mirror of https://github.com/Mai-with-u/MaiBot.git
792 lines
41 KiB
Python
792 lines
41 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, TYPE_CHECKING
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import json
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from ....config.config import global_config
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from ...chat.message import MessageRecv, BaseMessageInfo, MessageThinking, MessageSending
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from ...chat.chat_stream import ChatStream
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from ...message import UserInfo
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from src.heart_flow.heartflow import heartflow, SubHeartflow
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from src.plugins.chat.chat_stream import chat_manager
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from .messagesender import MessageManager
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from src.common.logger import get_module_logger, LogConfig, DEFAULT_CONFIG # 引入 DEFAULT_CONFIG
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from src.plugins.models.utils_model import LLMRequest
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from src.plugins.chat.utils import parse_text_timestamps
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from src.plugins.person_info.relationship_manager import relationship_manager
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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=DEFAULT_CONFIG["console_format"], # 使用默认控制台格式
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file_format=DEFAULT_CONFIG["file_format"], # 使用默认文件格式
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)
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logger = get_module_logger("PFChattingLoop", config=interest_log_config) # Logger Name Changed
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# Forward declaration for type hinting
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if TYPE_CHECKING:
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from .heartFC_chat import HeartFC_Chat
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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 PFChatting:
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"""
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Manages a continuous Plan-Filter-Check (now Plan-Replier-Sender) loop
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for generating replies within a specific chat stream, controlled by a timer.
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The loop runs as long as the timer > 0.
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"""
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def __init__(self, chat_id: str, heartfc_chat_instance: "HeartFC_Chat"):
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"""
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初始化PFChatting实例。
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Args:
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chat_id: The identifier for the chat stream (e.g., stream_id).
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heartfc_chat_instance: 访问共享资源和方法的主HeartFC_Chat实例。
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"""
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self.heartfc_chat = heartfc_chat_instance # 访问logger, gpt, tool_user, _send_response_messages等。
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self.stream_id: str = chat_id
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self.chat_stream: Optional[ChatStream] = None
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self.sub_hf: Optional[SubHeartflow] = None
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self._initialized = False
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self._init_lock = asyncio.Lock() # Ensure initialization happens only once
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self._processing_lock = asyncio.Lock() # 确保只有一个 Plan-Replier-Sender 周期在运行
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self._timer_lock = asyncio.Lock() # 用于安全更新计时器
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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",
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)
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# Internal state for loop control
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self._loop_timer: float = 0.0 # Remaining time for the loop in seconds
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self._loop_active: bool = False # Is the loop currently running?
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self._loop_task: Optional[asyncio.Task] = None # Stores the main loop task
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self._trigger_count_this_activation: int = 0 # Counts triggers within an active period
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self._initial_duration: float = 30.0 # 首次触发增加的时间
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self._last_added_duration: float = self._initial_duration # <--- 新增：存储上次增加的时间
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# Removed pending_replies as processing is now serial within the loop
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# self.pending_replies: Dict[str, PendingReply] = {}
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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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async with self._init_lock:
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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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# 子心流(SubHeartflow)可能初始不存在但后续会被创建
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# 在需要它的方法中应优雅处理其可能缺失的情况
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self.sub_hf = heartflow.get_subheartflow(self.stream_id)
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if not self.sub_hf:
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logger.warning(f"{log_prefix} 获取SubHeartflow失败。一些功能可能受限。")
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# 决定是否继续初始化。目前允许初始化。
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self._initialized = True
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logger.info(f"麦麦感觉到了，激发了PFChatting{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 add_time(self):
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"""
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为麦麦添加时间，麦麦有兴趣时，时间增加。
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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} 无法添加时间: 未初始化。")
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return
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async with self._timer_lock:
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duration_to_add: float = 0.0
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if not self._loop_active: # First trigger for this activation cycle
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duration_to_add = self._initial_duration # 使用初始值
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self._last_added_duration = duration_to_add # 更新上次增加的值
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self._trigger_count_this_activation = 1 # Start counting
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logger.info(
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f"{log_prefix} 麦麦有兴趣！ #{self._trigger_count_this_activation}. 麦麦打算聊： {duration_to_add:.2f}s."
