import time from random import random import traceback from typing import List, Optional import asyncio from ...moods.moods import MoodManager from ....config.config import global_config from ...chat.emoji_manager import emoji_manager from .heartFC__generator import ResponseGenerator from ...chat.message import MessageSending, MessageRecv, MessageThinking, MessageSet from .messagesender import MessageManager from ...chat.utils_image import image_path_to_base64 from ...message import UserInfo, Seg from src.heart_flow.heartflow import heartflow from src.common.logger import get_module_logger, CHAT_STYLE_CONFIG, LogConfig from ...person_info.relationship_manager import relationship_manager from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager from ...utils.timer_calculater import Timer from src.do_tool.tool_use import ToolUser from .interest import InterestManager, InterestChatting # 定义日志配置 chat_config = LogConfig( console_format=CHAT_STYLE_CONFIG["console_format"], file_format=CHAT_STYLE_CONFIG["file_format"], ) logger = get_module_logger("heartFC_chat", config=chat_config) # 新增常量 INTEREST_LEVEL_REPLY_THRESHOLD = 4.0 INTEREST_MONITOR_INTERVAL_SECONDS = 1 class HeartFC_Chat: def __init__(self): self.gpt = ResponseGenerator() self.mood_manager = MoodManager.get_instance() self.mood_manager.start_mood_update() self.tool_user = ToolUser() self.interest_manager = InterestManager() self._interest_monitor_task: Optional[asyncio.Task] = None async def start(self): """Starts asynchronous tasks like the interest monitor.""" logger.info("HeartFC_Chat starting asynchronous tasks...") await self.interest_manager.start_background_tasks() self._initialize_monitor_task() logger.info("HeartFC_Chat asynchronous tasks started.") def _initialize_monitor_task(self): """启动后台兴趣监控任务""" if self._interest_monitor_task is None or self._interest_monitor_task.done(): try: loop = asyncio.get_running_loop() self._interest_monitor_task = loop.create_task(self._interest_monitor_loop()) logger.info(f"Interest monitor task created. Interval: {INTEREST_MONITOR_INTERVAL_SECONDS}s, Level Threshold: {INTEREST_LEVEL_REPLY_THRESHOLD}") except RuntimeError: logger.error("Failed to create interest monitor task: No running event loop.") raise else: logger.warning("Interest monitor task creation skipped: already running or exists.") async def _interest_monitor_loop(self): """后台任务，定期检查兴趣度变化并触发回复""" logger.info("Interest monitor loop starting...") await asyncio.sleep(0.3) while True: await asyncio.sleep(INTEREST_MONITOR_INTERVAL_SECONDS) try: interest_items_snapshot: List[tuple[str, InterestChatting]] = [] stream_ids = list(self.interest_manager.interest_dict.keys()) for stream_id in stream_ids: chatting_instance = self.interest_manager.get_interest_chatting(stream_id) if chatting_instance: interest_items_snapshot.append((stream_id, chatting_instance)) for stream_id, chatting_instance in interest_items_snapshot: triggering_message = chatting_instance.last_triggering_message current_interest = chatting_instance.get_interest() # 添加调试日志，检查触发条件 # logger.debug(f"[兴趣监控][{stream_id}] 当前兴趣: {current_interest:.2f}, 阈值: {INTEREST_LEVEL_REPLY_THRESHOLD}, 触发消息存在: {triggering_message is not None}") if current_interest > INTEREST_LEVEL_REPLY_THRESHOLD and triggering_message is not None: logger.info(f"[{stream_id}] 检测到高兴趣度 ({current_interest:.2f} > {INTEREST_LEVEL_REPLY_THRESHOLD}). 基于消息 ID: {triggering_message.message_info.message_id} 的上下文触发回复") # 更新日志信息使其更清晰 chatting_instance.reset_trigger_info() logger.debug(f"[{stream_id}] Trigger info reset before starting reply task.") asyncio.create_task(self._process_triggered_reply(stream_id, triggering_message)) except asyncio.CancelledError: logger.info("Interest monitor loop cancelled.") break except Exception as e: logger.error(f"Error in interest monitor loop: {e}") logger.error(traceback.format_exc()) await asyncio.sleep(5) async def _process_triggered_reply(self, stream_id: str, triggering_message: MessageRecv): """Helper coroutine