1322 lines
56 KiB
Python
1322 lines
56 KiB
Python
import asyncio
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import time
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import traceback
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from typing import List, Optional, Dict, Any, Deque, Callable, Coroutine
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from collections import deque
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from src.plugins.chat.message import MessageRecv, BaseMessageInfo, MessageThinking, MessageSending
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from src.plugins.chat.message import Seg # Local import needed after move
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from src.plugins.chat.chat_stream import ChatStream
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from src.plugins.chat.message import UserInfo
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from src.plugins.chat.chat_stream import chat_manager
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from src.common.logger_manager import get_logger
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from src.plugins.models.utils_model import LLMRequest
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from src.config.config import global_config
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from src.plugins.chat.utils_image import image_path_to_base64 # Local import needed after move
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from src.plugins.utils.timer_calculator import Timer # <--- Import Timer
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from src.do_tool.tool_use import ToolUser
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from src.plugins.emoji_system.emoji_manager import emoji_manager
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from src.plugins.utils.json_utils import process_llm_tool_calls, extract_tool_call_arguments
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from src.heart_flow.sub_mind import SubMind
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from src.heart_flow.observation import Observation
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from src.plugins.heartFC_chat.heartflow_prompt_builder import global_prompt_manager, prompt_builder
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import contextlib
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from src.plugins.utils.chat_message_builder import num_new_messages_since
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from src.plugins.heartFC_chat.heartFC_Cycleinfo import CycleInfo
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from .heartFC_sender import HeartFCSender
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from src.plugins.chat.utils import process_llm_response
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from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
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from src.plugins.moods.moods import MoodManager
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from src.individuality.individuality import Individuality
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INITIAL_DURATION = 60.0
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logger = get_logger("interest") # Logger Name Changed
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# 默认动作定义
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DEFAULT_ACTIONS = {"no_reply": "不回复", "text_reply": "文本回复, 可选附带表情", "emoji_reply": "仅表情回复"}
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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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# 初始化为默认动作集
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self._available_actions: Dict[str, str] = DEFAULT_ACTIONS.copy()
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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
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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 clear_actions(self):
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"""清空所有动作"""
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self._available_actions.clear()
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def reset_to_default(self):
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"""重置为默认动作集"""
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self._available_actions = DEFAULT_ACTIONS.copy()
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def get_planner_tool_definition(self) -> List[Dict[str, Any]]:
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"""获取当前动作集对应的规划器工具定义"""
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return [
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{
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"type": "function",
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"function": {
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"name": "decide_reply_action",
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"description": "根据当前聊天内容和上下文，决定机器人是否应该回复以及如何回复。",
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"parameters": {
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"type": "object",
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"properties": {
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"action": {
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"type": "string",
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"enum": list(self._available_actions.keys()),
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"description": "决定采取的行动："
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+ ", ".join([f"'{k}'({v})" for k, v in self._available_actions.items()]),
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},
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"reasoning": {"type": "string", "description": "做出此决定的简要理由。"},
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"emoji_query": {
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"type": "string",
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"description": "如果行动是'emoji_reply'，指定表情的主题或概念。如果行动是'text_reply'且希望在文本后追加表情，也在此指定表情主题。",
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},
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},
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"required": ["action", "reasoning"],
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},
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},
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}
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]
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# 在文件开头添加自定义异常类
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class HeartFCError(Exception):
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"""麦麦聊天系统基础异常类"""
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pass