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)
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else: # Loop is already active, apply 50% reduction
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self._trigger_count_this_activation += 1
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duration_to_add = self._last_added_duration * 0.5
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if duration_to_add < 0.5:
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duration_to_add = 0.5
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self._last_added_duration = duration_to_add # 更新上次增加的值
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else:
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self._last_added_duration = duration_to_add # 更新上次增加的值
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logger.info(
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f"{log_prefix} 麦麦兴趣增加！ #{self._trigger_count_this_activation}. 想继续聊： {duration_to_add:.2f}s,麦麦还能聊： {self._loop_timer:.1f}s."
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)
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# 添加计算出的时间
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new_timer_value = self._loop_timer + duration_to_add
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self._loop_timer = max(0, new_timer_value)
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if self._loop_timer % 5 == 0:
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logger.info(f"{log_prefix} 麦麦现在想聊{self._loop_timer:.1f}秒")
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# Start the loop if it wasn't active and timer is positive
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if not self._loop_active and self._loop_timer > 0:
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# logger.info(f"{log_prefix} 麦麦有兴趣！开始聊天")
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self._loop_active = True
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if self._loop_task and not self._loop_task.done():
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logger.warning(f"{log_prefix} 发现意外的循环任务正在进行。取消它。")
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self._loop_task.cancel()
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self._loop_task = asyncio.create_task(self._run_pf_loop())
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self._loop_task.add_done_callback(self._handle_loop_completion)
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elif self._loop_active:
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logger.trace(f"{log_prefix} 循环已经激活。计时器延长。")
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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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# Check if the task raised an exception
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exception = task.exception()
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if exception:
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logger.error(f"{log_prefix} PFChatting: 麦麦脱离了聊天(异常)")
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logger.error(traceback.format_exc())
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else:
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logger.debug(f"{log_prefix} PFChatting: 麦麦脱离了聊天")
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except asyncio.CancelledError:
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logger.info(f"{log_prefix} PFChatting: 麦麦脱离了聊天(异常取消)")
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finally:
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# Reset state regardless of how the task finished
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self._loop_active = False
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self._loop_task = None
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self._last_added_duration = self._initial_duration # <--- 重置下次首次触发的增加时间
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self._trigger_count_this_activation = 0 # 重置计数器
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# Ensure lock is released if the loop somehow exited while holding it
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if self._processing_lock.locked():
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logger.warning(f"{log_prefix} PFChatting: 锁没有正常释放")
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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，当计时器>0时持续进行计划并可能回复消息
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管理每个循环周期的处理锁
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"""
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logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦打算好好聊聊")
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try:
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while True:
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# 使用计时器锁安全地检查当前计时器值
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async with self._timer_lock:
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current_timer = self._loop_timer
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if current_timer <= 0:
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logger.info(
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f"{self._get_log_prefix()} PFChatting: 聊太久了，麦麦打算休息一下(已经聊了{current_timer:.1f}秒)，退出PFChatting"
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)
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break # 退出条件：计时器到期
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# 记录循环开始时间
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loop_cycle_start_time = time.monotonic()
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# 标记本周期是否执行了操作
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action_taken_this_cycle = False
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# 获取处理锁，确保每个计划-回复-发送周期独占执行
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acquired_lock = False
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try:
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await self._processing_lock.acquire()
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acquired_lock = True
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# logger.debug(f"{self._get_log_prefix()} PFChatting: 循环获取到处理锁")
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# --- Planner ---
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# Planner decides action, reasoning, emoji_query, etc.
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planner_result = await self._planner() # Modify planner to return decision dict
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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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current_mind = planner_result.get("current_mind", "[Mind unavailable]")
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send_emoji_from_tools = planner_result.get("send_emoji_from_tools", "")
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observed_messages = planner_result.get("observed_messages", []) # Planner needs to return this
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if action == "text_reply":
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logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦决定回复文本.")