to handle the processing of a triggered reply based on interest level.""" try: logger.info(f"[{stream_id}] Starting level-triggered reply generation for message ID: {triggering_message.message_info.message_id}...") await self.trigger_reply_generation(triggering_message) # 在回复处理后降低兴趣度，降低固定值：新阈值的一半 decrease_value = INTEREST_LEVEL_REPLY_THRESHOLD / 2 self.interest_manager.decrease_interest(stream_id, value=decrease_value) post_trigger_interest = self.interest_manager.get_interest(stream_id) # 更新日志以反映降低的是基于新阈值的固定值 logger.info(f"[{stream_id}] Interest decreased by fixed value {decrease_value:.2f} (LevelThreshold/2) after processing level-triggered reply. Current interest: {post_trigger_interest:.2f}") except Exception as e: logger.error(f"Error processing level-triggered reply for stream_id {stream_id}, context message_id {triggering_message.message_info.message_id}: {e}") logger.error(traceback.format_exc()) async def _create_thinking_message(self, message: MessageRecv): """创建思考消息 (从 message 获取信息)""" chat = message.chat_stream if not chat: logger.error(f"Cannot create thinking message, chat_stream is None for message ID: {message.message_info.message_id}") return None userinfo = message.message_info.user_info # 发起思考的用户（即原始消息发送者） messageinfo = message.message_info # 原始消息信息 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, # 思考消息的发出者是 bot reply=message, # 回复的是原始消息 thinking_start_time=thinking_time_point, ) MessageManager().add_message(thinking_message) return thinking_id async def _send_response_messages(self, message: MessageRecv, response_set: List[str], thinking_id) -> MessageSending: chat = message.chat_stream container = MessageManager().get_container(chat.stream_id) thinking_message = None for msg in container.messages: if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id: thinking_message = msg container.messages.remove(msg) break if not thinking_message: logger.warning("未找到对应的思考消息，可能已超时被移除") return None thinking_start_time = thinking_message.thinking_start_time message_set = MessageSet(chat, thinking_id) mark_head = False first_bot_msg = None for msg in response_set: message_segment = Seg(type="text", data=msg) bot_message = MessageSending( message_id=thinking_id, chat_stream=chat, bot_user_info=UserInfo( user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform=message.message_info.platform, # 从传入的 message 获取 platform ), sender_info=message.message_info.user_info, # 发送给谁 message_segment=message_segment, reply=message, # 回复原始消息 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) MessageManager().add_message(message_set) return first_bot_msg async def _handle_emoji(self, message: MessageRecv, response_set, send_emoji=""): """处理表情包 (从 message 获取信息)""" chat = 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(message.message_info.time, 2) message_segment = Seg(type="emoji", data=emoji_cq) bot_message = MessageSending( message_id="mt" + str(thinking_time_point), chat_stream=chat, bot_user_info=UserInfo( user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform=message.message_info.platform, ), sender_info=message.message_info.user_info, # 发送给谁 message_segment=message_segment, reply=message, # 回复原始消息 is_head=False, is_emoji=True, ) MessageManager().add_message(bot_message) async def _update_relationship(self, message: MessageRecv, response_set): """更新关系情绪""" ori_response = ",".join(response_set) stance, emotion = await self.gpt._get_emotion_tags(ori_response, message.processed_plain_text) await relationship_manager.calculate_update_relationship_value( chat_stream=message.chat_stream, label=emotion, stance=stance ) self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor) async def trigger_reply_generation(self, message: MessageRecv): """根据意愿阈值触发的实际回复生成和发送逻辑 (V3 - 简化参数)""" chat = message.chat_stream userinfo = message.message_info.user_info messageinfo = message.message_info timing_results = {} response_set = None thinking_id = None info_catcher = None try: try: with Timer("观察", timing_results): sub_hf = heartflow.get_subheartflow(chat.stream_id) if not sub_hf: logger.warning(f"尝试观察时未找到 stream_id {chat.stream_id} 的 subheartflow") return await sub_hf.do_observe() except Exception as e: logger.error(f"心流观察失败: {e}") logger.error(traceback.format_exc()) container = MessageManager().get_container(chat.stream_id) thinking_count = container.count_thinking_messages() max_thinking_messages = getattr(global_config, 'max_concurrent_thinking_messages', 3) if thinking_count >= max_thinking_messages: logger.warning(f"聊天流 {chat.stream_id} 已有 {thinking_count} 条思考消息，取消回复。