,
|
||
get_ip_info,
|
||
initialize_modules,
|
||
)
|
||
from concurrent.futures import ThreadPoolExecutor, TimeoutError
|
||
from core.handle.sendAudioHandle import sendAudioMessage
|
||
from core.handle.receiveAudioHandle import handleAudioMessage
|
||
from core.handle.functionHandler import FunctionHandler
|
||
from plugins_func.register import Action, ActionResponse
|
||
from core.auth import AuthMiddleware, AuthenticationError
|
||
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
|
||
|
||
TAG = __name__
|
||
|
||
auto_import_modules("plugins_func.functions")
|
||
|
||
|
||
class TTSException(RuntimeError):
|
||
pass
|
||
|
||
|
||
class ConnectionHandler:
|
||
def __init__(
|
||
self, config: Dict[str, Any], _vad, _asr, _llm, _tts, _memory, _intent
|
||
):
|
||
self.config = copy.deepcopy(config)
|
||
self.logger = setup_logging()
|
||
self.auth = AuthMiddleware(config)
|
||
|
||
self.need_bind = False
|
||
self.bind_code = None
|
||
|
||
self.websocket = None
|
||
self.headers = None
|
||
self.client_ip = None
|
||
self.client_ip_info = {}
|
||
self.session_id = None
|
||
self.prompt = None
|
||
self.welcome_msg = None
|
||
self.max_output_size = 0
|
||
|
||
# 客户端状态相关
|
||
self.client_abort = False
|
||
self.client_listen_mode = "auto"
|
||
|
||
# 线程任务相关
|
||
self.loop = asyncio.get_event_loop()
|
||
self.stop_event = threading.Event()
|
||
self.tts_queue = queue.Queue()
|
||
self.audio_play_queue = queue.Queue()
|
||
self.executor = ThreadPoolExecutor(max_workers=10)
|
||
|
||
# 依赖的组件
|
||
self.vad = _vad
|
||
self.asr = _asr
|
||
self.llm = _llm
|
||
self.tts = _tts
|
||
self.memory = _memory
|
||
self.intent = _intent
|
||
|
||
# vad相关变量
|
||
self.client_audio_buffer = bytearray()
|
||
self.client_have_voice = False
|
||
self.client_have_voice_last_time = 0.0
|
||
self.client_no_voice_last_time = 0.0
|
||
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
|
||
|
||
# iot相关变量
|
||
self.iot_descriptors = {}
|
||
self.func_handler = None
|
||
|
||
self.cmd_exit = self.config["exit_commands"]
|
||
self.max_cmd_length = 0
|
||
for cmd in self.cmd_exit:
|
||
if len(cmd) > self.max_cmd_length:
|
||
self.max_cmd_length = len(cmd)
|
||
|
||
self.close_after_chat = False # 是否在聊天结束后关闭连接
|
||
self.use_function_call_mode = False
|
||
|
||
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
|
||
|
||
async def handle_connection(self, ws):
|
||
try:
|
||
# 获取并验证headers
|
||
self.headers = dict(ws.request.headers)
|
||
|
||
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:
|
||
self.logger.bind(tag=TAG).error(
|
||
"无法从请求头和URL查询参数中获取device-id"
|
||
)
|
||
return
|
||
|
||
# 获取客户端ip地址
|
||
self.client_ip = ws.remote_address[0]
|
||
self.logger.bind(tag=TAG).info(
|
||
f"{self.client_ip} conn - Headers: {self.headers}"
|
||
)
|
||
|
||
# 进行认证
|
||
await self.auth.authenticate(self.headers)
|
||
|
||
# 认证通过,继续处理
|
||
self.websocket = ws
|
||
self.session_id = str(uuid.uuid4())
|
||
|
||
# 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
|
||
private_config = self._initialize_private_config()
|
||
# 异步初始化
|
||
self.executor.submit(self._initialize_components, private_config)
|
||
# tts 消化线程
|
||
self.tts_priority_thread = threading.Thread(
|
||
target=self._tts_priority_thread, daemon=True
|
||
)
|
||
self.tts_priority_thread.start()
|
||
|
||
# 音频播放 消化线程
|
||
self.audio_play_priority_thread = threading.Thread(
|
||
target=self._audio_play_priority_thread, daemon=True
|
||
)
|
||