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class PlannerError(HeartFCError):
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"""规划器异常"""
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pass
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class ReplierError(HeartFCError):
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"""回复器异常"""
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pass
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class SenderError(HeartFCError):
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"""发送器异常"""
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pass
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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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CONSECUTIVE_NO_REPLY_THRESHOLD = 5 # 连续不回复的阈值
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def __init__(
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self,
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chat_id: str,
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sub_mind: SubMind,
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observations: 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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sub_mind: 关联的子思维
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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.sub_mind: SubMind = sub_mind # 关联的子思维
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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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# 日志前缀
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self.log_prefix: str = f"[{chat_manager.get_stream_name(chat_id) or chat_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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# --- 移除 gpt_instance, 直接初始化 LLM 模型 ---
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# self.gpt_instance = HeartFCGenerator() # <-- 移除
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self.model_normal = LLMRequest( # <-- 新增 LLM 初始化
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model=global_config.llm_normal,
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temperature=global_config.llm_normal["temp"],
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max_tokens=256,
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request_type="response_heartflow",
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)
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self.tool_user = ToolUser()
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self.heart_fc_sender = HeartFCSender()
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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[CycleInfo] = deque(maxlen=10) # 保留最近10个循环的信息
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self._current_cycle: Optional[CycleInfo] = None
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self._lian_xu_bu_hui_fu_ci_shu: 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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async def _initialize(self) -> bool:
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"""
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懒初始化以使用提供的标识符解析chat_stream。
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确保实例已准备好处理触发器。
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"""
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if self._initialized:
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return True
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self.chat_stream = chat_manager.get_stream(self.stream_id)
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if not self.chat_stream:
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logger.error(f"{self.log_prefix} 获取ChatStream失败。")
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return False
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# 更新日志前缀（以防流名称发生变化）
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self.log_prefix = f"[{chat_manager.get_stream_name(self.stream_id) or self.stream_id}]"
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self._initialized = True
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logger.info(f"麦麦感觉到了，可以开始认真水群{self.log_prefix} ")
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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.info(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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# --- 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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||
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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 = CycleInfo(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
|
||
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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|
||
# 记录规划开始时间点
|
||
planner_start_db_time = time.time()
|
||
|
||
# 主循环：思考->决策->执行
|
||
action_taken, thinking_id = await self._think_plan_execute_loop(cycle_timers, planner_start_db_time)
|
||
|
||
# 更新循环信息
|
||
self._current_cycle.set_thinking_id(thinking_id)
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self._current_cycle.timers = cycle_timers
|
||
|
||
# 防止循环过快消耗资源
|
||
await self._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
|
||
self._current_cycle.complete_cycle()
|
||
self._cycle_history.append(self._current_cycle)
|
||
|
||
# 记录循环信息和计时器结果
|
||
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"
|
||
timer_strings.append(f"{name}: {formatted_time}")
|
||
|
||
logger.debug(
|
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f"{self.log_prefix} 第 #{self._current_cycle.cycle_id}次思考完成,"
|
||
f"耗时: {self._current_cycle.end_time - self._current_cycle.start_time:.2f}秒, "
|
||
f"动作: {self._current_cycle.action_type}"
|
||
+ (f"\n计时器详情: {'; '.join(timer_strings)}" if timer_strings else "")
|
||
)
|
||
|
||
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 _check_new_messages(self, start_time: float) -> bool:
|
||
"""
|
||
检查从指定时间点后是否有新消息
|
||
|
||
参数:
|
||
start_time: 开始检查的时间点
|
||
|
||
返回:
|
||
bool: 是否有新消息
|
||
"""
|
||
try:
|
||
new_msg_count = num_new_messages_since(self.stream_id, start_time)
|
||
if new_msg_count > 0:
|
||
logger.info(f"{self.log_prefix} 检测到{new_msg_count}条新消息")
|
||
return True
|
||
return False
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 检查新消息时出错: {e}")
|
||
return False
|
||
|
||
async def _think_plan_execute_loop(self, cycle_timers: dict, planner_start_db_time: float) -> tuple[bool, str]:
|
||
"""执行规划阶段"""
|
||
try:
|
||
# think:思考
|
||
current_mind = await self._get_submind_thinking(cycle_timers)
|
||
# 记录子思维思考内容
|
||
if self._current_cycle:
|
||
self._current_cycle.set_response_info(sub_mind_thinking=current_mind)
|
||
|
||
# plan:决策
|
||