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action_taken_this_cycle = True
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# --- 回复器 ---
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anchor_message = await self._get_anchor_message(observed_messages)
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if not anchor_message:
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logger.error(f"{self._get_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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thinking_id = await self.heartfc_chat._create_thinking_message(anchor_message)
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if not thinking_id:
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logger.error(f"{self._get_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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# 直接 await 回复器工作
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replier_result = await self._replier_work(
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observed_messages=observed_messages,
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anchor_message=anchor_message,
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thinking_id=thinking_id,
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current_mind=current_mind,
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send_emoji=send_emoji_from_tools,
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)
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except Exception as e_replier:
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logger.error(f"{self._get_log_prefix()} 循环: 回复器工作失败: {e_replier}")
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self._cleanup_thinking_message(thinking_id) # 清理思考消息
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# 继续循环, 视为非操作周期
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if replier_result:
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# --- Sender ---
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try:
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await self._sender(thinking_id, anchor_message, replier_result)
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logger.info(f"{self._get_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"{self._get_log_prefix()} 循环: 发送器失败: {e_sender}")
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self._cleanup_thinking_message(thinking_id) # 确保发送失败时清理
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# 继续循环, 视为非操作周期
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else:
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# Replier failed to produce result
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logger.warning(f"{self._get_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) # 清理思考消息
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elif action == "emoji_reply":
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logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦决定回复表情 ('{emoji_query}').")
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action_taken_this_cycle = True
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anchor = await self._get_anchor_message(observed_messages)
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if anchor:
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try:
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await self.heartfc_chat._handle_emoji(anchor, [], emoji_query)
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except Exception as e_emoji:
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logger.error(f"{self._get_log_prefix()} 循环: 发送表情失败: {e_emoji}")
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else:
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logger.warning(f"{self._get_log_prefix()} 循环: 无法发送表情, 无法获取锚点.")
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elif action == "no_reply":
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logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦决定不回复. 原因: {reasoning}")
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# Do nothing else, action_taken_this_cycle remains False
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elif action == "error":
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logger.error(f"{self._get_log_prefix()} PFChatting: 麦麦回复出错. 原因: {reasoning}")
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# 视为非操作周期
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else: # Unknown action
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logger.warning(f"{self._get_log_prefix()} PFChatting: 麦麦做了奇怪的事情. 原因: {reasoning}")
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# 视为非操作周期
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except Exception as e_cycle:
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# Catch errors occurring within the locked section (e.g., planner crash)
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logger.error(f"{self._get_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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# Ensure lock is released if an error occurs before the finally block
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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 # 防止在 finally 块中重复释放
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logger.warning(f"{self._get_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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# Ensure the lock is always released after a cycle
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if acquired_lock:
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self._processing_lock.release()
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logger.debug(f"{self._get_log_prefix()} 循环释放了处理锁.")
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# --- Timer Decrement ---
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cycle_duration = time.monotonic() - loop_cycle_start_time
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async with self._timer_lock:
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self._loop_timer -= cycle_duration
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logger.debug(
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f"{self._get_log_prefix()} PFChatting: 麦麦聊了{cycle_duration:.2f}秒. 还能聊: {self._loop_timer:.1f}s."
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)
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# --- Delay ---
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# Add a small delay, especially if no action was taken, to prevent busy-waiting
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try:
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if not action_taken_this_cycle and cycle_duration < 1.5:
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# If nothing happened and cycle was fast, wait a bit longer
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await asyncio.sleep(1.5 - cycle_duration)
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elif cycle_duration < 0.2: # Minimum delay even if action was taken
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await asyncio.sleep(0.2)
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except asyncio.CancelledError:
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logger.info(f"{self._get_log_prefix()} Sleep interrupted, likely loop cancellation.")
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break # Exit loop if cancelled during sleep
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except asyncio.CancelledError:
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logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦的聊天被取消了")
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except Exception as e_loop_outer:
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# Catch errors outside the main cycle lock (should be rare)
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logger.error(f"{self._get_log_prefix()} PFChatting: 麦麦的聊天出错了: {e_loop_outer}")
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logger.error(traceback.format_exc())
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finally:
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# Reset trigger count when loop finishes
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async with self._timer_lock:
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self._trigger_count_this_activation = 0
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logger.debug(f"{self._get_log_prefix()} Trigger count reset to 0 as loop finishes.")
