mirror of https://github.com/Mai-with-u/MaiBot.git
982 lines
44 KiB
Python
982 lines
44 KiB
Python
import asyncio
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import contextlib
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import json # <--- 确保导入 json
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import random # <--- 添加导入
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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, Coroutine
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from src.chat.message_receive.chat_stream import ChatStream
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from src.chat.message_receive.chat_stream import chat_manager
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from rich.traceback import install
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from src.common.logger_manager import get_logger
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from src.chat.models.utils_model import LLMRequest
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from src.config.config import global_config
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from src.chat.utils.timer_calculator import Timer
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from src.chat.heart_flow.observation.observation import Observation
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from src.chat.focus_chat.heartflow_prompt_builder import prompt_builder
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from src.chat.focus_chat.heartFC_Cycleinfo import CycleDetail
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from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
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from src.chat.heart_flow.utils_chat import get_chat_type_and_target_info
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from src.chat.focus_chat.info.info_base import InfoBase
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from src.chat.focus_chat.info.obs_info import ObsInfo
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from src.chat.focus_chat.info.cycle_info import CycleInfo
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from src.chat.focus_chat.info.mind_info import MindInfo
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from src.chat.focus_chat.info.structured_info import StructuredInfo
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from src.chat.focus_chat.info_processors.chattinginfo_processor import ChattingInfoProcessor
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from src.chat.focus_chat.info_processors.mind_processor import MindProcessor
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from src.chat.heart_flow.observation.memory_observation import MemoryObservation
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from src.chat.heart_flow.observation.hfcloop_observation import HFCloopObservation
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from src.chat.heart_flow.observation.working_observation import WorkingObservation
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from src.chat.focus_chat.info_processors.tool_processor import ToolProcessor
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from src.chat.focus_chat.expressors.default_expressor import DefaultExpressor
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from src.chat.focus_chat.hfc_utils import create_empty_anchor_message, parse_thinking_id_to_timestamp
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from src.chat.focus_chat.memory_activator import MemoryActivator
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install(extra_lines=3)
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WAITING_TIME_THRESHOLD = 300 # 等待新消息时间阈值，单位秒
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EMOJI_SEND_PRO = 0.3 # 设置一个概率，比如 30% 才真的发
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CONSECUTIVE_NO_REPLY_THRESHOLD = 3 # 连续不回复的阈值
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logger = get_logger("hfc") # Logger Name Changed
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# 默认动作定义
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DEFAULT_ACTIONS = {"no_reply": "不操作，继续浏览", "reply": "表达想法，可以只包含文本、表情或两者都有"}
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class ActionManager:
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"""动作管理器：控制每次决策可以使用的动作"""
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def __init__(self):
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# 初始化为新的默认动作集
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self._available_actions: Dict[str, str] = DEFAULT_ACTIONS.copy()
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self._original_actions_backup: Optional[Dict[str, str]] = None
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def get_available_actions(self) -> Dict[str, str]:
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"""获取当前可用的动作集"""
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return self._available_actions.copy() # 返回副本以防外部修改
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def add_action(self, action_name: str, description: str) -> bool:
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"""
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添加新的动作
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参数:
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action_name: 动作名称
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description: 动作描述
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返回:
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bool: 是否添加成功
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"""
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if action_name in self._available_actions:
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return False
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self._available_actions[action_name] = description
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return True
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def remove_action(self, action_name: str) -> bool:
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"""
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移除指定动作
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参数:
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action_name: 动作名称
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返回:
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bool: 是否移除成功
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"""
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if action_name not in self._available_actions:
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return False
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del self._available_actions[action_name]
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return True
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def temporarily_remove_actions(self, actions_to_remove: List[str]):
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"""
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临时移除指定的动作，备份原始动作集。
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如果已经有备份，则不重复备份。
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"""
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if self._original_actions_backup is None:
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self._original_actions_backup = self._available_actions.copy()
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actions_actually_removed = []
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for action_name in actions_to_remove:
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if action_name in self._available_actions:
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del self._available_actions[action_name]
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actions_actually_removed.append(action_name)
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# logger.debug(f"临时移除了动作: {actions_actually_removed}") # 可选日志
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def restore_actions(self):
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"""
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恢复之前备份的原始动作集。
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"""
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if self._original_actions_backup is not None:
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self._available_actions = self._original_actions_backup.copy()
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self._original_actions_backup = None
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# logger.debug("恢复了原始动作集") # 可选日志
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async def _handle_cycle_delay(action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
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"""处理循环延迟"""
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cycle_duration = time.monotonic() - cycle_start_time
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try:
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sleep_duration = 0.0
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if not action_taken_this_cycle and cycle_duration < 1:
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sleep_duration = 1 - cycle_duration
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elif cycle_duration < 0.2:
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sleep_duration = 0.2
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if sleep_duration > 0:
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await asyncio.sleep(sleep_duration)
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except asyncio.CancelledError:
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logger.info(f"{log_prefix} Sleep interrupted, loop likely cancelling.")