with Timer("决策", cycle_timers):
|
||
planner_result = await self._planner(current_mind, cycle_timers)
|
||
|
||
# 效果不太好，还没处理replan导致观察时间点改变的问题
|
||
|
||
# action = planner_result.get("action", "error")
|
||
# reasoning = planner_result.get("reasoning", "未提供理由")
|
||
|
||
# self._current_cycle.set_action_info(action, reasoning, False)
|
||
|
||
# 在获取规划结果后检查新消息
|
||
|
||
# if await self._check_new_messages(planner_start_db_time):
|
||
# if random.random() < 0.2:
|
||
# logger.info(f"{self.log_prefix} 看到了新消息，麦麦决定重新观察和规划...")
|
||
# # 重新规划
|
||
# with Timer("重新决策", cycle_timers):
|
||
# self._current_cycle.replanned = True
|
||
# planner_result = await self._planner(current_mind, cycle_timers, is_re_planned=True)
|
||
# logger.info(f"{self.log_prefix} 重新规划完成.")
|
||
|
||
# 解析规划结果
|
||
action = planner_result.get("action", "error")
|
||
reasoning = planner_result.get("reasoning", "未提供理由")
|
||
# 更新循环信息
|
||
self._current_cycle.set_action_info(action, reasoning, True)
|
||
|
||
# 处理LLM错误
|
||
if planner_result.get("llm_error"):
|
||
logger.error(f"{self.log_prefix} LLM失败: {reasoning}")
|
||
return False, ""
|
||
|
||
# execute:执行
|
||
|
||
return await self._handle_action(
|
||
action, reasoning, planner_result.get("emoji_query", ""), cycle_timers, planner_start_db_time
|
||
)
|
||
|
||
except PlannerError as e:
|
||
logger.error(f"{self.log_prefix} 规划错误: {e}")
|
||
# 更新循环信息
|
||
self._current_cycle.set_action_info("error", str(e), False)
|
||
return False, ""
|
||
|
||
async def _handle_action(
|
||
self, action: str, reasoning: str, emoji_query: str, cycle_timers: dict, planner_start_db_time: float
|
||
) -> tuple[bool, str]:
|
||
"""
|
||
处理规划动作
|
||
|
||
参数:
|
||
action: 动作类型
|
||
reasoning: 决策理由
|
||
emoji_query: 表情查询
|
||
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 = {
|
||
"text_reply": self._handle_text_reply,
|
||
"emoji_reply": self._handle_emoji_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 == "text_reply":
|
||
return await handler(reasoning, emoji_query, cycle_timers)
|
||
elif action == "emoji_reply":
|
||
return await handler(reasoning, emoji_query), ""
|
||
else: # no_reply
|
||
return await handler(reasoning, planner_start_db_time, cycle_timers), ""
|
||
except HeartFCError as e:
|
||
logger.error(f"{self.log_prefix} 处理{action}时出错: {e}")
|
||
# 出错时也重置计数器
|
||
self._lian_xu_bu_hui_fu_ci_shu = 0
|
||
return False, ""
|
||
|
||
async def _handle_text_reply(self, reasoning: str, emoji_query: str, cycle_timers: dict) -> tuple[bool, str]:
|
||
"""
|
||
处理文本回复
|
||
|
||
工作流程：
|
||
1. 获取锚点消息
|
||
2. 创建思考消息
|
||
3. 生成回复
|
||
4. 发送消息
|
||
|
||
参数:
|
||
reasoning: 回复原因
|
||
emoji_query: 表情查询
|
||
cycle_timers: 计时器字典
|
||
|
||
返回:
|
||
tuple[bool, str]: (是否回复成功, 思考消息ID)
|
||
"""
|
||
# 重置连续不回复计数器
|
||
self._lian_xu_bu_hui_fu_ci_shu = 0
|
||
|
||
# 获取锚点消息
|
||
anchor_message = await self._get_anchor_message()
|
||
if not anchor_message:
|
||
raise PlannerError("无法获取锚点消息")
|
||
|
||
# 创建思考消息
|
||
thinking_id = await self._create_thinking_message(anchor_message)
|
||
if not thinking_id:
|
||
raise PlannerError("无法创建思考消息")
|
||
|
||
try:
|
||
# 生成回复
|
||
with Timer("生成回复", cycle_timers):
|
||
reply = await self._replier_work(
|
||
anchor_message=anchor_message,
|
||
thinking_id=thinking_id,
|
||
reason=reasoning,
|
||
)
|
||
|
||
if not reply:
|
||
raise ReplierError("回复生成失败")
|
||
|
||
# 发送消息
|
||
|
||
with Timer("发送消息", cycle_timers):
|
||
await self._sender(
|
||
thinking_id=thinking_id,
|
||
anchor_message=anchor_message,
|
||
response_set=reply,
|
||
send_emoji=emoji_query,
|
||
)
|
||
|
||
return True, thinking_id
|
||
|
||
except (ReplierError, SenderError) as e:
|
||
logger.error(f"{self.log_prefix} 回复失败: {e}")
|
||
return True, thinking_id # 仍然返回thinking_id以便跟踪
|
||
|
||
async def _handle_emoji_reply(self, reasoning: str, emoji_query: str) -> bool:
|
||
"""
|
||
处理表情回复
|
||
|
||
工作流程：
|
||
1. 获取锚点消息
|
||
2. 发送表情
|
||
|
||
参数:
|
||
reasoning: 回复原因
|
||
emoji_query: 表情查询
|
||
|
||
返回:
|
||
bool: 是否发送成功
|
||
"""
|
||
logger.info(f"{self.log_prefix} 决定回复表情({emoji_query}): {reasoning}")
|
||
|
||
try:
|
||
anchor = await self._get_anchor_message()
|
||
if not anchor:
|
||
raise PlannerError("无法获取锚点消息")
|
||
|
||
await self._handle_emoji(anchor, [], emoji_query)
|
||
return True
|
||
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 表情发送失败: {e}")
|
||
return False
|
||
|
||
async def _handle_no_reply(self, reasoning: str, planner_start_db_time: float, cycle_timers: dict) -> 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, planner_start_db_time, self.log_prefix)
|
||
|
||
if not self._shutting_down:
|
||
self._lian_xu_bu_hui_fu_ci_shu += 1
|
||
logger.debug(
|
||
f"{self.log_prefix} 连续不回复计数增加: {self._lian_xu_bu_hui_fu_ci_shu}/{self.CONSECUTIVE_NO_REPLY_THRESHOLD}"
|
||
)
|
||
|
||
# 检查是否达到阈值
|
||
if self._lian_xu_bu_hui_fu_ci_shu >= self.CONSECUTIVE_NO_REPLY_THRESHOLD:
|
||
logger.info(
|
||
f"{self.log_prefix} 连续不回复达到阈值 ({self._lian_xu_bu_hui_fu_ci_shu}次)，调用回调请求状态转换"
|
||
)
|
||
# 调用回调。注意：这里不重置计数器，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()
|
||
|
||
return True
|
||
|
||
except asyncio.CancelledError:
|
||
# 如果在等待过程中任务被取消（可能是因为 shutdown）
|
||
logger.info(f"{self.log_prefix} 处理 'no_reply' 时等待被中断 (CancelledError)")
|
||
# 让异常向上传播，由 _hfc_loop 的异常处理逻辑接管
|
||
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())
|
||
# 发生意外错误时，可以选择是否重置计数器，这里选择不重置
|
||
return False # 表示动作未成功
|
||
|
||
async def _wait_for_new_message(self, observation, planner_start_db_time: float, 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
|
||
# -----------------------------------
|
||
|
||
# 检查新消息
|
||
if await observation.has_new_messages_since(planner_start_db_time):
|
||
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 > 120:
|
||
logger.warning(f"{log_prefix} 等待新消息超时(20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 _log_cycle_timers(self, cycle_timers: dict, log_prefix: str):
|
||
"""记录循环周期的计时器结果"""
|
||
if cycle_timers:
|
||
timer_strings = []
|
||
for name, elapsed in cycle_timers.items():
|
||
formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
|
||
timer_strings.append(f"{name}: {formatted_time}")
|
||
|
||
if timer_strings:
|
||
# 在记录前检查关闭标志
|
||
if not self._shutting_down:
|
||
logger.debug(f"{log_prefix} 该次决策耗时: {'; '.join(timer_strings)}")
|
||
|
||
async def _handle_cycle_delay(self, action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
|
||
"""处理循环延迟"""
|
||
cycle_duration = time.monotonic() - cycle_start_time
|
||
|
||
try:
|
||
sleep_duration = 0.0
|
||
if not action_taken_this_cycle and cycle_duration < 1:
|
||
sleep_duration = 1 - cycle_duration
|
||
elif cycle_duration < 0.2:
|
||
sleep_duration = 0.2
|
||
|
||
if sleep_duration > 0:
|
||
await asyncio.sleep(sleep_duration)
|
||
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{log_prefix} Sleep interrupted, loop likely cancelling.")
