791 lines
39 KiB
Python
791 lines
39 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
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from src.plugins.chat.message import MessageRecv, BaseMessageInfo, MessageThinking, MessageSending
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from src.plugins.chat.message import MessageSet, 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 import get_module_logger, LogConfig, PFC_STYLE_CONFIG # 引入 DEFAULT_CONFIG
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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_calculater import Timer # <--- Import Timer
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from src.plugins.heartFC_chat.heartFC_generator import HeartFCGenerator
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from src.do_tool.tool_use import ToolUser
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from ..chat.message_sender import message_manager # <-- Import the global manager
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from src.plugins.chat.emoji_manager import emoji_manager
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from src.plugins.utils.json_utils import process_llm_tool_response # 导入新的JSON工具
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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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# --- End import ---
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INITIAL_DURATION = 60.0
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# 定义日志配置 (使用 loguru 格式)
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interest_log_config = LogConfig(
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console_format=PFC_STYLE_CONFIG["console_format"], # 使用默认控制台格式
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file_format=PFC_STYLE_CONFIG["file_format"], # 使用默认文件格式
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)
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logger = get_module_logger("HeartFCLoop", config=interest_log_config) # Logger Name Changed
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PLANNER_TOOL_DEFINITION = [
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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": ["no_reply", "text_reply", "emoji_reply"],
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"description": "决定采取的行动：'no_reply'(不回复), 'text_reply'(文本回复, 可选附带表情) 或 'emoji_reply'(仅表情回复)。",
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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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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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sub_mind: SubMind,
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observations: Observation
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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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"""
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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: Observation = observations # 关联的观察
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# 初始化状态控制
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self._initialized = False # 是否已初始化标志
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self._processing_lock = asyncio.Lock() # 处理锁(确保单次Plan-Replier-Sender周期)
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# 依赖注入存储
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self.gpt_instance = HeartFCGenerator() # 文本回复生成器
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self.tool_user = ToolUser() # 工具使用实例
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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_normal,
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temperature=global_config.llm_normal["temp"],
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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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def _get_log_prefix(self) -> str:
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"""获取日志前缀，包含可读的流名称"""
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stream_name = chat_manager.get_stream_name(self.stream_id) or self.stream_id
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return f"[{stream_name}]"
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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和sub_hf。
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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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log_prefix = self._get_log_prefix() # 获取前缀
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try:
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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"{log_prefix} 获取ChatStream失败。")
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return False
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self._initialized = True
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logger.info(f"麦麦感觉到了，激发了HeartFChatting{log_prefix} 初始化成功。")
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return True
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except Exception as e:
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logger.error(f"{log_prefix} 初始化失败: {e}")
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logger.error(traceback.format_exc())
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return False
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async def start(self):
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"""
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显式尝试启动 HeartFChatting 的主循环。
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如果循环未激活，则启动循环。
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"""
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log_prefix = self._get_log_prefix()
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if not self._initialized:
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if not await self._initialize():
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logger.error(f"{log_prefix} 无法启动循环: 初始化失败。")
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return
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logger.info(f"{log_prefix} 尝试显式启动循环...")
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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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log_prefix = self._get_log_prefix()
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should_start_loop = False
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# 直接检查是否激活，无需检查计时器
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if not self._loop_active:
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should_start_loop = True
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self._loop_active = True # 标记为活动，防止重复启动
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if should_start_loop:
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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"{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"{log_prefix} 循环未激活，启动主循环...")