self.audio_play_priority_thread.start()
|
||
|
||
try:
|
||
async for message in self.websocket:
|
||
await self._route_message(message)
|
||
except websockets.exceptions.ConnectionClosed:
|
||
self.logger.bind(tag=TAG).info("客户端断开连接")
|
||
|
||
except AuthenticationError as e:
|
||
self.logger.bind(tag=TAG).error(f"Authentication failed: {str(e)}")
|
||
return
|
||
except Exception as e:
|
||
stack_trace = traceback.format_exc()
|
||
self.logger.bind(tag=TAG).error(f"Connection error: {str(e)}-{stack_trace}")
|
||
return
|
||
finally:
|
||
await self._save_and_close(ws)
|
||
|
||
async def _save_and_close(self, ws):
|
||
"""保存记忆并关闭连接"""
|
||
try:
|
||
await self.memory.save_memory(self.dialogue.dialogue)
|
||
except Exception as e:
|
||
self.logger.bind(tag=TAG).error(f"保存记忆失败: {e}")
|
||
finally:
|
||
await self.close(ws)
|
||
|
||
async def _route_message(self, message):
|
||
"""消息路由"""
|
||
# 重置超时计时器
|
||
if self.timeout_task:
|
||
self.timeout_task.cancel()
|
||
self.timeout_task = asyncio.create_task(self._check_timeout())
|
||
|
||
if isinstance(message, str):
|
||
await handleTextMessage(self, message)
|
||
elif isinstance(message, bytes):
|
||
await handleAudioMessage(self, message)
|
||
|
||
def _initialize_components(self, private_config):
|
||
"""初始化组件"""
|
||
if private_config is not None:
|
||
self._initialize_models(private_config)
|
||
else:
|
||
self.prompt = self.config["prompt"]
|
||
self.change_system_prompt(self.prompt)
|
||
"""加载记忆"""
|
||
self._initialize_memory()
|
||
"""加载意图识别"""
|
||
self._initialize_intent()
|
||
"""加载位置信息"""
|
||
self.client_ip_info = get_ip_info(self.client_ip, self.logger)
|
||
if self.client_ip_info is not None and "city" in self.client_ip_info:
|
||
self.logger.bind(tag=TAG).info(f"Client ip info: {self.client_ip_info}")
|
||
self.prompt = self.prompt + f"\nuser location:{self.client_ip_info}"
|
||
|
||
self.dialogue.update_system_message(self.prompt)
|
||
|
||
def _initialize_private_config(self):
|
||
read_config_from_api = self.config.get("read_config_from_api", False)
|
||
"""如果是从配置文件获取，则进行二次实例化"""
|
||
if not read_config_from_api:
|
||
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()
|
||
private_config = get_private_config_from_api(
|
||
self.config,
|
||
self.headers.get("device-id"),
|
||
self.headers.get("client-id", self.headers.get("device-id")),
|
||
)
|
||
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: {private_config}"
|
||
)
|
||
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 = {}
|
||
except Exception as e:
|
||
self.need_bind = True
|
||
self.logger.bind(tag=TAG).error(f"获取差异化配置失败: {e}")
|
||
private_config = {}
|
||
|
||
init_tts = False
|
||
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"
|
||
]
|
||
|
||
try:
|
||
modules = initialize_modules(
|
||
self.logger,
|
||
private_config,
|
||
False,
|
||
False,
|
||
False,
|
||
init_tts,
|
||
False,
|
||
False,
|
||
)
|
||
except Exception as e:
|
||
self.logger.bind(tag=TAG).error(f"初始化组件失败: {e}")
|
||
modules = {}
|
||
if modules.get("tts", None) is not None:
|
||
self.tts = modules["tts"]
|
||
if modules.get("prompt", None) is not None:
|
||
self.change_system_prompt(modules["prompt"])
|
||
private_config["prompt"] = None
|
||
return private_config
|
||
|
||
def _initialize_models(self, private_config):
|
||
init_vad, init_asr, init_llm, init_memory, init_intent = (
|
||
False,
|
||
False,
|
||
False,
|
||
False,
|
||
False,
|
||
)
|
||
if private_config.get("VAD", None) is not None:
|
||
init_vad = True
|
||
self.config["VAD"] = private_config["VAD"]
|
||
self.config["selected_module"]["VAD"] = private_config["selected_module"][
|
||
"VAD"
|
||
]
|
||
if private_config.get("ASR", None) is not None:
|
||
init_asr = True
|
||
self.config["ASR"] = private_config["ASR"]
|
||
self.config["selected_module"]["ASR"] = private_config["selected_module"][
|
||
"ASR"
|
||
]
|
||
if private_config.get("LLM", None) is not None:
|
||
init_llm = True
|
||
self.config["LLM"] = private_config["LLM"]
|
||
self.config["selected_module"]["LLM"] = private_config["selected_module"][
|
||
"LLM"
|
||
]
|
||
if private_config.get("Memory", None) is not None:
|
||
init_memory = True
|
||
self.config["Memory"] = private_config["Memory"]
|
||
self.config["selected_module"]["Memory"] = private_config[
|
||
"selected_module"
|
||
]["Memory"]
|
||
if private_config.get("Intent", None) is not None:
|
||
init_intent = True
|
||
self.config["Intent"] = private_config["Intent"]
|
||
self.config["selected_module"]["Intent"] = private_config[
|
||
"selected_module"
|
||
]["Intent"]
|
||
if private_config.get("device_max_output_size", None) is not None:
|
||
self.max_output_size = int(private_config["device_max_output_size"])
|
||
try:
|
||
modules = initialize_modules(
|
||
self.logger,
|
||
private_config,
|
||
init_vad,
|
||
init_asr,
|
||
init_llm,
|
||
False,
|
||
init_memory,
|
||
init_intent,
|
||
)
|
||
except Exception as e:
|
||
self.logger.bind(tag=TAG).error(f"初始化组件失败: {e}")
|
||
modules = {}
|
||
if modules.get("vad", None) is not None:
|
||
self.vad = modules["vad"]
|
||
if modules.get("asr", None) is not None:
|
||
self.asr = modules["asr"]
|
||
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"""
|
||
device_id = self.headers.get("device-id", None)
|
||
self.memory.init_memory(device_id, self.llm)
|
||
|
||
def _initialize_intent(self):
|
||
if (
|
||
self.config["Intent"][self.config["selected_module"]["Intent"]]["type"]
|
||
== "function_call"
|
||
):
|
||
self.use_function_call_mode = True
|
||
"""初始化意图识别模块"""
|
||
# 获取意图识别配置
|
||
intent_config = self.config["Intent"]
|
||
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":
|
||
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)
|
||
|
||
"""加载MCP工具"""
|
||
asyncio.run_coroutine_threadsafe(
|
||
self.mcp_manager.initialize_servers(), self.loop
|
||
)
|
||
|
||
def change_system_prompt(self, prompt):
|
||
self.prompt = prompt
|
||
# 更新系统prompt至上下文
|
||
self.dialogue.update_system_message(self.prompt)
|
||
|
||
def chat(self, query):
|
||
|
||
self.dialogue.put(Message(role="user", content=query))
|
||
|
||
response_message = []
|
||
processed_chars = 0 # 跟踪已处理的字符位置
|
||
try:
|
||
# 使用带记忆的对话
|
||
future = asyncio.run_coroutine_threadsafe(
|
||
self.memory.query_memory(query), self.loop
|
||
)
|
||
memory_str = future.result()
|
||
|
||
self.logger.bind(tag=TAG).debug(f"记忆内容: {memory_str}")
|
||
llm_responses = self.llm.response(
|
||
self.session_id, self.dialogue.get_llm_dialogue_with_memory(memory_str)
|
||
)
|
||
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
|
||
for content in llm_responses:
|
||
response_message.append(content)
|
||
if self.client_abort:
|
||
break
|
||
|
||
# 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 = ("。", "？", "！", "；", "：")
|
||
last_punct_pos = -1
|
||
for punct in punctuations:
|
||
pos = current_text.rfind(punct)
|
||
if pos > last_punct_pos:
|
||
last_punct_pos = pos
|
||
|
||
