593 lines
27 KiB
Python
593 lines
27 KiB
Python
import asyncio
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import contextlib
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import time
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import traceback
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from collections import deque
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from typing import List, Optional, Dict, Any, Deque, Callable, Awaitable
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from src.chat.message_receive.chat_stream import get_chat_manager
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from rich.traceback import install
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from src.chat.utils.prompt_builder import global_prompt_manager
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from src.common.logger import get_logger
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from src.chat.utils.timer_calculator import Timer
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from src.chat.focus_chat.focus_loop_info import FocusLoopInfo
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from src.chat.planner_actions.planner import ActionPlanner
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from src.chat.planner_actions.action_modifier import ActionModifier
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from src.chat.planner_actions.action_manager import ActionManager
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from src.config.config import global_config
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from src.chat.focus_chat.hfc_performance_logger import HFCPerformanceLogger
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from src.person_info.relationship_builder_manager import relationship_builder_manager
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from src.chat.focus_chat.hfc_utils import CycleDetail
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install(extra_lines=3)
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# 注释：原来的动作修改超时常量已移除，因为改为顺序执行
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logger = get_logger("hfc") # Logger Name Changed
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class HeartFChatting:
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"""
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管理一个连续的Focus Chat循环
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用于在特定聊天流中生成回复。
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其生命周期现在由其关联的 SubHeartflow 的 FOCUSED 状态控制。
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"""
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def __init__(
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self,
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chat_id: str,
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on_stop_focus_chat: Optional[Callable[[], Awaitable[None]]] = None,
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):
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"""
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HeartFChatting 初始化函数
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参数:
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chat_id: 聊天流唯一标识符(如stream_id)
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on_stop_focus_chat: 当收到stop_focus_chat命令时调用的回调函数
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performance_version: 性能记录版本号，用于区分不同启动版本
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"""
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# 基础属性
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self.stream_id: str = chat_id # 聊天流ID
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self.chat_stream = get_chat_manager().get_stream(self.stream_id)
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self.log_prefix = f"[{get_chat_manager().get_stream_name(self.stream_id) or self.stream_id}]"
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self.relationship_builder = relationship_builder_manager.get_or_create_builder(self.stream_id)
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# 新增：消息计数器和疲惫阈值
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self._message_count = 0 # 发送的消息计数
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# 基于exit_focus_threshold动态计算疲惫阈值
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# 基础值30条，通过exit_focus_threshold调节：threshold越小，越容易疲惫
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self._message_threshold = max(10, int(30 * global_config.chat.exit_focus_threshold))
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self._fatigue_triggered = False # 是否已触发疲惫退出
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self.loop_info: FocusLoopInfo = FocusLoopInfo(observe_id=self.stream_id)
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self.action_manager = ActionManager()
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self.action_planner = ActionPlanner(chat_id=self.stream_id, action_manager=self.action_manager)
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self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.stream_id)
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self._processing_lock = asyncio.Lock()
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# 循环控制内部状态
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self._loop_active: bool = False # 循环是否正在运行
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self._loop_task: Optional[asyncio.Task] = None # 主循环任务
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# 添加循环信息管理相关的属性
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self._cycle_counter = 0
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self._cycle_history: Deque[CycleDetail] = deque(maxlen=10) # 保留最近10个循环的信息
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self._current_cycle_detail: Optional[CycleDetail] = None
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self._shutting_down: bool = False # 关闭标志位
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# 存储回调函数
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self.on_stop_focus_chat = on_stop_focus_chat
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self.reply_timeout_count = 0
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self.plan_timeout_count = 0
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# 初始化性能记录器
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# 如果没有指定版本号，则使用全局版本管理器的版本号
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self.performance_logger = HFCPerformanceLogger(chat_id)
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logger.info(
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f"{self.log_prefix} HeartFChatting 初始化完成，消息疲惫阈值: {self._message_threshold}条（基于exit_focus_threshold={global_config.chat.exit_focus_threshold}计算，仅在auto模式下生效）"
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)
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async def start(self):
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"""检查是否需要启动主循环，如果未激活则启动。"""
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# 如果循环已经激活，直接返回