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# 创建新的循环任务
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self._loop_task = asyncio.create_task(self._run_pf_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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# else:
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# logger.trace(f"{log_prefix} 不需要启动循环（已激活）") # 可以取消注释以进行调试
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def _handle_loop_completion(self, task: asyncio.Task):
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"""当 _run_pf_loop 任务完成时执行的回调。"""
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log_prefix = self._get_log_prefix()
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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"{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"{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"{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"{log_prefix} HeartFChatting: 处理锁在循环结束时仍被锁定，强制释放。")
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self._processing_lock.release()
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async def _run_pf_loop(self):
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"""
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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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管理每个循环周期的处理锁。
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"""
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log_prefix = self._get_log_prefix()
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logger.info(f"{log_prefix} HeartFChatting: 麦麦打算好好聊聊 (进入专注模式)")
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try:
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thinking_id = ""
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while True: # Loop indefinitely until cancelled
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cycle_timers = {} # <--- Initialize timers dict for this cycle
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# Access MessageManager directly
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if message_manager.check_if_sending_message_exist(self.stream_id, thinking_id):
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# logger.info(f"{log_prefix} HeartFChatting: 麦麦还在发消息，等会再规划")
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await asyncio.sleep(1)
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continue
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else:
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# logger.info(f"{log_prefix} HeartFChatting: 麦麦不发消息了，开始规划")
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pass
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# 记录循环周期开始时间，用于计时和休眠计算
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loop_cycle_start_time = time.monotonic()
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action_taken_this_cycle = False
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acquired_lock = False
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planner_start_db_time = 0.0 # 初始化
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try:
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with Timer("Total Cycle", cycle_timers) as _total_timer: # <--- Start total cycle timer
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# Use try_acquire pattern or timeout?
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await self._processing_lock.acquire()
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acquired_lock = True
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# logger.debug(f"{log_prefix} HeartFChatting: 循环获取到处理锁")
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# 在规划前记录数据库时间戳
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planner_start_db_time = time.time()
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# --- Planner --- #
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planner_result = {}
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with Timer("Planner", cycle_timers): # <--- Start Planner timer
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planner_result = await self._planner()
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action = planner_result.get("action", "error")
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reasoning = planner_result.get("reasoning", "Planner did not provide reasoning.")
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emoji_query = planner_result.get("emoji_query", "")
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llm_error = planner_result.get("llm_error", False)
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if llm_error:
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logger.error(f"{log_prefix} Planner LLM 失败，跳过本周期回复尝试。理由: {reasoning}")
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# Optionally add a longer sleep?
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action_taken_this_cycle = False # Ensure no action is counted
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# Continue to sleep logic
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elif action == "text_reply":
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logger.debug(f"{log_prefix} HeartFChatting: 麦麦决定回复文本. 理由: {reasoning}")
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action_taken_this_cycle = True
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anchor_message = await self._get_anchor_message()
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if not anchor_message:
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logger.error(f"{log_prefix} 循环: 无法获取锚点消息用于回复. 跳过周期.")
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else:
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# --- Create Thinking Message (Moved) ---
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thinking_id = await self._create_thinking_message(anchor_message)
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if not thinking_id:
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logger.error(f"{log_prefix} 循环: 无法创建思考ID. 跳过周期.")
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else:
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replier_result = None
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try:
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# --- Replier Work --- #
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with Timer("Replier", cycle_timers): # <--- Start Replier timer
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replier_result = await self._replier_work(
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anchor_message=anchor_message,
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thinking_id=thinking_id,
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reason=reasoning,
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)
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except Exception as e_replier:
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logger.error(f"{log_prefix} 循环: 回复器工作失败: {e_replier}")
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# self._cleanup_thinking_message(thinking_id) <-- Remove cleanup call
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if replier_result:
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# --- Sender Work --- #
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try:
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with Timer("Sender", cycle_timers): # <--- Start Sender timer
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await self._sender(
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thinking_id=thinking_id,
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anchor_message=anchor_message,
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response_set=replier_result,
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send_emoji=emoji_query,
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)
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# logger.info(f"{log_prefix} 循环: 发送器完成成功.")
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except Exception as e_sender:
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logger.error(f"{log_prefix} 循环: 发送器失败: {e_sender}")
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# _sender should handle cleanup, but double check
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# self._cleanup_thinking_message(thinking_id) <-- Remove cleanup call
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else:
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logger.warning(f"{log_prefix} 循环: 回复器未产生结果. 跳过发送.")
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# self._cleanup_thinking_message(thinking_id) <-- Remove cleanup call
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elif action == "emoji_reply":
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logger.info(
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f"{log_prefix} HeartFChatting: 麦麦决定回复表情 ('{emoji_query}'). 理由: {reasoning}"
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)
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action_taken_this_cycle = True
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anchor = await self._get_anchor_message()
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if anchor:
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try:
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# --- Handle Emoji (Moved) --- #
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with Timer("Emoji Handler", cycle_timers): # <--- Start Emoji timer
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await self._handle_emoji(anchor, [], emoji_query)
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except Exception as e_emoji:
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logger.error(f"{log_prefix} 循环: 发送表情失败: {e_emoji}")
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else:
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logger.warning(f"{log_prefix} 循环: 无法发送表情, 无法获取锚点.")