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raise
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class HeartFChatting:
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"""
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管理一个连续的Plan-Replier-Sender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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observations: list[Observation],
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on_consecutive_no_reply_callback: Callable[[], Coroutine[None, 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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observations: 关联的观察列表
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on_consecutive_no_reply_callback: 连续不回复达到阈值时调用的异步回调函数
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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: Optional[ChatStream] = None # 关联的聊天流
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self.observations: List[Observation] = observations # 关联的观察列表，用于监控聊天流状态
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self.on_consecutive_no_reply_callback = on_consecutive_no_reply_callback
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self.chatting_info_processor = ChattingInfoProcessor()
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self.mind_processor = MindProcessor(subheartflow_id=self.stream_id)
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self.memory_observation = MemoryObservation(observe_id=self.stream_id)
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self.hfcloop_observation = HFCloopObservation(observe_id=self.stream_id)
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self.tool_processor = ToolProcessor(subheartflow_id=self.stream_id)
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self.working_observation = WorkingObservation(observe_id=self.stream_id)
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self.memory_activator = MemoryActivator()
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# 日志前缀
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self.log_prefix: str = str(chat_id) # Initial default, will be updated
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# --- Initialize attributes (defaults) ---
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self.is_group_chat: bool = False
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self.chat_target_info: Optional[dict] = None
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# --- End Initialization ---
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self.expressor = DefaultExpressor(chat_id=self.stream_id)
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# 动作管理器
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self.action_manager = ActionManager()
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# 初始化状态控制
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self._initialized = False
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self._processing_lock = asyncio.Lock()
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# LLM规划器配置
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self.planner_llm = LLMRequest(
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model=global_config.llm_plan,
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max_tokens=1000,
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request_type="action_planning", # 用于动作规划
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)
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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: Optional[CycleDetail] = None
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self.total_no_reply_count: int = 0 # <--- 新增：连续不回复计数器
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self._shutting_down: bool = False # <--- 新增：关闭标志位
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self.total_waiting_time: float = 0.0 # <--- 新增：累计等待时间
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async def _initialize(self) -> bool:
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"""
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执行懒初始化操作
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功能:
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1. 获取聊天类型(群聊/私聊)和目标信息
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2. 获取聊天流对象
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3. 设置日志前缀
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返回:
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bool: 初始化是否成功
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注意:
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- 如果已经初始化过会直接返回True
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- 需要获取chat_stream对象才能继续后续操作
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"""
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# 如果已经初始化过，直接返回成功
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if self._initialized:
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return True
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try:
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self.is_group_chat, self.chat_target_info = await get_chat_type_and_target_info(self.stream_id)
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await self.expressor.initialize()
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self.chat_stream = await asyncio.to_thread(chat_manager.get_stream, self.stream_id)
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self.expressor.chat_stream = self.chat_stream
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self.log_prefix = f"[{chat_manager.get_stream_name(self.stream_id) or self.stream_id}]"
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except Exception as e:
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logger.error(f"[HFC:{self.stream_id}] 初始化HFC时发生错误: {e}")
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return False
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# 标记初始化完成
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self._initialized = True
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logger.debug(f"{self.log_prefix} 初始化完成，准备开始处理消息")
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return True
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async def start(self):
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"""
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启动 HeartFChatting 的主循环。
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注意：调用此方法前必须确保已经成功初始化。
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"""
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logger.info(f"{self.log_prefix} 开始认真水群(HFC)...")
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await self._start_loop_if_needed()
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async def _start_loop_if_needed(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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return
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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=0.5)
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except (asyncio.CancelledError, asyncio.TimeoutError):
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pass # 忽略取消或超时错误
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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} 启动认真水群(HFC)主循环...")