|
||
raise
|
||
|
||
async def _get_submind_thinking(self, cycle_timers: dict) -> str:
|
||
"""
|
||
获取子思维的思考结果
|
||
|
||
返回:
|
||
str: 思考结果，如果思考失败则返回错误信息
|
||
"""
|
||
try:
|
||
with Timer("观察", cycle_timers):
|
||
observation = self.observations[0]
|
||
await observation.observe()
|
||
|
||
# 获取上一个循环的信息
|
||
# last_cycle = self._cycle_history[-1] if self._cycle_history else None
|
||
|
||
with Timer("思考", cycle_timers):
|
||
# 获取上一个循环的动作
|
||
# 传递上一个循环的信息给 do_thinking_before_reply
|
||
current_mind, _past_mind = await self.sub_mind.do_thinking_before_reply(
|
||
history_cycle=self._cycle_history
|
||
)
|
||
return current_mind
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix}[SubMind] 思考失败: {e}")
|
||
logger.error(traceback.format_exc())
|
||
return "[思考时出错]"
|
||
|
||
async def _planner(self, current_mind: str, cycle_timers: dict, is_re_planned: bool = False) -> Dict[str, Any]:
|
||
"""
|
||
规划器 (Planner): 使用LLM根据上下文决定是否和如何回复。
|
||
|
||
参数:
|
||
current_mind: 子思维的当前思考结果
|
||
"""
|
||
logger.info(f"{self.log_prefix}[Planner] 开始{'重新' if is_re_planned else ''}执行规划器")
|
||
|
||
# 获取观察信息
|
||
observation = self.observations[0]
|
||
if is_re_planned:
|
||
await observation.observe()
|
||
observed_messages = observation.talking_message
|
||
observed_messages_str = observation.talking_message_str
|
||
|
||
# --- 使用 LLM 进行决策 --- #
|
||
reasoning = "默认决策或获取决策失败"
|
||
llm_error = False # LLM错误标志
|
||
arguments = None # 初始化参数变量
|
||
emoji_query = "" # <--- 在这里初始化 emoji_query
|
||
|
||
try:
|
||
# --- 构建提示词 ---
|
||
replan_prompt_str = ""
|
||
if is_re_planned:
|
||
replan_prompt_str = await self._build_replan_prompt(
|
||
self._current_cycle.action_type, self._current_cycle.reasoning
|
||
)
|
||
prompt = await self._build_planner_prompt(
|
||
observed_messages_str, current_mind, self.sub_mind.structured_info, replan_prompt_str
|
||
)
|
||
|
||
# --- 调用 LLM ---
|
||
try:
|
||
planner_tools = self.action_manager.get_planner_tool_definition()
|
||
_response_text, _reasoning_content, tool_calls = await self.planner_llm.generate_response_tool_async(
|
||
prompt=prompt,
|
||
tools=planner_tools,
|
||
)
|
||
logger.debug(f"{self.log_prefix}[Planner] 原始人 LLM响应: {_response_text}")
|
||
except Exception as req_e:
|
||
logger.error(f"{self.log_prefix}[Planner] LLM请求执行失败: {req_e}")
|
||
action = "error"
|
||
reasoning = f"LLM请求失败: {req_e}"
|
||
llm_error = True
|
||
# 直接返回错误结果
|
||
return {
|
||
"action": action,
|
||
"reasoning": reasoning,
|
||
"emoji_query": "",
|
||
"current_mind": current_mind,
|
||
"observed_messages": observed_messages,
|
||
"llm_error": llm_error,
|
||
}
|
||
|
||
# 默认错误状态
|
||
action = "error"
|
||
reasoning = "处理工具调用时出错"
|
||
llm_error = True
|
||
|
||
# 1. 验证工具调用
|
||
success, valid_tool_calls, error_msg = process_llm_tool_calls(
|
||
tool_calls, log_prefix=f"{self.log_prefix}[Planner] "
|
||
)
|
||
|
||
if success and valid_tool_calls:
|
||
# 2. 提取第一个调用并获取参数
|
||
first_tool_call = valid_tool_calls[0]
|
||
tool_name = first_tool_call.get("function", {}).get("name")
|
||
arguments = extract_tool_call_arguments(first_tool_call, None)
|
||
|
||
# 3. 检查名称和参数
|
||
expected_tool_name = "decide_reply_action"
|
||
if tool_name == expected_tool_name and arguments is not None:
|
||
# 4. 成功，提取决策
|
||
extracted_action = arguments.get("action", "no_reply")
|
||
# 验证动作
|
||
if extracted_action not in self.action_manager.get_available_actions():
|
||
logger.warning(
|
||
f"{self.log_prefix}[Planner] LLM返回了未授权的动作: {extracted_action}，使用默认动作no_reply"
|
||
)
|
||
action = "no_reply"
|
||
reasoning = f"LLM返回了未授权的动作: {extracted_action}"
|
||
emoji_query = ""
|
||
llm_error = False # 视为非LLM错误，只是逻辑修正
|
||
else:
|
||
# 动作有效，使用提取的值
|
||
action = extracted_action
|
||
reasoning = arguments.get("reasoning", "未提供理由")
|
||
emoji_query = arguments.get("emoji_query", "")
|
||
llm_error = False # 成功处理
|
||
# 记录决策结果
|
||
logger.debug(
|
||
f"{self.log_prefix}[要做什么]\nPrompt:\n{prompt}\n\n决策结果: {action}, 理由: {reasoning}, 表情查询: '{emoji_query}'"