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if self._loop_active:
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logger.debug(f"{self.log_prefix} HeartFChatting 已激活，无需重复启动")
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return
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try:
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# 重置消息计数器，开始新的focus会话
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self.reset_message_count()
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# 标记为活动状态，防止重复启动
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self._loop_active = True
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# 检查是否已有任务在运行（理论上不应该，因为 _loop_active=False）
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if self._loop_task and not self._loop_task.done():
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logger.warning(f"{self.log_prefix} 发现之前的循环任务仍在运行（不符合预期）。取消旧任务。")
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self._loop_task.cancel()
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try:
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# 等待旧任务确实被取消
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await asyncio.wait_for(self._loop_task, timeout=5.0)
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except Exception as e:
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logger.warning(f"{self.log_prefix} 等待旧任务取消时出错: {e}")
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self._loop_task = None # 清理旧任务引用
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logger.debug(f"{self.log_prefix} 创建新的 HeartFChatting 主循环任务")
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self._loop_task = asyncio.create_task(self._run_focus_chat())
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self._loop_task.add_done_callback(self._handle_loop_completion)
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logger.debug(f"{self.log_prefix} HeartFChatting 启动完成")
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except Exception as e:
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# 启动失败时重置状态
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self._loop_active = False
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self._loop_task = None
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logger.error(f"{self.log_prefix} HeartFChatting 启动失败: {e}")
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raise
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def _handle_loop_completion(self, task: asyncio.Task):
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"""当 _hfc_loop 任务完成时执行的回调。"""
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try:
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exception = task.exception()
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if exception:
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logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}")
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logger.error(traceback.format_exc()) # Log full traceback for exceptions
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else:
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logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)")
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except asyncio.CancelledError:
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logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天(任务取消)")
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finally:
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self._loop_active = False
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self._loop_task = None
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if self._processing_lock.locked():
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logger.warning(f"{self.log_prefix} HeartFChatting: 处理锁在循环结束时仍被锁定，强制释放。")
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self._processing_lock.release()
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async def _run_focus_chat(self):
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"""主循环，持续进行计划并可能回复消息，直到被外部取消。"""
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try:
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while True: # 主循环
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logger.debug(f"{self.log_prefix} 开始第{self._cycle_counter}次循环")
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# 检查关闭标志
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if self._shutting_down:
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logger.info(f"{self.log_prefix} 检测到关闭标志，退出 Focus Chat 循环。")
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break
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# 创建新的循环信息
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self._cycle_counter += 1
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self._current_cycle_detail = CycleDetail(self._cycle_counter)
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self._current_cycle_detail.prefix = self.log_prefix
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# 初始化周期状态
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cycle_timers = {}
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# 执行规划和处理阶段
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try:
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async with self._get_cycle_context():
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thinking_id = "tid" + str(round(time.time(), 2))
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self._current_cycle_detail.set_thinking_id(thinking_id)
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# 使用异步上下文管理器处理消息
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try:
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async with global_prompt_manager.async_message_scope(
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self.chat_stream.context.get_template_name()
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):
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# 在上下文内部检查关闭状态
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if self._shutting_down:
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logger.info(f"{self.log_prefix} 在处理上下文中检测到关闭信号，退出")
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break
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logger.debug(f"模板 {self.chat_stream.context.get_template_name()}")
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loop_info = await self._observe_process_plan_action_loop(cycle_timers, thinking_id)
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if loop_info["loop_action_info"]["command"] == "stop_focus_chat":
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logger.info(f"{self.log_prefix} 麦麦决定停止专注聊天")
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# 如果是私聊，则不停止，而是重置疲劳度并继续
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if not self.chat_stream.group_info:
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logger.info(f"{self.log_prefix} 私聊模式下收到停止请求，不退出。")
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continue # 继续下一次循环，而不是退出