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# 创建新的循环任务
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self._loop_task = asyncio.create_task(self._hfc_loop())
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# 添加完成回调
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self._loop_task.add_done_callback(self._handle_loop_completion)
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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: 麦麦脱离了聊天(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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# Loop completing normally now means it was cancelled/shutdown externally
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logger.info(f"{self.log_prefix} HeartFChatting: 麦麦脱离了聊天 (外部停止)")
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except asyncio.CancelledError:
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logger.info(f"{self.log_prefix} HeartFChatting: 麦麦脱离了聊天(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 _hfc_loop(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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# --- 在循环开始处检查关闭标志 ---
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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 HFC 循环。")
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break
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# --------------------------------
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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 = CycleDetail(self._cycle_counter)
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# 初始化周期状态
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cycle_timers = {}
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loop_cycle_start_time = time.monotonic()
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# 执行规划和处理阶段
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async with self._get_cycle_context() as acquired_lock:
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if not acquired_lock:
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# 如果未能获取锁（理论上不太可能，除非 shutdown 过程中释放了但又被抢了？）
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# 或者也可以在这里再次检查 self._shutting_down
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if self._shutting_down:
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break # 再次检查，确保退出
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logger.warning(f"{self.log_prefix} 未能获取循环处理锁，跳过本次循环。")
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await asyncio.sleep(0.1) # 短暂等待避免空转
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continue
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# thinking_id 是思考过程的ID，用于标记每一轮思考
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thinking_id = "tid" + str(round(time.time(), 2))
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# 主循环：思考->决策->执行
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action_taken = await self._think_plan_execute_loop(cycle_timers, thinking_id)
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# 更新循环信息
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self._current_cycle.set_thinking_id(thinking_id)
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self._current_cycle.timers = cycle_timers
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# 防止循环过快消耗资源
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await _handle_cycle_delay(action_taken, loop_cycle_start_time, self.log_prefix)
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# 完成当前循环并保存历史
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self._current_cycle.complete_cycle()
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self._cycle_history.append(self._current_cycle)
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# 保存CycleInfo到文件
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try:
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filepath = CycleDetail.save_to_file(self._current_cycle, self.stream_id)
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logger.info(f"{self.log_prefix} 已保存循环信息到文件: {filepath}")
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except Exception as e:
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logger.error(f"{self.log_prefix} 保存循环信息到文件时出错: {e}")
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||