# 找到分割点则处理
|
||
if last_punct_pos != -1:
|
||
segment_text_raw = current_text[: last_punct_pos + 1]
|
||
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)
|
||
future = self.executor.submit(
|
||
self.speak_and_play, segment_text, text_index
|
||
)
|
||
self.tts_queue.put(future)
|
||
processed_chars += len(segment_text_raw) # 更新已处理字符位置
|
||
|
||
# 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)
|
||
future = self.executor.submit(
|
||
self.speak_and_play, segment_text, text_index
|
||
)
|
||
self.tts_queue.put(future)
|
||
|
||
self.llm_finish_task = True
|
||
self.dialogue.put(Message(role="assistant", content="".join(response_message)))
|
||
self.logger.bind(tag=TAG).debug(
|
||
json.dumps(self.dialogue.get_llm_dialogue(), indent=4, ensure_ascii=False)
|
||
)
|
||
return True
|
||
|
||
def chat_with_function_calling(self, query, tool_call=False):
|
||
self.logger.bind(tag=TAG).debug(f"Chat with function calling start: {query}")
|
||
"""Chat with function calling for intent detection using streaming"""
|
||
|
||
if not tool_call:
|
||
self.dialogue.put(Message(role="user", content=query))
|
||
|
||
# Define intent functions
|
||
functions = None
|
||
if hasattr(self, "func_handler"):
|
||
functions = self.func_handler.get_functions()
|
||
response_message = []
|
||
processed_chars = 0 # 跟踪已处理的字符位置
|
||
|
||
try:
|
||
start_time = time.time()
|
||
|
||
# 使用带记忆的对话
|
||
future = asyncio.run_coroutine_threadsafe(
|
||
self.memory.query_memory(query), self.loop
|
||
)
|
||
memory_str = future.result()
|
||
|
||
# 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),
|
||
functions=functions,
|
||
)
|
||
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
|
||
tool_call_flag = False
|
||
function_name = None
|
||
function_id = None
|
||
function_arguments = ""
|
||
content_arguments = ""
|
||
|
||
for response in llm_responses:
|
||
content, tools_call = response
|
||
|
||
if "content" in response:
|
||
content = response["content"]
|
||
tools_call = None
|
||
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
|
||
|
||
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
|
||
|
||
if content is not None and len(content) > 0:
|
||
if not tool_call_flag:
|
||
response_message.append(content)
|
||
|
||
if self.client_abort:
|
||
break
|
||
|
||
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}")
|
||
|
||
# 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
|
||
|
||
# 查找最后一个有效标点
|
||
punctuations = ("。", "？", "！", "；", "：")
|
||
last_punct_pos = -1
|
||
for punct in punctuations:
|
||
pos = current_text.rfind(punct)
|
||
if pos > last_punct_pos:
|
||
last_punct_pos = pos
|
||
|
||
# 找到分割点则处理
|
||
if last_punct_pos != -1:
|
||
segment_text_raw = current_text[: last_punct_pos + 1]
|
||
segment_text = get_string_no_punctuation_or_emoji(
|
||
segment_text_raw
|
||
)
|
||
if segment_text:
|
||
text_index += 1
|
||
self.recode_first_last_text(segment_text, text_index)
|
||
future = self.executor.submit(
|
||
self.speak_and_play, segment_text, text_index
|
||
)
|
||
self.tts_queue.put(future)
|
||
# 更新已处理字符位置
|
||
processed_chars += len(segment_text_raw)
|
||
|
||
# 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"]
|
||
function_arguments = json.dumps(
|
||
content_arguments_json["arguments"], ensure_ascii=False
|
||
)
|
||
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:
|
||
self.logger.bind(tag=TAG).error(
|
||
f"function call error: {content_arguments}"
|
||
)
|
||