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# 如果是群聊，则执行原来的停止逻辑
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# 如果设置了回调函数，则调用它
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if self.on_stop_focus_chat:
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try:
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await self.on_stop_focus_chat()
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logger.info(f"{self.log_prefix} 成功调用回调函数处理停止专注聊天")
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except Exception as e:
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logger.error(f"{self.log_prefix} 调用停止专注聊天回调函数时出错: {e}")
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logger.error(traceback.format_exc())
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break
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except asyncio.CancelledError:
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logger.info(f"{self.log_prefix} 处理上下文时任务被取消")
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break
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except Exception as e:
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logger.error(f"{self.log_prefix} 处理上下文时出错: {e}")
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# 为当前循环设置错误状态，防止后续重复报错
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error_loop_info = {
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"loop_plan_info": {
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"action_result": {
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"action_type": "error",
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"action_data": {},
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},
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},
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"loop_action_info": {
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"action_taken": False,
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"reply_text": "",
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"command": "",
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"taken_time": time.time(),
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},
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}
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self._current_cycle_detail.set_loop_info(error_loop_info)
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self._current_cycle_detail.complete_cycle()
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# 上下文处理失败，跳过当前循环
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await asyncio.sleep(1)
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continue
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self._current_cycle_detail.set_loop_info(loop_info)
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self.loop_info.add_loop_info(self._current_cycle_detail)
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self._current_cycle_detail.timers = cycle_timers
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# 完成当前循环并保存历史
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self._current_cycle_detail.complete_cycle()
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self._cycle_history.append(self._current_cycle_detail)
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# 记录循环信息和计时器结果
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timer_strings = []
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for name, elapsed in cycle_timers.items():
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formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
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timer_strings.append(f"{name}: {formatted_time}")
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logger.info(
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f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考,"
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f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒, "
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f"选择动作: {self._current_cycle_detail.loop_plan_info.get('action_result', {}).get('action_type', '未知动作')}"
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+ (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
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)
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# 记录性能数据
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try:
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action_result = self._current_cycle_detail.loop_plan_info.get("action_result", {})
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cycle_performance_data = {
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"cycle_id": self._current_cycle_detail.cycle_id,
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"action_type": action_result.get("action_type", "unknown"),
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"total_time": self._current_cycle_detail.end_time - self._current_cycle_detail.start_time,
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"step_times": cycle_timers.copy(),
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"reasoning": action_result.get("reasoning", ""),
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"success": self._current_cycle_detail.loop_action_info.get("action_taken", False),
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}
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self.performance_logger.record_cycle(cycle_performance_data)
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except Exception as perf_e:
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logger.warning(f"{self.log_prefix} 记录性能数据失败: {perf_e}")
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await asyncio.sleep(global_config.focus_chat.think_interval)
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except asyncio.CancelledError:
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logger.info(f"{self.log_prefix} 循环处理时任务被取消")
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break
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except Exception as e:
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logger.error(f"{self.log_prefix} 循环处理时出错: {e}")
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logger.error(traceback.format_exc())
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# 如果_current_cycle_detail存在但未完成，为其设置错误状态
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if self._current_cycle_detail and not hasattr(self._current_cycle_detail, "end_time"):
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error_loop_info = {
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"loop_plan_info": {
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"action_result": {
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"action_type": "error",
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"action_data": {},
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"reasoning": f"循环处理失败: {e}",
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},