|
||
)
|
||
elif tool_name != expected_tool_name:
|
||
reasoning = f"LLM返回了非预期的工具: {tool_name}"
|
||
logger.warning(f"{self.log_prefix}[Planner] {reasoning}")
|
||
else: # arguments is None
|
||
reasoning = f"无法提取工具 {tool_name} 的参数"
|
||
logger.warning(f"{self.log_prefix}[Planner] {reasoning}")
|
||
elif not success:
|
||
reasoning = f"验证工具调用失败: {error_msg}"
|
||
logger.warning(f"{self.log_prefix}[Planner] {reasoning}")
|
||
else: # not valid_tool_calls
|
||
reasoning = "LLM未返回有效的工具调用"
|
||
logger.warning(f"{self.log_prefix}[Planner] {reasoning}")
|
||
# 如果 llm_error 仍然是 True，说明在处理过程中有错误发生
|
||
|
||
except Exception as llm_e:
|
||
logger.error(f"{self.log_prefix}[Planner] Planner LLM处理过程中发生意外错误: {llm_e}")
|
||
logger.error(traceback.format_exc())
|
||
action = "error"
|
||
reasoning = f"Planner内部处理错误: {llm_e}"
|
||
llm_error = True
|
||
# --- 结束 LLM 决策 --- #
|
||
|
||
return {
|
||
"action": action,
|
||
"reasoning": reasoning,
|
||
"emoji_query": emoji_query,
|
||
"current_mind": current_mind,
|
||
"observed_messages": observed_messages,
|
||
"llm_error": llm_error,
|
||
}
|
||
|
||
async def _get_anchor_message(self) -> Optional[MessageRecv]:
|
||
"""
|
||
重构观察到的最后一条消息作为回复的锚点，
|
||
如果重构失败或观察为空，则创建一个占位符。
|
||
"""
|
||
|
||
try:
|
||
placeholder_id = f"mid_pf_{int(time.time() * 1000)}"
|
||
placeholder_user = UserInfo(
|
||
user_id="system_trigger", user_nickname="System Trigger", platform=self.chat_stream.platform
|
||
)
|
||
placeholder_msg_info = BaseMessageInfo(
|
||
message_id=placeholder_id,
|
||
platform=self.chat_stream.platform,
|
||
group_info=self.chat_stream.group_info,
|
||
user_info=placeholder_user,
|
||
time=time.time(),
|
||
)
|
||
placeholder_msg_dict = {
|
||
"message_info": placeholder_msg_info.to_dict(),
|
||
"processed_plain_text": "[System Trigger Context]",
|
||
"raw_message": "",
|
||
"time": placeholder_msg_info.time,
|
||
}
|
||
anchor_message = MessageRecv(placeholder_msg_dict)
|
||
anchor_message.update_chat_stream(self.chat_stream)
|
||
logger.info(
|
||
f"{self.log_prefix} Created placeholder anchor message: ID={anchor_message.message_info.message_id}"
|
||
)
|
||
return anchor_message
|
||
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} Error getting/creating anchor message: {e}")
|
||
logger.error(traceback.format_exc())
|
||
return None
|
||
|
||
# --- 发送器 (Sender) --- #
|
||
async def _sender(
|
||
self,
|
||
thinking_id: str,
|
||
anchor_message: MessageRecv,
|
||
response_set: List[str],
|
||
send_emoji: str, # Emoji query decided by planner or tools
|
||
):
|
||
"""
|
||
发送器 (Sender): 使用 HeartFCSender 实例发送生成的回复。
|
||
处理相关的操作，如发送表情和更新关系。
|
||
"""
|
||
logger.info(f"{self.log_prefix}开始发送回复 (使用 HeartFCSender)")
|
||
|
||
first_bot_msg: Optional[MessageSending] = None
|
||
try:
|
||
# _send_response_messages 现在将使用 self.sender 内部处理注册和发送
|
||
# 它需要负责创建 MessageThinking 和 MessageSending 对象
|
||
# 并调用 self.sender.register_thinking 和 self.sender.type_and_send_message
|
||
first_bot_msg = await self._send_response_messages(
|
||
anchor_message=anchor_message, response_set=response_set, thinking_id=thinking_id
|
||
)
|
||
|
||
if first_bot_msg:
|
||
# --- 处理关联表情(如果指定) --- #
|
||
if send_emoji:
|
||
logger.info(f"{self.log_prefix}正在发送关联表情: '{send_emoji}'")
|
||
# 优先使用 first_bot_msg 作为锚点，否则回退到原始锚点
|
||
emoji_anchor = first_bot_msg
|
||
await self._handle_emoji(emoji_anchor, response_set, send_emoji)
|
||
else:
|
||
# 如果 _send_response_messages 返回 None，表示在发送前就失败或没有消息可发送
|
||
logger.warning(
|
||
f"{self.log_prefix}[Sender-{thinking_id}] 未能发送任何回复消息 (_send_response_messages 返回 None)。"
|
||
)
|
||
# 这里可能不需要抛出异常，取决于 _send_response_messages 的具体实现
|
||
|
||
except Exception as e:
|
||
# 异常现在由 type_and_send_message 内部处理日志，这里只记录发送流程失败
|
||
logger.error(f"{self.log_prefix}[Sender-{thinking_id}] 发送回复过程中遇到错误: {e}")
|
||
# 思考状态应已在 type_and_send_message 的 finally 块中清理
|
||
# 可以选择重新抛出或根据业务逻辑处理
|
||
# raise RuntimeError(f"发送回复失败: {e}") from e
|
||
|
||