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logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦的聊天结束了")
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# State reset (_loop_active, _loop_task) is handled by _handle_loop_completion callback
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async def _planner(self) -> Dict[str, Any]:
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"""
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规划器 (Planner): 使用LLM根据上下文决定是否和如何回复。
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返回:
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dict: 包含决策和上下文的字典，结构如下:
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{
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'action': str, # 执行动作 (不回复/文字回复/表情包)
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'reasoning': str, # 决策理由
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'emoji_query': str, # 表情包查询词
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'current_mind': str, # 当前心理状态
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'send_emoji_from_tools': str, # 工具推荐的表情包
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'observed_messages': List[dict] # 观察到的消息列表
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}
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"""
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log_prefix = self._get_log_prefix()
|
||
observed_messages: List[dict] = []
|
||
tool_result_info = {}
|
||
get_mid_memory_id = []
|
||
send_emoji_from_tools = "" # Renamed for clarity
|
||
current_mind: Optional[str] = None
|
||
|
||
# --- 获取最新的观察信息 ---
|
||
try:
|
||
observation = self.sub_hf._get_primary_observation() # Call only once
|
||
|
||
if observation: # Now check if the result is truthy
|
||
# logger.debug(f"{log_prefix}[Planner] 调用 observation.observe()...")
|
||
await observation.observe() # 主动观察以获取最新消息
|
||
observed_messages = observation.talking_message # 获取更新后的消息列表
|
||
logger.debug(f"{log_prefix}[Planner] 观察获取到 {len(observed_messages)} 条消息。")
|
||
else:
|
||
logger.warning(f"{log_prefix}[Planner] 无法获取 Observation。")
|
||
except Exception as e:
|
||
logger.error(f"{log_prefix}[Planner] 获取观察信息时出错: {e}")
|
||
logger.error(traceback.format_exc())
|
||
# --- 结束获取观察信息 ---
|
||
|
||
# --- (Moved from _replier_work) 1. 思考前使用工具 ---
|
||
try:
|
||
observation_context_text = ""
|
||
if observed_messages:
|
||
context_texts = [
|
||
msg.get("detailed_plain_text", "") for msg in observed_messages if msg.get("detailed_plain_text")
|
||
]
|
||
observation_context_text = " ".join(context_texts)
|
||
# logger.debug(f"{log_prefix}[Planner] Context for tools: {observation_context_text[:100]}...")
|
||
|
||
tool_result = await self.heartfc_chat.tool_user.use_tool(
|
||
message_txt=observation_context_text, chat_stream=self.chat_stream, sub_heartflow=self.sub_hf
|
||
)
|
||
if tool_result.get("used_tools", False):
|
||
tool_result_info = tool_result.get("structured_info", {})
|
||
logger.debug(f"{log_prefix}[Planner] 规划前工具结果: {tool_result_info}")
|
||
if "mid_chat_mem" in tool_result_info:
|
||
get_mid_memory_id = [mem["content"] for mem in tool_result_info["mid_chat_mem"] if "content" in mem]
|
||
|
||
except Exception as e_tool:
|
||
logger.error(f"{log_prefix}[Planner] 规划前工具使用失败: {e_tool}")
|
||
# --- 结束工具使用 ---
|
||
|
||
current_mind, _past_mind = await self.sub_hf.do_thinking_before_reply(
|
||
chat_stream=self.chat_stream,
|
||
extra_info=tool_result_info,
|
||
obs_id=get_mid_memory_id,