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},
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"loop_action_info": {
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"action_taken": False,
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"reply_text": "",
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"command": "",
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"taken_time": time.time(),
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},
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}
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try:
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self._current_cycle_detail.set_loop_info(error_loop_info)
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self._current_cycle_detail.complete_cycle()
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except Exception as inner_e:
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logger.error(f"{self.log_prefix} 设置错误状态时出错: {inner_e}")
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await asyncio.sleep(1) # 出错后等待一秒再继续
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except asyncio.CancelledError:
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# 设置了关闭标志位后被取消是正常流程
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if not self._shutting_down:
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logger.warning(f"{self.log_prefix} 麦麦Focus聊天模式意外被取消")
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else:
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logger.info(f"{self.log_prefix} 麦麦已离开Focus聊天模式")
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except Exception as e:
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logger.error(f"{self.log_prefix} 麦麦Focus聊天模式意外错误: {e}")
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print(traceback.format_exc())
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@contextlib.asynccontextmanager
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async def _get_cycle_context(self):
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"""
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循环周期的上下文管理器
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用于确保资源的正确获取和释放：
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1. 获取处理锁
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2. 执行操作
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3. 释放锁
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"""
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acquired = False
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try:
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await self._processing_lock.acquire()
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acquired = True
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yield acquired
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finally:
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if acquired and self._processing_lock.locked():
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self._processing_lock.release()
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async def _observe_process_plan_action_loop(self, cycle_timers: dict, thinking_id: str) -> dict:
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try:
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loop_start_time = time.time()
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await self.loop_info.observe()
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await self.relationship_builder.build_relation()
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# 顺序执行调整动作和处理器阶段
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# 第一步：动作修改
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with Timer("动作修改", cycle_timers):
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try:
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# 调用完整的动作修改流程
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await self.action_modifier.modify_actions(
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loop_info=self.loop_info,
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mode="focus",
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)
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except Exception as e:
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logger.error(f"{self.log_prefix} 动作修改失败: {e}")
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# 继续执行，不中断流程
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with Timer("规划器", cycle_timers):
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plan_result = await self.action_planner.plan()
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loop_plan_info = {
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"action_result": plan_result.get("action_result", {}),
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}
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action_type, action_data, reasoning = (
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plan_result.get("action_result", {}).get("action_type", "error"),
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plan_result.get("action_result", {}).get("action_data", {}),
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plan_result.get("action_result", {}).get("reasoning", "未提供理由"),
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)
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action_data["loop_start_time"] = loop_start_time
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if action_type == "reply":
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action_str = "回复"
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elif action_type == "no_reply":
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action_str = "不回复"
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else:
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action_str = action_type
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logger.debug(f"{self.log_prefix} 麦麦想要：'{action_str}'，理由是：{reasoning}")
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# 动作执行计时
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with Timer("动作执行", cycle_timers):
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success, reply_text, command = await self._handle_action(
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action_type, reasoning, action_data, cycle_timers, thinking_id
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)
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loop_action_info = {
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"action_taken": success,
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"reply_text": reply_text,
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"command": command,
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"taken_time": time.time(),
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}
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loop_info = {
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"loop_plan_info": loop_plan_info,
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"loop_action_info": loop_action_info,
