import asyncio import time import traceback from typing import List, Optional, Dict, Any, TYPE_CHECKING import json from ....config.config import global_config from ...chat.message import MessageRecv, BaseMessageInfo, MessageThinking, MessageSending from ...chat.chat_stream import ChatStream from ...message import UserInfo from src.heart_flow.heartflow import heartflow, SubHeartflow from src.plugins.chat.chat_stream import chat_manager from .messagesender import MessageManager from src.common.logger import get_module_logger, LogConfig, DEFAULT_CONFIG # 引入 DEFAULT_CONFIG from src.plugins.models.utils_model import LLMRequest from src.plugins.chat.utils import parse_text_timestamps from src.plugins.person_info.relationship_manager import relationship_manager # 定义日志配置 (使用 loguru 格式) interest_log_config = LogConfig( console_format=DEFAULT_CONFIG["console_format"], # 使用默认控制台格式 file_format=DEFAULT_CONFIG["file_format"], # 使用默认文件格式 ) logger = get_module_logger("PFChattingLoop", config=interest_log_config) # Logger Name Changed # Forward declaration for type hinting if TYPE_CHECKING: from .heartFC_chat import HeartFC_Chat PLANNER_TOOL_DEFINITION = [ { "type": "function", "function": { "name": "decide_reply_action", "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。", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": ["no_reply", "text_reply", "emoji_reply"], "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)。", }, "reasoning": {"type": "string", "description": "做出此决定的简要理由。"}, "emoji_query": { "type": "string", "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。", }, }, "required": ["action", "reasoning"], }, }, } ] class PFChatting: """ Manages a continuous Plan-Filter-Check (now Plan-Replier-Sender) loop for generating replies within a specific chat stream, controlled by a timer. The loop runs as long as the timer > 0. """ def __init__(self, chat_id: str, heartfc_chat_instance: "HeartFC_Chat"): """ 初始化PFChatting实例。 Args: chat_id: The identifier for the chat stream (e.g., stream_id). heartfc_chat_instance: 访问共享资源和方法的主HeartFC_Chat实例。 """ self.heartfc_chat = heartfc_chat_instance # 访问logger, gpt, tool_user, _send_response_messages等。 self.stream_id: str = chat_id self.chat_stream: Optional[ChatStream] = None self.sub_hf: Optional[SubHeartflow] = None self._initialized = False self._init_lock = asyncio.Lock() # Ensure initialization happens only once self._processing_lock = asyncio.Lock() # 确保只有一个 Plan-Replier-Sender 周期在运行 self._timer_lock = asyncio.Lock() # 用于安全更新计时器 self.planner_llm = LLMRequest( model=global_config.llm_normal, temperature=global_config.llm_normal["temp"], max_tokens=1000, request_type="action_planning", ) # Internal state for loop control self._loop_timer: float = 0.0 # Remaining time for the loop in seconds self._loop_active: bool = False # Is the loop currently running? self._loop_task: Optional[asyncio.Task] = None # Stores the main loop task self._trigger_count_this_activation: int = 0 # Counts triggers within an active period self._initial_duration: float = 30.0 # 首次触发增加的时间 self._last_added_duration: float = self._initial_duration # <--- 新增：存储上次增加的时间 # Removed pending_replies as processing is now serial within the loop # self.pending_replies: Dict[str, PendingReply] = {} def _get_log_prefix(self) -> str: """获取日志前缀，包含可读的流名称""" stream_name = chat_manager.get_stream_name(self.stream_id) or self.stream_id return f"[{stream_name}]" async def _initialize(self) -> bool: """ 懒初始化以使用提供的标识符解析chat_stream和sub_hf。 确保实例已准备好处理触发器。 """ async with self._init_lock: if self._initialized: return True log_prefix = self._get_log_prefix() # 获取前缀 try: self.chat_stream = chat_manager.get_stream(self.stream_id) if not self.chat_stream: logger.error(f"{log_prefix} 获取ChatStream失败。") return False # 子心流(SubHeartflow)可能初始不存在但后续会被创建 # 在需要它的方法中应优雅处理其可能缺失的情况 self.sub_hf = heartflow.get_subheartflow(self.stream_id) if not self.sub_hf: logger.warning(f"{log_prefix} 获取SubHeartflow失败。一些功能可能受限。") # 决定是否继续初始化。目前允许初始化。 self._initialized = True logger.info(f"麦麦感觉到了，激发了PFChatting{log_prefix} 初始化成功。") return True except Exception as e: logger.error(f"{log_prefix} 初始化失败: {e}") logger.error(traceback.format_exc()) return False async def add_time(self): """ 为麦麦添加时间，麦麦有兴趣时，时间增加。 """ log_prefix = self._get_log_prefix() if not self._initialized: if not await self._initialize(): logger.error(f"{log_prefix} 无法添加时间: 未初始化。") return async with self._timer_lock: duration_to_add: float = 0.0 if not self._loop_active: # First trigger for this activation cycle duration_to_add = self._initial_duration # 使用初始值 self._last_added_duration = duration_to_add # 更新上次增加的值 self._trigger_count_this_activation = 1 # Start counting logger.info( f"{log_prefix} 麦麦有兴趣！ #{self._trigger_count_this_activation}. 麦麦打算聊： {duration_to_add:.2f}s." ) else: # Loop is already active, apply 50% reduction self._trigger_count_this_activation += 1 duration_to_add = self._last_added_duration * 0.5 if duration_to_add < 0.5: duration_to_add = 0.5 self._last_added_duration = duration_to_add # 更新上次增加的值 else: self._last_added_duration = duration_to_add # 更新上次增加的值 logger.info( 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." ) # 添加计算出的时间 new_timer_value = self._loop_timer + duration_to_add self._loop_timer = max(0, new_timer_value) if self._loop_timer % 5 == 0: logger.info(f"{log_prefix} 麦麦现在想聊{self._loop_timer:.1f}秒") # Start the loop if it wasn't active and timer is positive if not self._loop_active and self._loop_timer > 0: # logger.info(f"{log_prefix} 麦麦有兴趣！开始聊天") self._loop_active = True if self._loop_task and not self._loop_task.done(): logger.warning(f"{log_prefix} 发现意外的循环任务正在进行。取消它。") self._loop_task.cancel() self._loop_task = asyncio.create_task(self._run_pf_loop()) self._loop_task.add_done_callback(self._handle_loop_completion) elif self._loop_active: logger.trace(f"{log_prefix} 循环已经激活。计时器延长。") def _handle_loop_completion(self, task: asyncio.Task): """当 _run_pf_loop 任务完成时执行的回调。""" log_prefix = self._get_log_prefix() try: # Check if the task raised an exception exception = task.exception() if exception: logger.error(f"{log_prefix} PFChatting: 麦麦脱离了聊天(异常)") logger.error(traceback.format_exc()) else: logger.debug(f"{log_prefix} PFChatting: 麦麦脱离了聊天") except asyncio.CancelledError: logger.info(f"{log_prefix} PFChatting: 麦麦脱离了聊天(异常取消)") finally: # Reset state regardless of how the task finished self._loop_active = False self._loop_task = None self._last_added_duration = self._initial_duration # <--- 重置下次首次触发的增加时间 self._trigger_count_this_activation = 0 # 重置计数器 # Ensure lock is released if the loop somehow exited while holding it if self._processing_lock.locked(): logger.warning(f"{log_prefix} PFChatting: 锁没有正常释放") self._processing_lock.release() async def _run_pf_loop(self): """ 主循环，当计时器>0时持续进行计划并可能回复消息 管理每个循环周期的处理锁 """ logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦打算好好聊聊") try: while True: # 使用计时器锁安全地检查当前计时器值 async with self._timer_lock: current_timer = self._loop_timer if current_timer <= 0: logger.info( 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" ) break # 退出条件：计时器到期 # 记录循环开始时间 loop_cycle_start_time = time.monotonic() # 标记本周期是否执行了操作 action_taken_this_cycle = False # 获取处理锁，确保每个计划-回复-发送周期独占执行 acquired_lock = False try: await self._processing_lock.acquire() acquired_lock = True # logger.debug(f"{self._get_log_prefix()} PFChatting: 循环获取到处理锁") # --- Planner --- # Planner decides action, reasoning, emoji_query, etc. planner_result = await self._planner() # Modify planner to return decision dict action = planner_result.get("action", "error") reasoning = planner_result.get("reasoning", "Planner did not provide reasoning.") emoji_query = planner_result.get("emoji_query", "") current_mind = planner_result.get("current_mind", "[Mind unavailable]") send_emoji_from_tools = planner_result.get("send_emoji_from_tools", "") observed_messages = planner_result.get("observed_messages", []) # Planner needs to return this if action == "text_reply": logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦决定回复文本.") action_taken_this_cycle = True # --- 回复器 --- anchor_message = await self._get_anchor_message(observed_messages) if not anchor_message: 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.") else: thinking_id = await self.heartfc_chat._create_thinking_message(anchor_message) if not thinking_id: logger.error(f"{self._get_log_prefix()} 循环: 无法创建思考ID. 