|
||
)
|
||
|
||
# --- 使用 LLM 进行决策 ---
|
||
action = "no_reply" # Default action
|
||
emoji_query = ""
|
||
reasoning = "默认决策或获取决策失败"
|
||
llm_error = False # Flag for LLM failure
|
||
|
||
try:
|
||
# 构建提示 (Now includes current_mind)
|
||
prompt = await self._build_planner_prompt(observed_messages, current_mind)
|
||
logger.debug(f"{log_prefix}[Planner] 规划器 Prompt: {prompt}")
|
||
|
||
# 准备 LLM 请求 Payload
|
||
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"}}, # 强制调用此工具
|
||
}
|
||
|
||
# 调用 LLM
|
||
response = await self.planner_llm._execute_request(
|
||
endpoint="/chat/completions", payload=payload, prompt=prompt
|
||
)
|
||
|
||
# 解析 LLM 响应
|
||
if len(response) == 3: # 期望返回 content, reasoning_content, tool_calls
|
||
_, _, tool_calls = response
|
||
if tool_calls and isinstance(tool_calls, list) and len(tool_calls) > 0:
|
||
# 通常强制调用后只会有一个 tool_call
|
||
tool_call = tool_calls[0]
|
||
if (
|
||
tool_call.get("type") == "function"
|
||
and tool_call.get("function", {}).get("name") == "decide_reply_action"
|
||
):
|
||
try:
|
||
arguments = json.loads(tool_call["function"]["arguments"])
|
||
action = arguments.get("action", "no_reply")
|
||
reasoning = arguments.get("reasoning", "未提供理由")
|
||
if action == "emoji_reply":
|
||
# Planner's decision overrides tool's emoji if action is emoji_reply
|
||
emoji_query = arguments.get(
|
||
"emoji_query", send_emoji_from_tools
|
||
) # Use tool emoji as default if planner asks for emoji
|
||
logger.info(
|
||
f"{log_prefix}[Planner] LLM 决策: {action}, 理由: {reasoning}, EmojiQuery: '{emoji_query}'"
|
||
)
|
||
except json.JSONDecodeError as json_e:
|
||
logger.error(
|
||
f"{log_prefix}[Planner] 解析工具参数失败: {json_e}. Arguments: {tool_call['function'].get('arguments')}"
|
||
)
|
||
action = "error"
|
||
reasoning = "工具参数解析失败"
|
||
llm_error = True
|
||
except Exception as parse_e:
|
||
logger.error(f"{log_prefix}[Planner] 处理工具参数时出错: {parse_e}")
|
||
action = "error"
|
||
reasoning = "处理工具参数时出错"
|
||
llm_error = True
|
||
else:
|
||
logger.warning(
|
||
f"{log_prefix}[Planner] LLM 未按预期调用 'decide_reply_action' 工具。Tool calls: {tool_calls}"
|
||
)
|
||
action = "error"
|
||
reasoning = "LLM未调用预期工具"
|
||
llm_error = True
|
||
else:
|
||
logger.warning(f"{log_prefix}[Planner] LLM 响应中未包含有效的工具调用。Tool calls: {tool_calls}")
|
||
action = "error"
|
||
reasoning = "LLM响应无工具调用"
|
||
llm_error = True
|
||
else:
|
||
logger.warning(f"{log_prefix}[Planner] LLM 未返回预期的工具调用响应。Response parts: {len(response)}")
|
||
action = "error"
|
||
reasoning = "LLM响应格式错误"
|
||
llm_error = True
|
||
|
||
except Exception as llm_e:
|
||
logger.error(f"{log_prefix}[Planner] Planner LLM 调用失败: {llm_e}")
|
||
logger.error(traceback.format_exc())
|
||
action = "error"
|
||
reasoning = f"LLM 调用失败: {llm_e}"
|
||
llm_error = True
|
||
|
||
# --- 返回决策结果 ---
|
||
# Note: Lock release is handled by the loop now
|
||
return {
|
||
"action": action,
|
||
"reasoning": reasoning,
|
||
"emoji_query": emoji_query, # Specific query if action is emoji_reply
|
||
"current_mind": current_mind,
|
||
"send_emoji_from_tools": send_emoji_from_tools, # Emoji suggested by pre-thinking tools
|
||
"observed_messages": observed_messages,
|
||
"llm_error": llm_error, # Indicate if LLM decision process failed
|
||
}
|
||
|
||
async def _get_anchor_message(self, observed_messages: List[dict]) -> 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。
|
||
"""
|
||
if not self.chat_stream:
|
||
logger.error(f"{self._get_log_prefix()} 无法获取锚点消息: ChatStream 不可用.")