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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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||
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||
logger.debug(
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f"{self.log_prefix} 第 #{self._current_cycle.cycle_id}次思考完成,"
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f"耗时: {self._current_cycle.end_time - self._current_cycle.start_time:.2f}秒, "
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||
f"动作: {self._current_cycle.action_type}"
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||
+ (f"\n计时器详情: {'; '.join(timer_strings)}" if timer_strings else "")
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||
)
|
||
|
||
except asyncio.CancelledError:
|
||
# 设置了关闭标志位后被取消是正常流程
|
||
if not self._shutting_down:
|
||
logger.warning(f"{self.log_prefix} HeartFChatting: 麦麦的认真水群(HFC)循环意外被取消")
|
||
else:
|
||
logger.info(f"{self.log_prefix} HeartFChatting: 麦麦的认真水群(HFC)循环已取消 (正常关闭)")
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} HeartFChatting: 意外错误: {e}")
|
||
logger.error(traceback.format_exc())
|
||
|
||
@contextlib.asynccontextmanager
|
||
async def _get_cycle_context(self):
|
||
"""
|
||
循环周期的上下文管理器
|
||
|
||
用于确保资源的正确获取和释放：
|
||
1. 获取处理锁
|
||
2. 执行操作
|
||
3. 释放锁
|
||
"""
|
||
acquired = False
|
||
try:
|
||
await self._processing_lock.acquire()
|
||
acquired = True
|
||
yield acquired
|
||
finally:
|
||
if acquired and self._processing_lock.locked():
|
||
self._processing_lock.release()
|
||
|
||
async def _think_plan_execute_loop(self, cycle_timers: dict, thinking_id: str) -> tuple[bool, str]:
|
||
try:
|
||
with Timer("观察", cycle_timers):
|
||
await self.observations[0].observe()
|
||
await self.memory_observation.observe()
|
||
await self.working_observation.observe()
|
||
await self.hfcloop_observation.observe()
|
||
observations: List[Observation] = []
|
||
observations.append(self.observations[0])
|
||
observations.append(self.memory_observation)
|
||
observations.append(self.working_observation)
|
||
observations.append(self.hfcloop_observation)
|
||
|
||
for observation in observations:
|
||
logger.debug(f"{self.log_prefix} 观察信息: {observation}")
|
||
|
||
with Timer("回忆", cycle_timers):
|
||
running_memorys = await self.memory_activator.activate_memory(observations)
|
||
|
||
# 记录并行任务开始时间
|
||
parallel_start_time = time.time()
|
||
logger.debug(f"{self.log_prefix} 开始信息处理器并行任务")
|
||
|
||
# 并行执行两个任务：思考和工具执行
|
||
with Timer("执行 信息处理器", cycle_timers):
|
||
# 1. 子思维思考 - 不执行工具调用
|
||
think_task = asyncio.create_task(
|
||
self.mind_processor.process_info(observations=observations, running_memorys=running_memorys)
|
||
)
|
||
logger.debug(f"{self.log_prefix} 启动子思维思考任务")
|
||
|
||
# 2. 工具执行器 - 专门处理工具调用
|
||
tool_task = asyncio.create_task(
|
||
self.tool_processor.process_info(observations=observations, running_memorys=running_memorys)
|
||
)
|
||
logger.debug(f"{self.log_prefix} 启动工具执行任务")
|
||
|
||
# 3. 聊天信息处理器
|
||
chatting_info_task = asyncio.create_task(
|
||
self.chatting_info_processor.process_info(
|
||
observations=observations, running_memorys=running_memorys
|
||
)
|
||
)
|
||
logger.debug(f"{self.log_prefix} 启动聊天信息处理器任务")
|
||
|
||
# 创建任务完成状态追踪
|
||
tasks = {"思考任务": think_task, "工具任务": tool_task, "聊天信息处理任务": chatting_info_task}
|
||
pending = set(tasks.values())
|
||
|
||
# 等待所有任务完成，同时追踪每个任务的完成情况
|
||
results: dict[str, list[InfoBase]] = {}
|
||
while pending:
|
||
# 等待任务完成
|
||
done, pending = await asyncio.wait(pending, return_when=asyncio.FIRST_COMPLETED, timeout=1.0)
|
||
|
||
# 记录完成的任务
|
||
for task in done:
|
||
for name, t in tasks.items():
|
||
if task == t:
|
||
task_end_time = time.time()
|
||
task_duration = task_end_time - parallel_start_time
|
||
logger.info(f"{self.log_prefix} {name}已完成，耗时: {task_duration:.2f}秒")
|
||
results[name] = task.result()
|
||
break
|
||
|
||
# 如果仍有未完成任务，记录进行中状态
|
||
if pending:
|
||
current_time = time.time()
|
||
elapsed = current_time - parallel_start_time
|
||
pending_names = [name for name, t in tasks.items() if t in pending]
|
||
logger.info(
|
||
f"{self.log_prefix} 并行处理已进行{elapsed:.2f}秒，待完成任务: {', '.join(pending_names)}"
|
||
)
|
||
|
||
# 所有任务完成，从结果中提取数据
|
||
mind_processed_infos = results.get("思考任务", [])
|
||
tool_processed_infos = results.get("工具任务", [])