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")
|
||
|
||
async def _build_replan_prompt(self, action: str, reasoning: str) -> str:
|
||
"""构建 Replanner LLM 的提示词"""
|
||
prompt = (await global_prompt_manager.get_prompt_async("replan_prompt")).format(
|
||
action=action,
|
||
reasoning=reasoning,
|
||
)
|
||
|
||
# 在记录循环日志前检查关闭标志
|
||
if not self._shutting_down:
|
||
self._current_cycle.complete_cycle()
|
||
self._cycle_history.append(self._current_cycle)
|
||
|
||
# 记录循环信息和计时器结果
|
||
timer_strings = []
|
||
for name, elapsed in self._current_cycle.timers.items():
|
||
formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
|
||
timer_strings.append(f"{name}: {formatted_time}")
|
||
|
||
logger.debug(
|
||
f"{self.log_prefix} 第 #{self._current_cycle.cycle_id}次思考完成,"
|
||
f"耗时: {self._current_cycle.end_time - self._current_cycle.start_time:.2f}秒, "
|
||
f"动作: {self._current_cycle.action_type}"
|
||
+ (f"\n计时器详情: {'; '.join(timer_strings)}" if timer_strings else "")
|
||
)
|
||
|
||
return prompt
|
||
|
||
async def _build_planner_prompt(
|
||
self,
|
||
observed_messages_str: str,
|
||
current_mind: Optional[str],
|
||
structured_info: Dict[str, Any],
|
||
replan_prompt: str,
|
||
) -> str:
|
||
"""构建 Planner LLM 的提示词"""
|
||
try:
|
||
# 准备结构化信息块
|
||
structured_info_block = ""
|
||
if structured_info:
|
||
structured_info_block = f"以下是一些额外的信息：\n{structured_info}\n"
|
||
|
||
# 准备聊天内容块
|
||
chat_content_block = ""
|
||
if observed_messages_str:
|
||
chat_content_block = "观察到的最新聊天内容如下：\n---\n"
|
||
chat_content_block += observed_messages_str
|
||
chat_content_block += "\n---"
|
||
else:
|
||
chat_content_block = "当前没有观察到新的聊天内容。\n"
|
||
|
||
# 准备当前思维块
|
||
current_mind_block = ""
|
||
if current_mind:
|
||
current_mind_block = f"{current_mind}"
|
||
else:
|
||
current_mind_block = "[没有特别的想法]"
|
||
|
||
# 准备循环信息块 (分析最近的活动循环)
|
||
recent_active_cycles = []
|
||
for cycle in reversed(self._cycle_history):
|
||
# 只关心实际执行了动作的循环
|
||
if cycle.action_taken:
|
||
recent_active_cycles.append(cycle)
|
||
# 最多找最近的3个活动循环
|
||
if len(recent_active_cycles) == 3:
|
||
break
|
||
|
||
cycle_info_block = ""
|
||
consecutive_text_replies = 0
|
||
responses_for_prompt = []
|
||
|
||
# 检查这最近的活动循环中有多少是连续的文本回复 (从最近的开始看)
|
||
for cycle in recent_active_cycles:
|
||
if cycle.action_type == "text_reply":
|
||
consecutive_text_replies += 1
|
||
# 获取回复内容，如果不存在则返回'[空回复]'
|
||
response_text = cycle.response_info.get("response_text", [])
|
||
# 使用简单的 join 来格式化回复内容列表
|
||
formatted_response = "[空回复]" if not response_text else " ".join(response_text)
|
||
responses_for_prompt.append(formatted_response)
|
||
else:
|
||
# 一旦遇到非文本回复，连续性中断
|
||
break
|
||
|
||
# 根据连续文本回复的数量构建提示信息
|
||
# 注意: responses_for_prompt 列表是从最近到最远排序的
|
||
if consecutive_text_replies >= 3: # 如果最近的三个活动都是文本回复
|
||
cycle_info_block = f'你已经连续回复了三条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"，第三近: "{responses_for_prompt[2]}"）。你回复的有点多了，请注意'
|
||
elif consecutive_text_replies == 2: # 如果最近的两个活动是文本回复
|
||
cycle_info_block = f'你已经连续回复了两条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"），请注意'
|
||
elif consecutive_text_replies == 1: # 如果最近的一个活动是文本回复
|
||
cycle_info_block = f'你刚刚已经回复一条消息（内容: "{responses_for_prompt[0]}"）'
|
||
|
||
# 包装提示块，增加可读性，即使没有连续回复也给个标记
|
||
if cycle_info_block:
|
||
cycle_info_block = f"\n【近期回复历史】\n{cycle_info_block}\n"
|
||
else:
|
||
# 如果最近的活动循环不是文本回复，或者没有活动循环
|
||
cycle_info_block = "\n【近期回复历史】\n(最近没有连续文本回复)\n"
|
||
|
||
individuality = Individuality.get_instance()
|
||
prompt_personality = individuality.get_prompt(x_person=2, level=2)
|
||
|
||
# 获取提示词模板并填充数据
|
||
prompt = (await global_prompt_manager.get_prompt_async("planner_prompt")).format(
|
||
bot_name=global_config.BOT_NICKNAME,
|
||
prompt_personality=prompt_personality,
|
||
structured_info_block=structured_info_block,
|
||
chat_content_block=chat_content_block,
|
||
current_mind_block=current_mind_block,
|
||
replan=replan_prompt,
|
||
cycle_info_block=cycle_info_block,