|
||
return None
|
||
|
||
try:
|
||
last_msg_dict = None
|
||
if observed_messages:
|
||
last_msg_dict = observed_messages[-1]
|
||
|
||
if last_msg_dict:
|
||
try:
|
||
# Attempt reconstruction from the last observed message dictionary
|
||
anchor_message = MessageRecv(last_msg_dict, chat_stream=self.chat_stream)
|
||
# Basic validation
|
||
if not (
|
||
anchor_message
|
||
and anchor_message.message_info
|
||
and anchor_message.message_info.message_id
|
||
and anchor_message.message_info.user_info
|
||
):
|
||
raise ValueError("重构的 MessageRecv 缺少必要信息.")
|
||
logger.debug(
|
||
f"{self._get_log_prefix()} 重构的锚点消息: ID={anchor_message.message_info.message_id}"
|
||
)
|
||
return anchor_message
|
||
except Exception as e_reconstruct:
|
||
logger.warning(
|
||
f"{self._get_log_prefix()} 从观察到的消息重构 MessageRecv 失败: {e_reconstruct}. 创建占位符."
|
||
)
|
||
else:
|
||
logger.warning(f"{self._get_log_prefix()} observed_messages 为空. 创建占位符锚点消息.")
|
||
|
||
# --- Create Placeholder ---
|
||
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]", # Placeholder text
|
||
"raw_message": "",
|
||
"time": placeholder_msg_info.time,
|
||
}
|
||
anchor_message = MessageRecv(placeholder_msg_dict)
|
||
anchor_message.update_chat_stream(self.chat_stream) # Associate with the 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
|
||
|
||
def _cleanup_thinking_message(self, thinking_id: str):
|
||
"""Safely removes the thinking message."""
|
||
try:
|
||
container = MessageManager().get_container(self.stream_id)
|
||
container.remove_message(thinking_id, msg_type=MessageThinking)
|
||
logger.debug(f"{self._get_log_prefix()} Cleaned up thinking message {thinking_id}.")
|
||
except Exception as e:
|
||
logger.error(f"{self._get_log_prefix()} Error cleaning up thinking message {thinking_id}: {e}")
|
||
|
||
async def _sender(self, thinking_id: str, anchor_message: MessageRecv, replier_result: Dict[str, Any]):
|
||
"""
|
||
发送器 (Sender): 使用HeartFC_Chat的方法发送生成的回复。
|
||
被 _run_pf_loop 直接调用和 await。
|
||
也处理相关的操作，如发送表情和更新关系。
|
||
Raises exception on failure to signal the loop.
|
||
"""
|
||
# replier_result should contain 'response_set' and 'send_emoji'
|
||
response_set = replier_result.get("response_set")
|
||
send_emoji = replier_result.get("send_emoji", "") # Emoji determined by tools, passed via replier
|
||
|
||
if not response_set:
|
||
logger.error(f"{self._get_log_prefix()}[Sender-{thinking_id}] Called with empty response_set.")
|
||
# Clean up thinking message before raising error
|
||
self._cleanup_thinking_message(thinking_id)
|
||
raise ValueError("Sender called with no response_set") # Signal failure to loop
|
||
|
||
first_bot_msg: Optional[MessageSending] = None
|
||
send_success = False
|
||
try:
|
||
# --- Send the main text response ---
|
||
logger.debug(f"{self._get_log_prefix()}[Sender-{thinking_id}] Sending response messages...")
|
||
# This call implicitly handles replacing the MessageThinking with MessageSending/MessageSet
|
||
first_bot_msg = await self.heartfc_chat._send_response_messages(anchor_message, response_set, thinking_id)
|
||
|
||
if first_bot_msg:
|
||
send_success = True # Mark success
|
||
logger.info(f"{self._get_log_prefix()}[Sender-{thinking_id}] Successfully sent reply.")