|
||
chatting_info_processed_infos = results.get("聊天信息处理任务", [])
|
||
|
||
# 记录总耗时
|
||
parallel_end_time = time.time()
|
||
total_duration = parallel_end_time - parallel_start_time
|
||
logger.info(f"{self.log_prefix} 思考和工具并行任务全部完成，总耗时: {total_duration:.2f}秒")
|
||
|
||
all_plan_info = mind_processed_infos + tool_processed_infos + chatting_info_processed_infos
|
||
|
||
logger.debug(f"{self.log_prefix} 所有信息处理器处理后的信息: {all_plan_info}")
|
||
# 串行执行规划器 - 使用刚获取的思考结果
|
||
logger.debug(f"{self.log_prefix} 开始 规划器")
|
||
with Timer("规划器", cycle_timers):
|
||
planner_result = await self._planner(all_plan_info, cycle_timers)
|
||
|
||
action = planner_result.get("action", "error")
|
||
action_data = planner_result.get("action_data", {}) # 新增获取动作数据
|
||
reasoning = planner_result.get("reasoning", "未提供理由")
|
||
|
||
logger.debug(f"{self.log_prefix} 动作和动作信息: {action}, {action_data}, {reasoning}")
|
||
|
||
# 更新循环信息
|
||
self._current_cycle.set_action_info(
|
||
action_type=action,
|
||
action_data=action_data,
|
||
reasoning=reasoning,
|
||
action_taken=True,
|
||
)
|
||
|
||
# 处理LLM错误
|
||
if planner_result.get("llm_error"):
|
||
logger.error(f"{self.log_prefix} LLM失败: {reasoning}")
|
||
return False, ""
|
||
|
||
# 在此处添加日志记录
|
||
if action == "reply":
|
||
action_str = "回复"
|
||
elif action == "no_reply":
|
||
action_str = "不回复"
|
||
else:
|
||
action_str = "位置动作"
|
||
|
||
logger.info(f"{self.log_prefix} 麦麦决定'{action_str}', 原因'{reasoning}'")
|
||
|
||
self.hfcloop_observation.add_loop_info(self._current_cycle)
|
||
|
||
return await self._handle_action(action, reasoning, action_data, cycle_timers, thinking_id)
|
||
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 并行+串行处理失败: {e}")
|
||
logger.error(traceback.format_exc())
|
||
return False, ""
|
||
|
||
async def _handle_action(
|
||
self,
|
||
action: str,
|
||
reasoning: str,
|
||
action_data: dict,
|
||
cycle_timers: dict,
|
||
thinking_id: str,
|
||
) -> tuple[bool, str]:
|
||
"""
|
||
处理规划动作
|
||
|
||
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
|
||
planner_start_db_time: 规划开始时间
|
||
|
||
返回:
|
||
tuple[bool, str]: (是否执行了动作, 思考消息ID)
|
||
"""
|
||
action_handlers = {
|
||
"reply": self._handle_reply,
|
||
"no_reply": self._handle_no_reply,
|
||
}
|
||
|
||
handler = action_handlers.get(action)
|
||
if not handler:
|
||
logger.warning(f"{self.log_prefix} 未知动作: {action}, 原因: {reasoning}")
|
||
return False, ""
|
||
|
||
try:
|
||
if action == "reply":
|
||
return await handler(reasoning, action_data, cycle_timers, thinking_id)
|
||
else: # no_reply
|
||
return await handler(reasoning, cycle_timers, thinking_id)
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 处理{action}时出错: {e}")
|
||
traceback.print_exc()
|
||
return False, ""
|
||
|
||
async def _handle_no_reply(self, reasoning: str, cycle_timers: dict, thinking_id: str) -> bool:
|
||
"""
|
||
处理不回复的情况
|
||
|
||
工作流程：
|
||
1. 等待新消息、超时或关闭信号
|
||
2. 根据等待结果更新连续不回复计数
|
||
3. 如果达到阈值，触发回调
|
||
|
||
参数:
|
||
reasoning: 不回复的原因
|
||
planner_start_db_time: 规划开始时间
|
||
cycle_timers: 计时器字典
|
||
|
||
返回:
|
||
bool: 是否成功处理
|
||
"""
|
||
logger.info(f"{self.log_prefix} 决定不回复: {reasoning}")
|
||
|
||
observation = self.observations[0] if self.observations else None
|
||
|
||
try:
|
||
with Timer("等待新消息", cycle_timers):
|
||
# 等待新消息、超时或关闭信号，并获取结果
|
||
await self._wait_for_new_message(observation, thinking_id, self.log_prefix)
|
||
# 从计时器获取实际等待时间
|
||
current_waiting = cycle_timers.get("等待新消息", 0.0)
|
||
|
||
if not self._shutting_down:
|
||
self.total_no_reply_count += 1
|
||
self.total_waiting_time += current_waiting # 累加等待时间
|
||
logger.debug(
|
||
f"{self.log_prefix} 连续不回复计数增加: {self.total_no_reply_count}/{CONSECUTIVE_NO_REPLY_THRESHOLD}, "
|
||
f"本次等待: {current_waiting:.2f}秒, 累计等待: {self.total_waiting_time:.2f}秒"
|
||
)
|
||
|
||
# 检查是否同时达到次数和时间阈值
|
||
time_threshold = 0.66 * WAITING_TIME_THRESHOLD * CONSECUTIVE_NO_REPLY_THRESHOLD
|
||
if (
|
||
self.total_no_reply_count >= CONSECUTIVE_NO_REPLY_THRESHOLD
|
||
and self.total_waiting_time >= time_threshold
|
||
):
|
||
logger.info(
|
||
f"{self.log_prefix} 连续不回复达到阈值 ({self.total_no_reply_count}次) "
|
||
f"且累计等待时间达到 {self.total_waiting_time:.2f}秒 (阈值 {time_threshold}秒)，"
|
||
f"调用回调请求状态转换"
|
||
)
|
||
# 调用回调。注意：这里不重置计数器和时间，依赖回调函数成功改变状态来隐式重置上下文。
|
||
await self.on_consecutive_no_reply_callback()
|