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action_taken_this_cycle = True # 即使发送失败，Planner 也决策了动作
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elif action == "no_reply":
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logger.info(f"{log_prefix} HeartFChatting: 麦麦决定不回复. 原因: {reasoning}")
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action_taken_this_cycle = False # 标记为未执行动作
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# --- 新增：等待新消息 ---
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logger.debug(f"{log_prefix} HeartFChatting: 开始等待新消息 (自 {planner_start_db_time})...")
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observation = None
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observation = self.observations[0]
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if observation:
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with Timer("Wait New Msg", cycle_timers): # <--- Start Wait timer
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wait_start_time = time.monotonic()
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while True:
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# 检查是否有新消息
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has_new = await observation.has_new_messages_since(planner_start_db_time)
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if has_new:
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logger.info(f"{log_prefix} HeartFChatting: 检测到新消息，结束等待。")
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break # 收到新消息，退出等待
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# 检查等待是否超时（例如，防止无限等待）
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if time.monotonic() - wait_start_time > 60: # 等待60秒示例
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logger.warning(f"{log_prefix} HeartFChatting: 等待新消息超时（60秒）。")
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break # 超时退出
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# 等待一段时间再检查
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try:
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await asyncio.sleep(1.5) # 检查间隔
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except asyncio.CancelledError:
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logger.info(f"{log_prefix} 等待新消息的 sleep 被中断。")
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raise # 重新抛出取消错误，以便外层循环处理
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else:
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logger.warning(
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f"{log_prefix} HeartFChatting: 无法获取 Observation 实例，无法等待新消息。"
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)
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# --- 等待结束 ---
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elif action == "error": # Action specifically set to error by planner
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logger.error(f"{log_prefix} HeartFChatting: Planner返回错误状态. 原因: {reasoning}")
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action_taken_this_cycle = False
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else: # Unknown action from planner
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logger.warning(
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f"{log_prefix} HeartFChatting: Planner返回未知动作 '{action}'. 原因: {reasoning}"
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)
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action_taken_this_cycle = False
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# --- Print Timer Results --- #
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if cycle_timers: # 先检查cycle_timers是否非空
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timer_strings = []
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for name, elapsed in cycle_timers.items():
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# 直接格式化存储在字典中的浮点数 elapsed
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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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if timer_strings: # 如果有有效计时器数据才打印
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logger.debug(f"{log_prefix} 该次决策耗时: {'; '.join(timer_strings)}")
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# --- Timer Decrement Removed --- #
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cycle_duration = time.monotonic() - loop_cycle_start_time
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except Exception as e_cycle:
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logger.error(f"{log_prefix} 循环周期执行时发生错误: {e_cycle}")
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logger.error(traceback.format_exc())
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if acquired_lock and self._processing_lock.locked():
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self._processing_lock.release()
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acquired_lock = False
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logger.warning(f"{log_prefix} 由于循环周期中的错误释放了处理锁.")
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finally:
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if acquired_lock:
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self._processing_lock.release()
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# logger.trace(f"{log_prefix} 循环释放了处理锁.") # Reduce noise
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if cycle_duration > 0.1:
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logger.debug(f"{log_prefix} HeartFChatting: 周期耗时 {cycle_duration:.2f}s.")
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# --- Delay --- #
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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 < 1.5:
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sleep_duration = 1.5 - cycle_duration
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elif cycle_duration < 0.2: # Keep minimal sleep even after action
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sleep_duration = 0.2
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if sleep_duration > 0:
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# logger.debug(f"{log_prefix} Sleeping for {sleep_duration:.2f}s")
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await asyncio.sleep(sleep_duration)
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|
||
except asyncio.CancelledError:
|
||
logger.info(f"{log_prefix} Sleep interrupted, loop likely cancelling.")