|
||
|
||
# --- Handle associated emoji (if determined by tools) ---
|
||
if send_emoji:
|
||
logger.info(
|
||
f"{self._get_log_prefix()}[Sender-{thinking_id}] Sending associated emoji: {send_emoji}"
|
||
)
|
||
try:
|
||
# Use first_bot_msg as anchor if available, otherwise fallback to original anchor
|
||
emoji_anchor = first_bot_msg if first_bot_msg else anchor_message
|
||
await self.heartfc_chat._handle_emoji(emoji_anchor, response_set, send_emoji)
|
||
except Exception as e_emoji:
|
||
logger.error(
|
||
f"{self._get_log_prefix()}[Sender-{thinking_id}] Failed to send associated emoji: {e_emoji}"
|
||
)
|
||
# Log error but don't fail the whole send process for emoji failure
|
||
|
||
# --- Update relationship ---
|
||
try:
|
||
await self.heartfc_chat._update_relationship(anchor_message, response_set)
|
||
logger.debug(f"{self._get_log_prefix()}[Sender-{thinking_id}] Updated relationship.")
|
||
except Exception as e_rel:
|
||
logger.error(
|
||
f"{self._get_log_prefix()}[Sender-{thinking_id}] Failed to update relationship: {e_rel}"
|
||
)
|
||
# Log error but don't fail the whole send process for relationship update failure
|
||
|
||
else:
|
||
# Sending failed (e.g., _send_response_messages found thinking message already gone)
|
||
send_success = False
|
||
logger.warning(
|
||
f"{self._get_log_prefix()}[Sender-{thinking_id}] Failed to send reply (maybe thinking message expired or was removed?)."
|
||
)
|
||
# No need to clean up thinking message here, _send_response_messages implies it's gone or handled
|
||
raise RuntimeError("Sending reply failed, _send_response_messages returned None.") # Signal failure
|
||
|
||
except Exception as e:
|
||
# Catch potential errors during sending or post-send actions
|
||
logger.error(f"{self._get_log_prefix()}[Sender-{thinking_id}] Error during sending process: {e}")
|
||
logger.error(traceback.format_exc())
|
||
# Ensure thinking message is cleaned up if send failed mid-way and wasn't handled
|
||
if not send_success:
|
||
self._cleanup_thinking_message(thinking_id)
|
||
raise # Re-raise the exception to signal failure to the loop
|
||
|
||
# No finally block needed for lock management
|
||
|
||
async def shutdown(self):
|
||
"""
|
||
Gracefully shuts down the PFChatting instance by cancelling the active loop task.
|
||
"""
|
||
logger.info(f"{self._get_log_prefix()} Shutting down PFChatting...")
|
||
if self._loop_task and not self._loop_task.done():
|
||
logger.info(f"{self._get_log_prefix()} Cancelling active PF loop task.")
|
||
self._loop_task.cancel()
|
||
try:
|
||
# Wait briefly for the task to acknowledge cancellation
|
||
await asyncio.wait_for(self._loop_task, timeout=5.0)
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{self._get_log_prefix()} PF loop task cancelled successfully.")
|
||
except asyncio.TimeoutError:
|
||
logger.warning(f"{self._get_log_prefix()} Timeout waiting for PF loop task cancellation.")
|
||
except Exception as e:
|
||
logger.error(f"{self._get_log_prefix()} Error during loop task cancellation: {e}")
|
||
else:
|
||
logger.info(f"{self._get_log_prefix()} No active PF loop task found to cancel.")
|
||
|
||
# Ensure loop state is reset even if task wasn't running or cancellation failed
|
||
self._loop_active = False
|
||
self._loop_task = None
|
||
|
||
# Double-check lock state (should be released by loop completion/cancellation handler)
|
||
if self._processing_lock.locked():
|
||
logger.warning(f"{self._get_log_prefix()} Releasing processing lock during shutdown.")
|
||
self._processing_lock.release()
|
||
|
||
logger.info(f"{self._get_log_prefix()} PFChatting shutdown complete.")