||
elif self.total_no_reply_count >= CONSECUTIVE_NO_REPLY_THRESHOLD:
|
||
# 仅次数达到阈值，但时间未达到
|
||
logger.debug(
|
||
f"{self.log_prefix} 连续不回复次数达到阈值 ({self.total_no_reply_count}次) "
|
||
f"但累计等待时间 {self.total_waiting_time:.2f}秒 未达到时间阈值 ({time_threshold}秒)，暂不调用回调"
|
||
)
|
||
# else: 次数和时间都未达到阈值，不做处理
|
||
|
||
return True, thinking_id
|
||
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{self.log_prefix} 处理 'no_reply' 时等待被中断 (CancelledError)")
|
||
raise
|
||
except Exception as e: # 捕获调用管理器或其他地方可能发生的错误
|
||
logger.error(f"{self.log_prefix} 处理 'no_reply' 时发生错误: {e}")
|
||
logger.error(traceback.format_exc())
|
||
return False, thinking_id
|
||
|
||
async def _wait_for_new_message(self, observation: ChattingObservation, thinking_id: str, log_prefix: str) -> bool:
|
||
"""
|
||
等待新消息 或 检测到关闭信号
|
||
|
||
参数:
|
||
observation: 观察实例
|
||
planner_start_db_time: 开始等待的时间
|
||
log_prefix: 日志前缀
|
||
|
||
返回:
|
||
bool: 是否检测到新消息 (如果因关闭信号退出则返回 False)
|
||
"""
|
||
wait_start_time = time.monotonic()
|
||
while True:
|
||
# --- 在每次循环开始时检查关闭标志 ---
|
||
if self._shutting_down:
|
||
logger.info(f"{log_prefix} 等待新消息时检测到关闭信号，中断等待。")
|
||
return False # 表示因为关闭而退出
|
||
# -----------------------------------
|
||
|
||
thinking_id_timestamp = parse_thinking_id_to_timestamp(thinking_id)
|
||
|
||
# 检查新消息
|
||
if await observation.has_new_messages_since(thinking_id_timestamp):
|
||
logger.info(f"{log_prefix} 检测到新消息")
|
||
return True
|
||
|
||
# 检查超时 (放在检查新消息和关闭之后)
|
||
if time.monotonic() - wait_start_time > WAITING_TIME_THRESHOLD:
|
||
logger.warning(f"{log_prefix} 等待新消息超时({WAITING_TIME_THRESHOLD}秒)")
|
||
return False
|
||
|
||
try:
|
||
# 短暂休眠，让其他任务有机会运行，并能更快响应取消或关闭
|
||
await asyncio.sleep(0.5) # 缩短休眠时间
|
||
except asyncio.CancelledError:
|
||
# 如果在休眠时被取消，再次检查关闭标志
|
||
# 如果是正常关闭，则不需要警告
|
||
if not self._shutting_down:
|
||
logger.warning(f"{log_prefix} _wait_for_new_message 的休眠被意外取消")
|
||
# 无论如何，重新抛出异常，让上层处理
|
||
raise
|
||
|
||
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
|
||
|
||
# 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")
|
||
|
||
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]
|
||
|
||
async def _planner(self, all_plan_info: List[InfoBase], cycle_timers: dict) -> Dict[str, Any]:
|
||
"""
|
||
规划器 (Planner): 使用LLM根据上下文决定是否和如何回复。
|
||
重构为：让LLM返回结构化JSON文本，然后在代码中解析。
|
||
|
||
参数:
|
||
current_mind: 子思维的当前思考结果
|
||
cycle_timers: 计时器字典
|
||
is_re_planned: 是否为重新规划 (此重构中暂时简化，不处理 is_re_planned 的特殊逻辑)
|
||
"""
|
||
logger.info(f"{self.log_prefix}开始 规划")
|
||
|
||
actions_to_remove_temporarily = []
|
||
# --- 检查历史动作并决定临时移除动作 (逻辑保持不变) ---
|
||
lian_xu_wen_ben_hui_fu = 0
|
||
probability_roll = random.random()
|
||
for cycle in reversed(self._cycle_history):
|
||
if cycle.action_taken:
|
||
if cycle.action_type == "text_reply":
|
||
lian_xu_wen_ben_hui_fu += 1
|
||
else:
|
||
break
|
||
if len(self._cycle_history) > 0 and cycle.cycle_id <= self._cycle_history[0].cycle_id + (
|
||
len(self._cycle_history) - 4
|
||
):
|
||
break
|
||
logger.debug(f"{self.log_prefix}[Planner] 检测到连续文本回复次数: {lian_xu_wen_ben_hui_fu}")
|
||
|
||
if lian_xu_wen_ben_hui_fu >= 3:
|
||
logger.info(f"{self.log_prefix}[Planner] 连续回复 >= 3 次，强制移除 text_reply 和 emoji_reply")
|
||
actions_to_remove_temporarily.extend(["text_reply", "emoji_reply"])
|
||
elif lian_xu_wen_ben_hui_fu == 2:
|
||
if probability_roll < 0.8:
|
||
logger.info(f"{self.log_prefix}[Planner] 连续回复 2 次，80% 概率移除 text_reply 和 emoji_reply (触发)")
|
||
actions_to_remove_temporarily.extend(["text_reply", "emoji_reply"])
|
||
else:
|
||
logger.info(
|
||
f"{self.log_prefix}[Planner] 连续回复 2 次，80% 概率移除 text_reply 和 emoji_reply (未触发)"
|
||
)
|
||
elif lian_xu_wen_ben_hui_fu == 1:
|
||
if probability_roll < 0.4:
|
||
logger.info(f"{self.log_prefix}[Planner] 连续回复 1 次，40% 概率移除 text_reply (触发)")
|
||
actions_to_remove_temporarily.append("text_reply")
|
||
else:
|
||
logger.info(f"{self.log_prefix}[Planner] 连续回复 1 次，40% 概率移除 text_reply (未触发)")
|
||
# --- 结束检查历史动作 ---
|
||
|
||
# 获取观察信息
|
||
for info in all_plan_info:
|
||
if isinstance(info, ObsInfo):
|
||
logger.debug(f"{self.log_prefix} 观察信息: {info}")
|
||
observed_messages = info.get_talking_message()
|
||
observed_messages_str = info.get_talking_message_str_truncate()
|
||
chat_type = info.get_chat_type()
|
||
if chat_type == "group":
|
||
is_group_chat = True
|
||
else:
|
||
is_group_chat = False
|
||
elif isinstance(info, MindInfo):
|
||
logger.debug(f"{self.log_prefix} 思维信息: {info}")
|
||
current_mind = info.get_current_mind()
|
||
elif isinstance(info, CycleInfo):
|
||
logger.debug(f"{self.log_prefix} 循环信息: {info}")
|
||
cycle_info = info.get_observe_info()
|
||
elif isinstance(info, StructuredInfo):
|
||
logger.debug(f"{self.log_prefix} 结构化信息: {info}")
|
||
structured_info = info.get_data()
|
||
|
||
# --- 使用 LLM 进行决策 (JSON 输出模式) --- #
|
||
action = "no_reply" # 默认动作
|
||
reasoning = "规划器初始化默认"
|
||
llm_error = False # LLM 请求或解析错误标志
|
||
|
||
# 获取我们将传递给 prompt 构建器和用于验证的当前可用动作
|
||
current_available_actions = self.action_manager.get_available_actions()
|
||
|
||
try:
|
||
# --- 应用临时动作移除 ---
|
||
if actions_to_remove_temporarily:
|
||
self.action_manager.temporarily_remove_actions(actions_to_remove_temporarily)
|
||
# 更新 current_available_actions 以反映移除后的状态
|
||
current_available_actions = self.action_manager.get_available_actions()
|
||
logger.debug(
|
||
f"{self.log_prefix}[Planner] 临时移除的动作: {actions_to_remove_temporarily}, 当前可用: {list(current_available_actions.keys())}"
|
||
)
|
||
|
||
# --- 构建提示词 (调用修改后的 PromptBuilder 方法) ---
|
||
prompt = await prompt_builder.build_planner_prompt(
|
||
is_group_chat=is_group_chat, # <-- Pass HFC state
|
||
chat_target_info=None,
|
||
observed_messages_str=observed_messages_str, # <-- Pass local variable
|
||
current_mind=current_mind, # <-- Pass argument
|
||
structured_info=structured_info, # <-- Pass SubMind info
|
||
current_available_actions=current_available_actions, # <-- Pass determined actions
|
||
cycle_info=cycle_info, # <-- Pass cycle info
|
||
)
|
||
|
||
# --- 调用 LLM (普通文本生成) ---
|
||
llm_content = None
|
||
try:
|
||
llm_content, _, _ = await self.planner_llm.generate_response(prompt=prompt)
|
||
logger.debug(f"{self.log_prefix}[Planner] LLM 原始 JSON 响应 (预期): {llm_content}")
|
||
except Exception as req_e:
|
||
logger.error(f"{self.log_prefix}[Planner] LLM 请求执行失败: {req_e}")
|
||
reasoning = f"LLM 请求失败: {req_e}"
|
||
llm_error = True
|
||
# 直接使用默认动作返回错误结果
|
||
action = "no_reply" # 明确设置为默认值
|
||
|
||
# --- 解析 LLM 返回的 JSON (仅当 LLM 请求未出错时进行) ---
|
||
if not llm_error and llm_content:
|
||
try:
|
||
# 尝试去除可能的 markdown 代码块标记
|
||
cleaned_content = (
|
||
llm_content.strip().removeprefix("```json").removeprefix("```").removesuffix("```").strip()
|
||
)
|
||
if not cleaned_content:
|
||
raise json.JSONDecodeError("Cleaned content is empty", cleaned_content, 0)
|
||
parsed_json = json.loads(cleaned_content)
|
||
|
||
# 提取决策，提供默认值
|
||
extracted_action = parsed_json.get("action", "no_reply")
|
||
extracted_reasoning = parsed_json.get("reasoning", "LLM未提供理由")
|
||
# extracted_emoji_query = parsed_json.get("emoji_query", "")
|
||
|
||
# 新的reply格式
|
||
if extracted_action == "reply":
|
||
action_data = {
|
||
"text": parsed_json.get("text", []),
|
||
"emojis": parsed_json.get("emojis", []),
|
||
"target": parsed_json.get("target", ""),
|
||
}
|
||
else:
|
||
action_data = {} # 其他动作可能不需要额外数据
|
||
|
||
# 验证动作是否在当前可用列表中
|
||
# !! 使用调用 prompt 时实际可用的动作列表进行验证
|
||
if extracted_action not in current_available_actions:
|
||
logger.warning(
|
||
f"{self.log_prefix}[Planner] LLM 返回了当前不可用或无效的动作: '{extracted_action}' (可用: {list(current_available_actions.keys())})，将强制使用 'no_reply'"
|
||
)
|
||
action = "no_reply"
|
||
reasoning = f"LLM 返回了当前不可用的动作 '{extracted_action}' (可用: {list(current_available_actions.keys())})。原始理由: {extracted_reasoning}"
|
||
# 检查 no_reply 是否也恰好被移除了 (极端情况)
|
||
if "no_reply" not in current_available_actions:
|
||
logger.error(
|
||
f"{self.log_prefix}[Planner] 严重错误：'no_reply' 动作也不可用！无法执行任何动作。"
|
||
)
|
||
action = "error" # 回退到错误状态
|
||
reasoning = "无法执行任何有效动作，包括 no_reply"
|
||
llm_error = True # 标记为严重错误
|
||
else:
|
||
llm_error = False # 视为逻辑修正而非 LLM 错误
|
||
else:
|
||
# 动作有效且可用
|
||
action = extracted_action
|
||
reasoning = extracted_reasoning
|
||
llm_error = False # 解析成功
|
||
logger.debug(
|
||
f"{self.log_prefix}[要做什么]\nPrompt:\n{prompt}\n\n决策结果 (来自JSON): {action}, 理由: {reasoning}"
|
||
)
|
||
logger.debug(f"{self.log_prefix}动作信息: '{action_data}'")
|
||
|
||
except Exception as json_e:
|
||
logger.warning(
|
||
f"{self.log_prefix}[Planner] 解析LLM响应JSON失败: {json_e}. LLM原始输出: '{llm_content}'"
|
||
)
|
||
reasoning = f"解析LLM响应JSON失败: {json_e}. 将使用默认动作 'no_reply'."