if not bHasError:
|
||
response_message.clear()
|
||
self.logger.bind(tag=TAG).debug(
|
||
f"function_name={function_name}, function_id={function_id}, function_arguments={function_arguments}"
|
||
)
|
||
function_call_data = {
|
||
"name": function_name,
|
||
"id": function_id,
|
||
"arguments": function_arguments,
|
||
}
|
||
|
||
# 处理MCP工具调用
|
||
if self.mcp_manager.is_mcp_tool(function_name):
|
||
result = self._handle_mcp_tool_call(function_call_data)
|
||
else:
|
||
# 处理系统函数
|
||
result = self.func_handler.handle_llm_function_call(
|
||
self, function_call_data
|
||
)
|
||
self._handle_function_result(result, function_call_data, text_index + 1)
|
||
|
||
# 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)
|
||
future = self.executor.submit(
|
||
self.speak_and_play, segment_text, text_index
|
||
)
|
||
self.tts_queue.put(future)
|
||
|
||
# 存储对话内容
|
||
if len(response_message) > 0:
|
||
self.dialogue.put(
|
||
Message(role="assistant", content="".join(response_message))
|
||
)
|
||
|
||
self.llm_finish_task = True
|
||
self.logger.bind(tag=TAG).debug(
|
||
json.dumps(self.dialogue.get_llm_dialogue(), indent=4, ensure_ascii=False)
|
||
)
|
||
|
||
return True
|
||
|
||
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:
|
||
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()
|
||
# 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
|
||
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
|
||
|
||
if len(content_text) > 0:
|
||
return ActionResponse(
|
||
action=Action.REQLLM, result=content_text, response=""
|
||
)
|
||
|
||
except Exception as e:
|
||
self.logger.bind(tag=TAG).error(f"MCP工具调用错误: {e}")
|
||
return ActionResponse(
|
||
action=Action.REQLLM, result="工具调用出错", response=""
|
||
)
|
||
|
||
return ActionResponse(action=Action.REQLLM, result="工具调用出错", response="")
|
||
|
||
def _handle_function_result(self, result, function_call_data, text_index):
|
||
if result.action == Action.RESPONSE: # 直接回复前端
|
||
text = result.response
|
||
self.recode_first_last_text(text, text_index)
|
||
future = self.executor.submit(self.speak_and_play, text, text_index)
|
||
self.tts_queue.put(future)
|
||
self.dialogue.put(Message(role="assistant", content=text))
|
||
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"]
|
||
self.dialogue.put(
|
||
Message(
|
||
role="assistant",
|
||
tool_calls=[
|
||
{
|
||
"id": function_id,
|
||
"function": {
|
||
"arguments": function_arguments,
|
||
"name": function_name,
|
||
},
|
||
"type": "function",
|
||
"index": 0,
|
||
}
|
||
],
|
||
)
|
||
)
|
||
|
||
self.dialogue.put(
|
||
Message(role="tool", tool_call_id=function_id, content=text)
|
||
)
|
||
self.chat_with_function_calling(text, tool_call=True)
|
||
elif result.action == Action.NOTFOUND or result.action == Action.ERROR:
|
||
text = result.result
|
||
self.recode_first_last_text(text, text_index)
|
||
future = self.executor.submit(self.speak_and_play, text, text_index)
|
||
self.tts_queue.put(future)
|
||
self.dialogue.put(Message(role="assistant", content=text))
|
||
else:
|
||
pass
|
||
|
||
def _tts_priority_thread(self):
|
||
while not self.stop_event.is_set():
|
||
text = None
|
||
try:
|
||
try:
|
||
future = self.tts_queue.get(timeout=1)
|
||
except queue.Empty:
|
||
if self.stop_event.is_set():
|
||
break
|
||
continue
|
||
if future is None:
|
||
continue
|
||
text = None
|
||
opus_datas, text_index, tts_file = [], 0, None
|
||
try:
|
||
self.logger.bind(tag=TAG).debug("正在处理TTS任务...")