|
||
|
||
async def _build_planner_prompt(self, observed_messages: List[dict], current_mind: Optional[str]) -> str:
|
||
"""构建 Planner LLM 的提示词 (现在包含 current_mind)"""
|
||
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"
|
||
|
||
# Add current mind state if available
|
||
|
||
if observed_messages:
|
||
context_text = " ".join(
|
||
[msg.get("detailed_plain_text", "") for msg in observed_messages if msg.get("detailed_plain_text")]
|
||
)
|
||
prompt += "观察到的最新聊天内容如下：\n---\n"
|
||
prompt += context_text[:1500] # Limit context length
|
||
prompt += "\n---\n"
|
||
else:
|
||
prompt += "当前没有观察到新的聊天内容。\n"
|
||
|
||
prompt += "\n看了这些内容，你的想法是："
|
||
|
||
if current_mind:
|
||
prompt += f"\n---\n{current_mind}\n---\n\n"
|
||
|
||
prompt += (
|
||
"\n请结合你的内部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"
|
||
)
|
||
prompt += "决策依据：\n"
|
||
prompt += "1. 如果聊天内容无聊、与你无关、或者你的内部想法认为不适合回复，选择 'no_reply'。\n"
|
||
prompt += "2. 如果聊天内容值得回应，且适合用文字表达（参考你的内部想法），选择 'text_reply'。如果想在文字后追加一个表情，请同时提供 'emoji_query'。\n"
|
||
prompt += (
|
||
"3. 如果聊天内容或你的内部想法适合用一个表情来回应，选择 'emoji_reply' 并提供表情主题 'emoji_query'。\n"
|
||
)
|
||
prompt += "4. 如果你已经回复过消息，也没有人又回复你，选择'no_reply'。\n"
|
||
prompt += "5. 除非大家都在这么做，否则不要重复聊相同的内容。\n"
|
||
prompt += "6. 表情包是用来表示情绪的，不要直接回复或者评价别人的表情包。\n"
|
||
prompt += "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'。"
|
||
|
||
prompt = await relationship_manager.convert_all_person_sign_to_person_name(prompt)
|
||
prompt = parse_text_timestamps(prompt, mode="lite")
|
||
|
||
return prompt
|
||
|
||
# --- 回复器 (Replier) 的定义 --- #
|
||
async def _replier_work(
|
||
self,
|
||
observed_messages: List[dict],
|
||
anchor_message: MessageRecv,
|
||
thinking_id: str,
|
||
current_mind: Optional[str],
|
||
send_emoji: str,
|
||
) -> Optional[Dict[str, Any]]:
|
||
"""
|
||
回复器 (Replier): 核心逻辑用于生成回复。
|
||
被 _run_pf_loop 直接调用和 await。
|
||
Returns dict with 'response_set' and 'send_emoji' or None on failure.
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
response_set: Optional[List[str]] = None
|
||
try:
|
||
# --- Tool Use and SubHF Thinking are now in _planner ---
|
||
|
||
# --- Generate Response with LLM ---
|
||
# logger.debug(f"{log_prefix}[Replier-{thinking_id}] Calling LLM to generate response...")
|
||
# 注意：实际的生成调用是在 self.heartfc_chat.gpt.generate_response 中
|
||
response_set = await self.heartfc_chat.gpt.generate_response(
|
||
anchor_message,
|
||
thinking_id,
|
||
# current_mind 不再直接传递给 gpt.generate_response，
|
||
# 因为 generate_response 内部会通过 thinking_id 或其他方式获取所需上下文
|
||
)
|
||
|
||
if not response_set:
|
||
logger.warning(f"{log_prefix}[Replier-{thinking_id}] LLM生成了一个空回复集。")
|
||
return None # Indicate failure
|
||
|
||
# --- 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)[:100]}...")
|
||
return {
|
||
"response_set": response_set,
|
||
"send_emoji": send_emoji, # Pass through the emoji determined earlier (usually by tools)
|
||
}
|
||
|
||
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 # Indicate failure
|