触发消息: {message.processed_plain_text[:30]}...") return try: with Timer("创建思考消息", timing_results): thinking_id = await self._create_thinking_message(message) except Exception as e: logger.error(f"心流创建思考消息失败: {e}") return if not thinking_id: logger.error("未能成功创建思考消息 ID，无法继续回复流程。") return logger.trace(f"创建捕捉器，thinking_id:{thinking_id}") info_catcher = info_catcher_manager.get_info_catcher(thinking_id) info_catcher.catch_decide_to_response(message) get_mid_memory_id = [] tool_result_info = {} send_emoji = "" try: with Timer("思考前使用工具", timing_results): tool_result = await self.tool_user.use_tool( message.processed_plain_text, userinfo.user_nickname, chat, heartflow.get_subheartflow(chat.stream_id), ) if tool_result.get("used_tools", False): if "structured_info" in tool_result: tool_result_info = tool_result["structured_info"] get_mid_memory_id = [] for tool_name, tool_data in tool_result_info.items(): if tool_name == "mid_chat_mem": for mid_memory in tool_data: get_mid_memory_id.append(mid_memory["content"]) if tool_name == "send_emoji": send_emoji = tool_data[0]["content"] except Exception as e: logger.error(f"思考前工具调用失败: {e}") logger.error(traceback.format_exc()) current_mind, past_mind = "", "" try: with Timer("思考前脑内状态", timing_results): sub_hf = heartflow.get_subheartflow(chat.stream_id) if sub_hf: current_mind, past_mind = await sub_hf.do_thinking_before_reply( message_txt=message.processed_plain_text, sender_info=userinfo, chat_stream=chat, obs_id=get_mid_memory_id, extra_info=tool_result_info, ) else: logger.warning(f"尝试思考前状态时未找到 stream_id {chat.stream_id} 的 subheartflow") except Exception as e: logger.error(f"心流思考前脑内状态失败: {e}") logger.error(traceback.format_exc()) if info_catcher: info_catcher.catch_afer_shf_step(timing_results.get("思考前脑内状态"), past_mind, current_mind) try: with Timer("生成回复", timing_results): response_set = await self.gpt.generate_response(message, thinking_id) except Exception as e: logger.error(f"GPT 生成回复失败: {e}") logger.error(traceback.format_exc()) if info_catcher: info_catcher.done_catch() return if info_catcher: info_catcher.catch_after_generate_response(timing_results.get("生成回复")) if not response_set: logger.info("回复生成失败，返回为空") if info_catcher: info_catcher.done_catch() return first_bot_msg = None try: with Timer("发送消息", timing_results): first_bot_msg = await self._send_response_messages(message, response_set, thinking_id) except Exception as e: logger.error(f"心流发送消息失败: {e}") if info_catcher: info_catcher.catch_after_response(timing_results.get("发送消息"), response_set, first_bot_msg) info_catcher.done_catch() try: with Timer("处理表情包", timing_results): if send_emoji: logger.info(f"麦麦决定发送表情包{send_emoji}") await self._handle_emoji(message, response_set, send_emoji) except Exception as e: logger.error(f"心流处理表情包失败: {e}") timing_str = " | ".join([f"{step}: {duration:.2f}秒" for step, duration in timing_results.items()]) trigger_msg = message.processed_plain_text response_msg = " ".join(response_set) if response_set else "无回复" logger.info(f"回复任务完成: 触发消息: {trigger_msg[:20]}... | 思维消息: {response_msg[:20]}... | 性能计时: {timing_str}") if first_bot_msg: try: with Timer("更新关系情绪", timing_results): await self._update_relationship(message, response_set) except Exception as e: logger.error(f"更新关系情绪失败: {e}") logger.error(traceback.format_exc()) except Exception as e: logger.error(f"回复生成任务失败 (trigger_reply_generation V3): {e}") logger.error(traceback.format_exc()) finally: pass