|
||
break # Exit loop immediately on cancellation
|
||
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{log_prefix} HeartFChatting: 麦麦的聊天主循环被取消了")
|
||
except Exception as e_loop_outer:
|
||
logger.error(f"{log_prefix} HeartFChatting: 麦麦的聊天主循环意外出错: {e_loop_outer}")
|
||
logger.error(traceback.format_exc())
|
||
finally:
|
||
# State reset is primarily handled by _handle_loop_completion callback
|
||
logger.info(f"{log_prefix} HeartFChatting: 麦麦的聊天主循环结束。")
|
||
|
||
async def _planner(self) -> Dict[str, Any]:
|
||
"""
|
||
规划器 (Planner): 使用LLM根据上下文决定是否和如何回复。
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
observed_messages: List[dict] = []
|
||
|
||
current_mind: Optional[str] = None
|
||
llm_error = False
|
||
|
||
try:
|
||
observation = self.observations[0]
|
||
await observation.observe()
|
||
observed_messages = observation.talking_message
|
||
observed_messages_str = observation.talking_message_str
|
||
except Exception as e:
|
||
logger.error(f"{log_prefix}[Planner] 获取观察信息时出错: {e}")
|
||
|
||
try:
|
||
current_mind, _past_mind = await self.sub_mind.do_thinking_before_reply()
|
||
except Exception as e_subhf:
|
||
logger.error(f"{log_prefix}[Planner] SubHeartflow 思考失败: {e_subhf}")
|
||
current_mind = "[思考时出错]"
|
||
|
||
# --- 使用 LLM 进行决策 --- #
|
||
action = "no_reply" # 默认动作
|
||
emoji_query = "" # 默认表情查询
|
||
reasoning = "默认决策或获取决策失败"
|
||
llm_error = False # LLM错误标志
|
||
|
||
try:
|
||
prompt = await self._build_planner_prompt(observed_messages_str, current_mind, self.sub_mind.structured_info)
|
||
payload = {
|
||
"model": self.planner_llm.model_name,
|
||
"messages": [{"role": "user", "content": prompt}],
|
||
"tools": PLANNER_TOOL_DEFINITION,
|
||
"tool_choice": {"type": "function", "function": {"name": "decide_reply_action"}},
|
||
}
|
||
|
||
# 执行LLM请求
|
||
try:
|
||
response = await self.planner_llm._execute_request(
|
||
endpoint="/chat/completions", payload=payload, prompt=prompt
|
||
)
|
||
except Exception as req_e:
|
||
logger.error(f"{log_prefix}[Planner] LLM请求执行失败: {req_e}")
|
||
return {
|
||
"action": "error",
|
||
"reasoning": f"LLM请求执行失败: {req_e}",
|
||
"emoji_query": "",
|
||
"current_mind": current_mind,
|
||
"observed_messages": observed_messages,
|
||
"llm_error": True,
|
||
}
|
||
|
||
# 使用辅助函数处理工具调用响应
|
||
success, arguments, error_msg = process_llm_tool_response(
|
||
response, expected_tool_name="decide_reply_action", log_prefix=f"{log_prefix}[Planner] "
|
||
)
|
||
|
||
if success:
|
||
# 提取决策参数
|
||
action = arguments.get("action", "no_reply")
|
||
reasoning = arguments.get("reasoning", "未提供理由")
|
||
emoji_query = arguments.get("emoji_query", "")
|
||
|
||
# 记录决策结果
|
||
logger.debug(f"{log_prefix}[Planner] 决策结果: {action}, 理由: {reasoning}, 表情查询: '{emoji_query}'")
|
||
else:
|
||
# 处理工具调用失败
|
||
logger.warning(f"{log_prefix}[Planner] {error_msg}")
|
||
action = "error"
|
||
reasoning = error_msg
|
||
llm_error = True
|
||
|
||
except Exception as llm_e:
|
||
logger.error(f"{log_prefix}[Planner] Planner LLM处理过程中出错: {llm_e}")
|
||
logger.error(traceback.format_exc()) # 记录完整堆栈以便调试
|
||
action = "error"
|
||
reasoning = f"LLM处理失败: {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._get_log_prefix()} Created placeholder anchor message: ID={anchor_message.message_info.message_id}"
|
||
)
|
||
return anchor_message
|
||
|
||
except Exception as e:
|
||
logger.error(f"{self._get_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): 使用本类的方法发送生成的回复。
|
||
处理相关的操作，如发送表情和更新关系。
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
|
||
first_bot_msg: Optional[MessageSending] = None
|
||
# 尝试发送回复消息
|
||
first_bot_msg = await self._send_response_messages(anchor_message, response_set, thinking_id)
|
||
if first_bot_msg:
|
||
# --- 处理关联表情(如果指定) --- #
|
||
if send_emoji:
|
||
logger.info(f"{log_prefix}[Sender-{thinking_id}] 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 if first_bot_msg else anchor_message
|
||
await self._handle_emoji(emoji_anchor, response_set, send_emoji)
|
||
|
||
else:
|
||
# logger.warning(f"{log_prefix}[Sender-{thinking_id}] 发送回复失败(_send_response_messages返回None)。思考消息{thinking_id}可能已被移除。")
|
||
# 无需清理，因为_send_response_messages返回None意味着已处理/已删除
|
||
raise RuntimeError("发送回复失败，_send_response_messages返回None")
|
||
|
||
async def shutdown(self):
|
||
"""优雅关闭HeartFChatting实例，取消活动循环任务"""
|
||
log_prefix = self._get_log_prefix()
|
||
logger.info(f"{log_prefix} 正在关闭HeartFChatting...")