|
||
tts_timeout = int(self.config.get("tts_timeout", 10))
|
||
tts_file, text, text_index = future.result(timeout=tts_timeout)
|
||
if text is None or len(text) <= 0:
|
||
self.logger.bind(tag=TAG).error(
|
||
f"TTS出错：{text_index}: tts text is empty"
|
||
)
|
||
elif tts_file is None:
|
||
self.logger.bind(tag=TAG).error(
|
||
f"TTS出错： file is empty: {text_index}: {text}"
|
||
)
|
||
else:
|
||
self.logger.bind(tag=TAG).debug(
|
||
f"TTS生成：文件路径: {tts_file}"
|
||
)
|
||
if os.path.exists(tts_file):
|
||
opus_datas, duration = self.tts.audio_to_opus_data(tts_file)
|
||
else:
|
||
self.logger.bind(tag=TAG).error(
|
||
f"TTS出错：文件不存在{tts_file}"
|
||
)
|
||
except TimeoutError:
|
||
self.logger.bind(tag=TAG).error("TTS超时")
|
||
except Exception as e:
|
||
self.logger.bind(tag=TAG).error(f"TTS出错: {e}")
|
||
if not self.client_abort:
|
||
# 如果没有中途打断就发送语音
|
||
self.audio_play_queue.put((opus_datas, text, text_index))
|
||
if (
|
||
self.tts.delete_audio_file
|
||
and tts_file is not None
|
||
and os.path.exists(tts_file)
|
||
):
|
||
os.remove(tts_file)
|
||
except Exception as e:
|
||
self.logger.bind(tag=TAG).error(f"TTS任务处理错误: {e}")
|
||
self.clearSpeakStatus()
|
||
asyncio.run_coroutine_threadsafe(
|
||
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}"
|
||
)
|
||
|
||
def _audio_play_priority_thread(self):
|
||
while not self.stop_event.is_set():
|
||
text = None
|
||
try:
|
||
try:
|
||
opus_datas, text, text_index = self.audio_play_queue.get(timeout=1)
|
||
except queue.Empty:
|
||
if self.stop_event.is_set():
|
||
break
|
||
continue
|
||
future = asyncio.run_coroutine_threadsafe(
|
||
sendAudioMessage(self, opus_datas, text, text_index), self.loop
|
||
)
|
||
future.result()
|
||
except Exception as e:
|
||
self.logger.bind(tag=TAG).error(
|
||
f"audio_play_priority priority_thread: {text} {e}"
|
||
)
|
||
|
||
def speak_and_play(self, text, text_index=0):
|
||
if text is None or len(text) <= 0:
|
||
self.logger.bind(tag=TAG).info(f"无需tts转换，query为空，{text}")
|
||
return None, text, text_index
|
||
tts_file = self.tts.to_tts(text)
|
||
if tts_file is None:
|
||
self.logger.bind(tag=TAG).error(f"tts转换失败，{text}")
|
||
return None, text, text_index
|
||
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
|
||
|
||
def clearSpeakStatus(self):
|
||
self.logger.bind(tag=TAG).debug(f"清除服务端讲话状态")
|
||
self.asr_server_receive = True
|
||
self.tts_last_text_index = -1
|
||
self.tts_first_text_index = -1
|
||
|
||
def recode_first_last_text(self, text, text_index=0):
|
||
if self.tts_first_text_index == -1:
|
||
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
|
||
|
||
async def close(self, ws=None):
|
||
"""资源清理方法"""
|
||
# 取消超时任务
|
||
if self.timeout_task:
|
||
self.timeout_task.cancel()
|
||
self.timeout_task = None
|
||
|
||
# 清理MCP资源
|
||
if hasattr(self, "mcp_manager") and self.mcp_manager:
|
||
await self.mcp_manager.cleanup_all()
|
||
|
||
# 触发停止事件并清理资源
|
||
if self.stop_event:
|
||
self.stop_event.set()
|
||
|
||
# 立即关闭线程池
|
||
if self.executor:
|
||
self.executor.shutdown(wait=False, cancel_futures=True)
|
||
self.executor = None
|
||
|
||
# 清空任务队列
|
||
self._clear_queues()
|
||
|
||
if ws:
|
||
await ws.close()
|
||
elif self.websocket:
|
||
await self.websocket.close()
|
||
self.logger.bind(tag=TAG).info("连接资源已释放")
|
||
|
||
def _clear_queues(self):
|
||
# 清空所有任务队列
|
||
for q in [self.tts_queue, self.audio_play_queue]:
|
||
if not q:
|
||
continue
|
||
while not q.empty():
|
||
try:
|
||
q.get_nowait()
|
||
except queue.Empty:
|
||
continue
|
||
q.queue.clear()
|
||
# 添加毒丸信号到队列，确保线程退出
|
||
# q.queue.put(None)
|
||
|
||
def reset_vad_states(self):
|
||
self.client_audio_buffer = bytearray()
|
||
self.client_have_voice = False
|
||
self.client_have_voice_last_time = 0
|
||
self.client_voice_stop = False
|
||
self.logger.bind(tag=TAG).debug("VAD states reset.")
|
||
|
||
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}")
|