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}
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return loop_info
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except Exception as e:
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logger.error(f"{self.log_prefix} FOCUS聊天处理失败: {e}")
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logger.error(traceback.format_exc())
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return {
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"loop_plan_info": {
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"action_result": {"action_type": "error", "action_data": {}, "reasoning": f"处理失败: {e}"},
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},
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"loop_action_info": {"action_taken": False, "reply_text": "", "command": "", "taken_time": time.time()},
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}
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async def _handle_action(
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self,
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action: str,
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reasoning: str,
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action_data: dict,
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cycle_timers: dict,
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thinking_id: str,
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) -> tuple[bool, str, str]:
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"""
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处理规划动作，使用动作工厂创建相应的动作处理器
|
||
|
||
参数:
|
||
action: 动作类型
|
||
reasoning: 决策理由
|
||
action_data: 动作数据，包含不同动作需要的参数
|
||
cycle_timers: 计时器字典
|
||
thinking_id: 思考ID
|
||
|
||
返回:
|
||
tuple[bool, str, str]: (是否执行了动作, 思考消息ID, 命令)
|
||
"""
|
||
try:
|
||
# 使用工厂创建动作处理器实例
|
||
try:
|
||
action_handler = self.action_manager.create_action(
|
||
action_name=action,
|
||
action_data=action_data,
|
||
reasoning=reasoning,
|
||
cycle_timers=cycle_timers,
|
||
thinking_id=thinking_id,
|
||
chat_stream=self.chat_stream,
|
||
log_prefix=self.log_prefix,
|
||
shutting_down=self._shutting_down,
|
||
)
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 创建动作处理器时出错: {e}")
|
||
traceback.print_exc()
|
||
return False, "", ""
|
||
|
||
if not action_handler:
|
||
logger.warning(f"{self.log_prefix} 未能创建动作处理器: {action}")
|
||
return False, "", ""
|
||
|
||
# 处理动作并获取结果
|
||
result = await action_handler.handle_action()
|
||
if len(result) == 3:
|
||
success, reply_text, command = result
|
||
else:
|
||
success, reply_text = result
|
||
command = ""
|
||
|
||
# 检查action_data中是否有系统命令，优先使用系统命令
|
||
if "_system_command" in action_data:
|
||
command = action_data["_system_command"]
|
||
logger.debug(f"{self.log_prefix} 从action_data中获取系统命令: {command}")
|
||
|
||
# 新增：消息计数和疲惫检查
|
||
if action == "reply" and success:
|
||
self._message_count += 1
|
||
current_threshold = self._get_current_fatigue_threshold()
|
||
logger.info(
|
||
f"{self.log_prefix} 已发送第 {self._message_count} 条消息（动态阈值: {current_threshold}, exit_focus_threshold: {global_config.chat.exit_focus_threshold}）"
|
||
)
|
||
|
||
# 检查是否达到疲惫阈值（只有在auto模式下才会自动退出）
|
||
if (
|
||
global_config.chat.chat_mode == "auto"
|
||
and self._message_count >= current_threshold
|
||
and not self._fatigue_triggered
|
||
):
|
||
self._fatigue_triggered = True
|
||
logger.info(
|
||
f"{self.log_prefix} [auto模式] 已发送 {self._message_count} 条消息，达到疲惫阈值 {current_threshold}，麦麦感到疲惫了，准备退出专注聊天模式"
|
||
)
|
||
# 设置系统命令，在下次循环检查时触发退出
|
||
command = "stop_focus_chat"
|
||
elif self._message_count >= current_threshold and global_config.chat.chat_mode != "auto":
|
||
logger.info(
|
||
f"{self.log_prefix} [非auto模式] 已发送 {self._message_count} 条消息，达到疲惫阈值 {current_threshold}，但非auto模式不会自动退出"
|
||
)
|
||
else:
|
||
if reply_text == "timeout":
|
||
self.reply_timeout_count += 1
|
||
if self.reply_timeout_count > 5:
|
||
logger.warning(
|
||
f"[{self.log_prefix} ] 连续回复超时次数过多，{global_config.chat.thinking_timeout}秒 内大模型没有返回有效内容，请检查你的api是否速度过慢或配置错误。建议不要使用推理模型，推理模型生成速度过慢。或者尝试拉高thinking_timeout参数，这可能导致回复时间过长。"
|
||
)
|
||
logger.warning(f"{self.log_prefix} 回复生成超时{global_config.chat.thinking_timeout}s，已跳过")
|
||
return False, "", ""
|
||
|
||
return success, reply_text, command
|
||
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 处理{action}时出错: {e}")
|
||
traceback.print_exc()
|
||
return False, "", ""
|
||
|
||
def _get_current_fatigue_threshold(self) -> int:
|
||
"""动态获取当前的疲惫阈值，基于exit_focus_threshold配置
|
||
|
||
Returns:
|
||
int: 当前的疲惫阈值
|
||
"""
|
||
return max(10, int(30 / global_config.chat.exit_focus_threshold))
|
||
|
||
def get_message_count_info(self) -> dict:
|
||
"""获取消息计数信息
|
||
|
||
Returns:
|
||
dict: 包含消息计数信息的字典
|
||
"""
|
||
current_threshold = self._get_current_fatigue_threshold()
|
||
return {
|
||
"current_count": self._message_count,
|
||
"threshold": current_threshold,
|
||
"fatigue_triggered": self._fatigue_triggered,
|
||
"remaining": max(0, current_threshold - self._message_count),
|
||
}
|
||
|
||
def reset_message_count(self):
|
||
"""重置消息计数器（用于重新启动focus模式时）"""
|
||
self._message_count = 0
|
||
self._fatigue_triggered = False
|
||
logger.info(f"{self.log_prefix} 消息计数器已重置")
|
||
|
||
async def shutdown(self):
|
||
"""优雅关闭HeartFChatting实例，取消活动循环任务"""
|
||
logger.info(f"{self.log_prefix} 正在关闭HeartFChatting...")
|
||
self._shutting_down = True # <-- 在开始关闭时设置标志位
|
||
|
||
# 记录最终的消息统计
|
||
if self._message_count > 0:
|
||
logger.info(f"{self.log_prefix} 本次focus会话共发送了 {self._message_count} 条消息")
|
||
if self._fatigue_triggered:
|
||
logger.info(f"{self.log_prefix} 因疲惫而退出focus模式")
|
||
|
||
# 取消循环任务
|
||
if self._loop_task and not self._loop_task.done():
|
||
logger.info(f"{self.log_prefix} 正在取消HeartFChatting循环任务")
|
||
self._loop_task.cancel()
|
||
try:
|
||
await asyncio.wait_for(self._loop_task, timeout=1.0)
|
||
logger.info(f"{self.log_prefix} HeartFChatting循环任务已取消")
|
||
except (asyncio.CancelledError, asyncio.TimeoutError):
|
||
pass
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 取消循环任务出错: {e}")
|
||
else:
|
||
logger.info(f"{self.log_prefix} 没有活动的HeartFChatting循环任务")
|
||
|
||
# 清理状态
|
||
self._loop_active = False
|
||
self._loop_task = None
|
||
if self._processing_lock.locked():
|
||
self._processing_lock.release()
|
||
logger.warning(f"{self.log_prefix} 已释放处理锁")
|
||
|
||
# 完成性能统计
|
||
try:
|
||
self.performance_logger.finalize_session()
|
||
logger.info(f"{self.log_prefix} 性能统计已完成")
|
||
except Exception as e:
|
||
logger.warning(f"{self.log_prefix} 完成性能统计时出错: {e}")
|
||
|
||
# 重置消息计数器，为下次启动做准备
|
||
self.reset_message_count()
|
||
|
||
logger.info(f"{self.log_prefix} HeartFChatting关闭完成")
|
||
|
||
def get_cycle_history(self, last_n: Optional[int] = None) -> List[Dict[str, Any]]:
|
||
"""获取循环历史记录
|
||
|
||
参数:
|
||
last_n: 获取最近n个循环的信息，如果为None则获取所有历史记录
|
||
|
||
返回:
|
||
List[Dict[str, Any]]: 循环历史记录列表
|
||
"""
|
||
history = list(self._cycle_history)
|
||
if last_n is not None:
|
||
history = history[-last_n:]
|
||
return [cycle.to_dict() for cycle in history]
|