|
||
|
||
# 取消循环任务
|
||
if self._loop_task and not self._loop_task.done():
|
||
logger.info(f"{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"{log_prefix} HeartFChatting循环任务已取消")
|
||
except (asyncio.CancelledError, asyncio.TimeoutError):
|
||
pass
|
||
except Exception as e:
|
||
logger.error(f"{log_prefix} 取消循环任务出错: {e}")
|
||
else:
|
||
logger.info(f"{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"{log_prefix} 已释放处理锁")
|
||
|
||
logger.info(f"{log_prefix} HeartFChatting关闭完成")
|
||
|
||
async def _build_planner_prompt(
|
||
self, observed_messages_str: str, current_mind: Optional[str], structured_info: Dict[str, Any]
|
||
) -> str:
|
||
"""构建 Planner LLM 的提示词"""
|
||
|
||
prompt = f"你的名字是 {global_config.BOT_NICKNAME}。是一个女大二学生，正在QQ聊天，正在决定是否以及如何回应当前的聊天。\n"
|
||
|
||
if structured_info:
|
||
prompt += f"以下是一些额外的信息：\n{structured_info}\n"
|
||
|
||
if observed_messages_str:
|
||
prompt += "观察到的最新聊天内容如下 (最近的消息在最后)：\n---\n"
|
||
prompt += observed_messages_str
|
||
prompt += "\n---"
|
||
else:
|
||
prompt += "当前没有观察到新的聊天内容。\n"
|
||
|
||
prompt += "\n看了以上内容，你产生的内心想法是："
|
||
if current_mind:
|
||
prompt += f"\n---\n{current_mind}\n---\n\n"
|
||
else:
|
||
prompt += " [没有特别的想法] \n\n"
|
||
|
||
prompt += (
|
||
"请结合你的内心想法和观察到的聊天内容，分析情况并使用 'decide_reply_action' 工具来决定你的最终行动。\n"
|
||
"决策依据：\n"
|
||
"1. 如果聊天内容无聊、与你无关、或者你的内心想法认为不适合回复（例如在讨论你不懂或不感兴趣的话题），选择 'no_reply'。\n"
|
||
"2. 如果聊天内容值得回应，且适合用文字表达（参考你的内心想法），选择 'text_reply'。如果你有情绪想表达，想在文字后追加一个表达情绪的表情，请同时提供 'emoji_query' (例如：'开心的'、'惊讶的')。\n"
|
||
"3. 如果聊天内容或你的内心想法适合用一个表情来回应（例如表示赞同、惊讶、无语等），选择 'emoji_reply' 并提供表情主题 'emoji_query'。\n"
|
||
"4. 如果最后一条消息是你自己发的，并且之后没有人回复你，通常选择 'no_reply'，除非有特殊原因需要追问。\n"
|
||
"5. 除非大家都在这么做，或者有特殊理由，否则不要重复别人刚刚说过的话或简单附和。\n"
|
||
"6. 表情包是用来表达情绪的，不要直接回复或评价别人的表情包，而是根据对话内容和情绪选择是否用表情回应。\n"
|
||
"7. 如果观察到的内容只有你自己的发言，选择 'no_reply'。\n"
|
||
"8. 不要回复你自己的话，不要把自己的话当做别人说的。\n"
|
||
"必须调用 'decide_reply_action' 工具并提供 'action' 和 'reasoning'。如果选择了 'emoji_reply' 或者选择了 'text_reply' 并想追加表情，则必须提供 'emoji_query'。"
|
||
)
|
||
|
||
return prompt
|
||
|
||
# --- 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): 核心逻辑用于生成回复。
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
response_set: Optional[List[str]] = None
|
||
try:
|
||
response_set = await self.gpt_instance.generate_response(
|
||
structured_info=self.sub_mind.structured_info,
|
||
current_mind_info=self.sub_mind.current_mind,
|
||
reason=reason,
|
||
message=anchor_message, # Pass anchor_message positionally (matches 'message' parameter)
|
||
thinking_id=thinking_id, # Pass thinking_id positionally
|
||
)
|
||
|
||
if not response_set:
|
||
logger.warning(f"{log_prefix}[Replier-{thinking_id}] LLM生成了一个空回复集。")