|
||
)
|
||
|
||
return prompt
|
||
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix}[Planner] 构建提示词时出错: {e}")
|
||
logger.error(traceback.format_exc())
|
||
return ""
|
||
|
||
# --- 回复器 (Replier) 的定义 --- #
|
||
async def _replier_work(
|
||
self,
|
||
reason: str,
|
||
anchor_message: MessageRecv,
|
||
thinking_id: str,
|
||
) -> Optional[List[str]]:
|
||
"""
|
||
回复器 (Replier): 核心逻辑，负责生成回复文本。
|
||
(已整合原 HeartFCGenerator 的功能)
|
||
"""
|
||
try:
|
||
# 1. 获取情绪影响因子并调整模型温度
|
||
arousal_multiplier = MoodManager.get_instance().get_arousal_multiplier()
|
||
current_temp = global_config.llm_normal["temp"] * arousal_multiplier
|
||
self.model_normal.temperature = current_temp # 动态调整温度
|
||
|
||
# 2. 获取信息捕捉器
|
||
info_catcher = info_catcher_manager.get_info_catcher(thinking_id)
|
||
|
||
# 3. 构建 Prompt
|
||
with Timer("构建Prompt", {}): # 内部计时器，可选保留
|
||
prompt = await prompt_builder.build_prompt(
|
||
build_mode="focus",
|
||
reason=reason,
|
||
current_mind_info=self.sub_mind.current_mind,
|
||
structured_info=self.sub_mind.structured_info,
|
||
message_txt="", # 似乎是固定的空字符串
|
||
sender_name="", # 似乎是固定的空字符串
|
||
chat_stream=anchor_message.chat_stream,
|
||
)
|
||
|
||
# 4. 调用 LLM 生成回复
|
||
content = None
|
||
reasoning_content = None
|
||
model_name = "unknown_model"
|
||
try:
|
||
with Timer("LLM生成", {}): # 内部计时器，可选保留
|
||
content, reasoning_content, model_name = await self.model_normal.generate_response(prompt)
|
||
logger.info(f"{self.log_prefix}[Replier-{thinking_id}]\\nPrompt:\\n{prompt}\\n生成回复: {content}\\n")
|
||
# 捕捉 LLM 输出信息
|
||
info_catcher.catch_after_llm_generated(
|
||
prompt=prompt, response=content, reasoning_content=reasoning_content, model_name=model_name
|
||
)
|
||
|
||
except Exception as llm_e:
|
||
# 精简报错信息
|
||
logger.error(f"{self.log_prefix}[Replier-{thinking_id}] LLM 生成失败: {llm_e}")
|
||
return None # LLM 调用失败则无法生成回复
|
||
|
||
# 5. 处理 LLM 响应
|
||
if not content:
|
||
logger.warning(f"{self.log_prefix}[Replier-{thinking_id}] LLM 生成了空内容。")
|
||
return None
|
||
|
||
with Timer("处理响应", {}): # 内部计时器，可选保留
|
||
processed_response = process_llm_response(content)
|
||
|
||
if not processed_response:
|
||
logger.warning(f"{self.log_prefix}[Replier-{thinking_id}] 处理后的回复为空。")
|
||
return None
|
||
|
||
return processed_response
|
||
|
||
except Exception as e:
|
||
# 更通用的错误处理，精简信息
|
||
logger.error(f"{self.log_prefix}[Replier-{thinking_id}] 回复生成意外失败: {e}")
|
||
# logger.error(traceback.format_exc()) # 可以取消注释这行以在调试时查看完整堆栈
|
||
return None
|
||
|
||
# --- Methods moved from HeartFCController start ---
|
||
async def _create_thinking_message(self, anchor_message: Optional[MessageRecv]) -> Optional[str]:
|
||
"""创建思考消息 (尝试锚定到 anchor_message)"""
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self.log_prefix} 无法创建思考消息，缺少有效的锚点消息或聊天流。")
|
||
return None
|
||
|
||
chat = anchor_message.chat_stream
|
||
messageinfo = anchor_message.message_info
|
||
bot_user_info = UserInfo(
|
||
user_id=global_config.BOT_QQ,
|
||
user_nickname=global_config.BOT_NICKNAME,
|
||
platform=messageinfo.platform,
|
||
)
|
||
|
||
thinking_time_point = round(time.time(), 2)
|
||
thinking_id = "mt" + str(thinking_time_point)
|
||
thinking_message = MessageThinking(
|
||
message_id=thinking_id,
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
reply=anchor_message, # 回复的是锚点消息
|
||
thinking_start_time=thinking_time_point,
|
||
)
|
||
# Access MessageManager directly
|
||
await self.heart_fc_sender.register_thinking(thinking_message)
|
||
return thinking_id
|
||
|
||
async def _send_response_messages(
|
||
self, anchor_message: Optional[MessageRecv], response_set: List[str], thinking_id: str
|
||
) -> Optional[MessageSending]:
|
||
"""发送回复消息 (尝试锚定到 anchor_message)，使用 HeartFCSender"""
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self.log_prefix} 无法发送回复，缺少有效的锚点消息或聊天流。")
|
||
return None
|
||
|
||
chat = anchor_message.chat_stream
|
||
chat_id = chat.stream_id
|
||