跳过周期.") else: replier_result = None try: # 直接 await 回复器工作 replier_result = await self._replier_work( observed_messages=observed_messages, anchor_message=anchor_message, thinking_id=thinking_id, current_mind=current_mind, send_emoji=send_emoji_from_tools, ) except Exception as e_replier: logger.error(f"{self._get_log_prefix()} 循环: 回复器工作失败: {e_replier}") self._cleanup_thinking_message(thinking_id) # 清理思考消息 # 继续循环, 视为非操作周期 if replier_result: # --- Sender --- try: await self._sender(thinking_id, anchor_message, replier_result) logger.info(f"{self._get_log_prefix()} 循环: 发送器完成成功.") except Exception as e_sender: logger.error(f"{self._get_log_prefix()} 循环: 发送器失败: {e_sender}") self._cleanup_thinking_message(thinking_id) # 确保发送失败时清理 # 继续循环, 视为非操作周期 else: # Replier failed to produce result logger.warning(f"{self._get_log_prefix()} 循环: 回复器未产生结果. 跳过发送.") self._cleanup_thinking_message(thinking_id) # 清理思考消息 elif action == "emoji_reply": logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦决定回复表情 ('{emoji_query}').") action_taken_this_cycle = True anchor = await self._get_anchor_message(observed_messages) if anchor: try: await self.heartfc_chat._handle_emoji(anchor, [], emoji_query) except Exception as e_emoji: logger.error(f"{self._get_log_prefix()} 循环: 发送表情失败: {e_emoji}") else: logger.warning(f"{self._get_log_prefix()} 循环: 无法发送表情, 无法获取锚点.") elif action == "no_reply": logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦决定不回复. 原因: {reasoning}") # Do nothing else, action_taken_this_cycle remains False elif action == "error": logger.error(f"{self._get_log_prefix()} PFChatting: 麦麦回复出错. 原因: {reasoning}") # 视为非操作周期 else: # Unknown action logger.warning(f"{self._get_log_prefix()} PFChatting: 麦麦做了奇怪的事情. 原因: {reasoning}") # 视为非操作周期 except Exception as e_cycle: # Catch errors occurring within the locked section (e.g., planner crash) logger.error(f"{self._get_log_prefix()} 循环周期执行时发生错误: {e_cycle}") logger.error(traceback.format_exc()) # Ensure lock is released if an error occurs before the finally block if acquired_lock and self._processing_lock.locked(): self._processing_lock.release() acquired_lock = False # 防止在 finally 块中重复释放 logger.warning(f"{self._get_log_prefix()} 由于循环周期中的错误释放了处理锁.") finally: # Ensure the lock is always released after a cycle if acquired_lock: self._processing_lock.release() logger.debug(f"{self._get_log_prefix()} 循环释放了处理锁.") # --- Timer Decrement --- cycle_duration = time.monotonic() - loop_cycle_start_time async with self._timer_lock: self._loop_timer -= cycle_duration logger.debug( f"{self._get_log_prefix()} PFChatting: 麦麦聊了{cycle_duration:.2f}秒. 还能聊: {self._loop_timer:.1f}s." ) # --- Delay --- # Add a small delay, especially if no action was taken, to prevent busy-waiting try: if not action_taken_this_cycle and cycle_duration < 1.5: # If nothing happened and cycle was fast, wait a bit longer await asyncio.sleep(1.5 - cycle_duration) elif cycle_duration < 0.2: # Minimum delay even if action was taken await asyncio.sleep(0.2) except asyncio.CancelledError: logger.info(f"{self._get_log_prefix()} Sleep interrupted, likely loop cancellation.") break # Exit loop if cancelled during sleep except asyncio.CancelledError: logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦的聊天被取消了") except Exception as e_loop_outer: # Catch errors outside the main cycle lock (should be rare) logger.error(f"{self._get_log_prefix()} PFChatting: 麦麦的聊天出错了: {e_loop_outer}") logger.error(traceback.format_exc()) finally: # Reset trigger count when loop finishes async with self._timer_lock: self._trigger_count_this_activation = 0 logger.debug(f"{self._get_log_prefix()} Trigger count reset to 0 as loop finishes.") logger.info(f"{self._get_log_prefix()} PFChatting: 麦麦的聊天结束了") # State reset (_loop_active, _loop_task) is handled by _handle_loop_completion callback 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。 返回: dict: 包含决策和上下文的字典，结构如下: { 'action': str, # 执行动作 (不回复/文字回复/表情包) 'reasoning': str, # 决策理由 'emoji_query': str, # 表情包查询词 'current_mind': str, # 当前心理状态 'send_emoji_from_tools': str, # 工具推荐的表情包 'observed_messages': List[dict] # 观察到的消息列表 } """ 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