|
||
return None
|
||
|
||
# --- 准备并返回结果 --- #
|
||
# logger.info(f"{log_prefix}[Replier-{thinking_id}] 成功生成了回复集: {' '.join(response_set)[:50]}...")
|
||
return response_set
|
||
|
||
except Exception as e:
|
||
logger.error(f"{log_prefix}[Replier-{thinking_id}] Unexpected error in replier_work: {e}")
|
||
logger.error(traceback.format_exc())
|
||
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._get_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 message_manager.add_message(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)"""
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self._get_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
|
||
# Access MessageManager directly
|
||
container = await message_manager.get_container(chat.stream_id)
|
||
thinking_message = None
|
||
|
||
# 移除思考消息
|
||
for msg in container.messages[:]: # Iterate over a copy
|
||
if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
|
||
thinking_message = msg
|
||
container.messages.remove(msg) # Remove the message directly here
|
||
logger.debug(f"{self._get_log_prefix()} Removed thinking message {thinking_id} via iteration.")
|
||
break
|
||
|
||
if not thinking_message:
|
||
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id # 获取流名称
|
||
logger.warning(f"[{stream_name}] {thinking_id}，思考太久了，超时被移除")
|
||
return None
|
||
|
||
thinking_start_time = thinking_message.thinking_start_time
|
||
message_set = MessageSet(chat, thinking_id)
|
||
mark_head = False
|
||
first_bot_msg = None
|
||
bot_user_info = UserInfo(
|
||
user_id=global_config.BOT_QQ,
|
||
user_nickname=global_config.BOT_NICKNAME,
|
||
platform=anchor_message.message_info.platform,
|
||
)
|
||
for msg_text in response_set:
|
||
message_segment = Seg(type="text", data=msg_text)
|
||
bot_message = MessageSending(
|
||
message_id=thinking_id, # 使用 thinking_id 作为批次标识
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
sender_info=anchor_message.message_info.user_info, # 发送给锚点消息的用户
|
||
message_segment=message_segment,
|
||
reply=anchor_message, # 回复锚点消息
|
||
is_head=not mark_head,
|
||
is_emoji=False,
|
||
thinking_start_time=thinking_start_time,
|
||
)
|
||
if not mark_head:
|
||
mark_head = True
|
||
first_bot_msg = bot_message
|
||
message_set.add_message(bot_message)
|
||
|
||
# Access MessageManager directly
|
||
await message_manager.add_message(message_set)
|
||
return first_bot_msg
|
||
|
||
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)"""
|
||
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self._get_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
|
||
|
||
if send_emoji:
|
||
emoji_raw = await emoji_manager.get_emoji_for_text(send_emoji)
|
||
else:
|
||
emoji_text_source = "".join(response_set) if response_set else ""
|
||
emoji_raw = await emoji_manager.get_emoji_for_text(emoji_text_source)
|
||
|
||
if emoji_raw:
|
||
emoji_path, _description = emoji_raw
|
||
emoji_cq = image_path_to_base64(emoji_path)
|
||
thinking_time_point = round(time.time(), 2)
|
||
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), # 使用不同的 ID 前缀?
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
sender_info=anchor_message.message_info.user_info,
|
||
message_segment=message_segment,
|
||
reply=anchor_message, # 回复锚点消息
|
||
is_head=False,
|
||
is_emoji=True,
|
||
)
|
||
# Access MessageManager directly
|
||
await message_manager.add_message(bot_message)
|