stream_name = chat_manager.get_stream_name(chat_id) or chat_id # 获取流名称用于日志
|
||
|
||
# 检查思考过程是否仍在进行，并获取开始时间
|
||
thinking_start_time = await self.heart_fc_sender.get_thinking_start_time(chat_id, thinking_id)
|
||
|
||
if thinking_start_time is None:
|
||
logger.warning(f"[{stream_name}] {thinking_id} 思考过程未找到或已结束，无法发送回复。")
|
||
return None
|
||
|
||
# 记录锚点消息ID和回复文本（在发送前记录）
|
||
self._current_cycle.set_response_info(
|
||
response_text=response_set, anchor_message_id=anchor_message.message_info.message_id
|
||
)
|
||
|
||
mark_head = False
|
||
first_bot_msg: Optional[MessageSending] = None
|
||
reply_message_ids = [] # 记录实际发送的消息ID
|
||
bot_user_info = UserInfo(
|
||
user_id=global_config.BOT_QQ,
|
||
user_nickname=global_config.BOT_NICKNAME,
|
||
platform=anchor_message.message_info.platform,
|
||
)
|
||
|
||
for i, msg_text in enumerate(response_set):
|
||
# 为每个消息片段生成唯一ID
|
||
part_message_id = f"{thinking_id}_{i}"
|
||
message_segment = Seg(type="text", data=msg_text)
|
||
bot_message = MessageSending(
|
||
message_id=part_message_id, # 使用片段的唯一ID
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
sender_info=anchor_message.message_info.user_info,
|
||
message_segment=message_segment,
|
||
reply=anchor_message, # 回复原始锚点
|
||
is_head=not mark_head,
|
||
is_emoji=False,
|
||
thinking_start_time=thinking_start_time, # 传递原始思考开始时间
|
||
)
|
||
try:
|
||
if not mark_head:
|
||
mark_head = True
|
||
first_bot_msg = bot_message # 保存第一个成功发送的消息对象
|
||
await self.heart_fc_sender.type_and_send_message(bot_message, type=False)
|
||
else:
|
||
await self.heart_fc_sender.type_and_send_message(bot_message, type=True)
|
||
|
||
reply_message_ids.append(part_message_id) # 记录我们生成的ID
|
||
|
||
except Exception as e:
|
||
logger.error(
|
||
f"{self.log_prefix}[Sender-{thinking_id}] 发送回复片段 {i} ({part_message_id}) 时失败: {e}"
|
||
)
|
||
# 这里可以选择是继续发送下一个片段还是中止
|
||
|
||
# 在尝试发送完所有片段后，完成原始的 thinking_id 状态
|
||
try:
|
||
await self.heart_fc_sender.complete_thinking(chat_id, thinking_id)
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix}[Sender-{thinking_id}] 完成思考状态 {thinking_id} 时出错: {e}")
|
||
|
||
self._current_cycle.set_response_info(
|
||
response_text=response_set, # 保留原始文本
|
||
anchor_message_id=anchor_message.message_info.message_id, # 保留锚点ID
|
||
reply_message_ids=reply_message_ids, # 添加实际发送的ID列表
|
||
)
|
||
|
||
return first_bot_msg # 返回第一个成功发送的消息对象
|
||
|
||
async def _handle_emoji(self, anchor_message: Optional[MessageRecv], response_set: List[str], send_emoji: str = ""):
|
||
"""处理表情包 (尝试锚定到 anchor_message)，使用 HeartFCSender"""
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self.log_prefix} 无法处理表情包，缺少有效的锚点消息或聊天流。")
|
||
return
|
||
|
||
chat = anchor_message.chat_stream
|
||
|
||
emoji_raw = await emoji_manager.get_emoji_for_text(send_emoji)
|
||
|
||
if emoji_raw:
|
||
emoji_path, description = emoji_raw
|
||
|
||
emoji_cq = image_path_to_base64(emoji_path)
|
||
thinking_time_point = round(time.time(), 2) # 用于唯一ID
|
||
message_segment = Seg(type="emoji", data=emoji_cq)
|
||
bot_user_info = UserInfo(
|
||
user_id=global_config.BOT_QQ,
|
||
user_nickname=global_config.BOT_NICKNAME,
|
||
platform=anchor_message.message_info.platform,
|
||
)
|
||
bot_message = MessageSending(
|
||
message_id="me" + str(thinking_time_point), # 表情消息的唯一ID
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
sender_info=anchor_message.message_info.user_info,
|
||
message_segment=message_segment,
|
||
reply=anchor_message, # 回复原始锚点
|
||
is_head=False, # 表情通常不是头部消息
|
||
is_emoji=True,
|
||
# 不需要 thinking_start_time
|
||
)
|
||
|
||
try:
|
||
await self.heart_fc_sender.send_and_store(bot_message)
|
||
except Exception as e:
|
||
logger.error(f"{self.log_prefix} 发送表情包 {bot_message.message_info.message_id} 时失败: {e}")
|
||
|
||
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]
|
||
|
||
def get_last_cycle_info(self) -> Optional[Dict[str, Any]]:
|
||
"""获取最近一个循环的信息"""
|
||
if self._cycle_history:
|
||
return self._cycle_history[-1].to_dict()
|
||
return None
|