|
||
action = "no_reply" # 解析失败则默认不回复
|
||
llm_error = True # 标记解析错误
|
||
elif not llm_error and not llm_content:
|
||
# LLM 请求成功但返回空内容
|
||
logger.warning(f"{self.log_prefix}[Planner] LLM 返回了空内容。")
|
||
reasoning = "LLM 返回了空内容，使用默认动作 'no_reply'."
|
||
action = "no_reply"
|
||
llm_error = True # 标记为空响应错误
|
||
|
||
except Exception as outer_e:
|
||
logger.error(f"{self.log_prefix}[Planner] Planner 处理过程中发生意外错误: {outer_e}")
|
||
traceback.print_exc()
|
||
action = "error" # 发生未知错误，标记为 error 动作
|
||
reasoning = f"Planner 内部处理错误: {outer_e}"
|
||
llm_error = True
|
||
finally:
|
||
# --- 确保动作恢复 ---
|
||
if self.action_manager._original_actions_backup is not None:
|
||
self.action_manager.restore_actions()
|
||
logger.debug(
|
||
f"{self.log_prefix}[Planner] 恢复了原始动作集, 当前可用: {list(self.action_manager.get_available_actions().keys())}"
|
||
)
|
||
|
||
# --- 概率性忽略文本回复附带的表情 (逻辑保持不变) ---
|
||
emoji = action_data.get("emojis")
|
||
if action == "reply" and emoji:
|
||
logger.debug(f"{self.log_prefix}[Planner] 大模型建议文字回复带表情: '{emoji}'")
|
||
if random.random() > EMOJI_SEND_PRO:
|
||
logger.info(f"{self.log_prefix}但是麦麦这次不想加表情 ({1 - EMOJI_SEND_PRO:.0%})，忽略表情 '{emoji}'")
|
||
action_data["emojis"] = "" # 清空表情请求
|
||
else:
|
||
logger.info(f"{self.log_prefix}好吧，加上表情 '{emoji}'")
|
||
# --- 结束概率性忽略 ---
|
||
|
||
# 返回结果字典
|
||
return {
|
||
"action": action,
|
||
"action_data": action_data,
|
||
"reasoning": reasoning,
|
||
"current_mind": current_mind,
|
||
"observed_messages": observed_messages,
|
||
"llm_error": llm_error, # 返回错误状态
|
||
}
|
||
|
||
async def _handle_reply(
|
||
self, reasoning: str, reply_data: dict, cycle_timers: dict, thinking_id: str
|
||
) -> tuple[bool, str]:
|
||
"""
|
||
处理统一的回复动作 - 可包含文本和表情，顺序任意
|
||
|
||
reply_data格式:
|
||
{
|
||
"text": "你好啊" # 文本内容列表（可选）
|
||
"target": "锚定消息", # 锚定消息的文本内容
|
||
"emojis": "微笑" # 表情关键词列表（可选）
|
||
}
|
||
"""
|
||
# 重置连续不回复计数器
|
||
self.total_no_reply_count = 0
|
||
self.total_waiting_time = 0.0
|
||
|
||
# 从聊天观察获取锚定消息
|
||
observations: ChattingObservation = self.observations[0]
|
||
anchor_message = observations.serch_message_by_text(reply_data["target"])
|
||
|
||
# 如果没有找到锚点消息，创建一个占位符
|
||
if not anchor_message:
|
||
logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
|
||
anchor_message = await create_empty_anchor_message(
|
||
self.chat_stream.platform, self.chat_stream.group_info, self.chat_stream
|
||
)
|
||
else:
|
||
anchor_message.update_chat_stream(self.chat_stream)
|
||
|
||
success, reply_set = await self.expressor.deal_reply(
|
||
cycle_timers=cycle_timers,
|
||
action_data=reply_data,
|
||
anchor_message=anchor_message,
|
||
reasoning=reasoning,
|
||
thinking_id=thinking_id,
|
||
)
|
||
|
||
reply_text = ""
|
||
for reply in reply_set:
|
||
type = reply[0]
|
||
data = reply[1]
|
||
if type == "text":
|
||
reply_text += data
|
||
elif type == "emoji":
|
||
reply_text += data
|
||
|
||
self._current_cycle.set_response_info(
|
||
response_text=reply_text,
|
||
)
|
||
|
||
return success, reply_text
|