492 lines
23 KiB
Python
492 lines
23 KiB
Python
from .observation import Observation, ChattingObservation
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import asyncio
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from src.plugins.moods.moods import MoodManager
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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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import time
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from typing import Optional
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from datetime import datetime
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import traceback
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from src.plugins.chat.message import UserInfo
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from src.plugins.chat.utils import parse_text_timestamps
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# from src.plugins.schedule.schedule_generator import bot_schedule
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# from src.plugins.memory_system.Hippocampus import HippocampusManager
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from src.common.logger import get_module_logger, LogConfig, SUB_HEARTFLOW_STYLE_CONFIG # noqa: E402
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# from src.plugins.chat.utils import get_embedding
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# from src.common.database import db
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# from typing import Union
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from src.individuality.individuality import Individuality
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import random
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from src.plugins.chat.chat_stream import ChatStream
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from src.plugins.person_info.relationship_manager import relationship_manager
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from src.plugins.chat.utils import get_recent_group_speaker
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from ..plugins.utils.prompt_builder import Prompt, global_prompt_manager
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subheartflow_config = LogConfig(
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# 使用海马体专用样式
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console_format=SUB_HEARTFLOW_STYLE_CONFIG["console_format"],
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file_format=SUB_HEARTFLOW_STYLE_CONFIG["file_format"],
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)
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logger = get_module_logger("subheartflow", config=subheartflow_config)
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def init_prompt():
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prompt = ""
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# prompt += f"麦麦的总体想法是：{self.main_heartflow_info}\n\n"
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prompt += "{extra_info}\n"
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# prompt += "{prompt_schedule}\n"
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# prompt += "{relation_prompt_all}\n"
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prompt += "{prompt_personality}\n"
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prompt += "刚刚你的想法是{current_thinking_info}。可以适当转换话题\n"
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prompt += "-----------------------------------\n"
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prompt += "现在是{time_now}，你正在上网，和qq群里的网友们聊天，群里正在聊的话题是：\n{chat_observe_info}\n"
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prompt += "你现在{mood_info}\n"
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# prompt += "你注意到{sender_name}刚刚说：{message_txt}\n"
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prompt += "现在你接下去继续思考，产生新的想法，不要分点输出，输出连贯的内心独白"
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prompt += "思考时可以想想如何对群聊内容进行回复。回复的要求是：平淡一些，简短一些，说中文，尽量不要说你说过的话。如果你要回复，最好只回复一个人的一个话题\n"
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prompt += "请注意不要输出多余内容(包括前后缀，冒号和引号，括号， 表情，等)，不要带有括号和动作描写"
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prompt += "记得结合上述的消息，生成内心想法，文字不要浮夸，注意{bot_name}指的就是你。"
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Prompt(prompt, "sub_heartflow_prompt_before")
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prompt = ""
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# prompt += f"你现在正在做的事情是：{schedule_info}\n"
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prompt += "{extra_info}\n"
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prompt += "{prompt_personality}\n"
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prompt += "现在是{time_now}，你正在上网，和qq群里的网友们聊天，群里正在聊的话题是：\n{chat_observe_info}\n"
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prompt += "刚刚你的想法是{current_thinking_info}。"
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prompt += "你现在看到了网友们发的新消息:{message_new_info}\n"
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prompt += "你刚刚回复了群友们:{reply_info}"
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prompt += "你现在{mood_info}"
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prompt += "现在你接下去继续思考，产生新的想法，记得保留你刚刚的想法，不要分点输出，输出连贯的内心独白"
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prompt += "不要太长，但是记得结合上述的消息，要记得你的人设，关注聊天和新内容，关注你回复的内容，不要思考太多:"
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Prompt(prompt, "sub_heartflow_prompt_after")
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# prompt += f"你现在正在做的事情是：{schedule_info}\n"
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prompt += "{extra_info}\n"
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prompt += "{prompt_personality}\n"
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prompt += "现在是{time_now}，你正在上网，和qq群里的网友们聊天，群里正在聊的话题是：\n{chat_observe_info}\n"
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prompt += "刚刚你的想法是{current_thinking_info}。"
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prompt += "你现在看到了网友们发的新消息:{message_new_info}\n"
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# prompt += "你刚刚回复了群友们:{reply_info}"
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prompt += "你现在{mood_info}"
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prompt += "现在你接下去继续思考，产生新的想法，记得保留你刚刚的想法，不要分点输出，输出连贯的内心独白"
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prompt += "不要思考太多，不要输出多余内容(包括前后缀，冒号和引号，括号， 表情，等)，不要带有括号和动作描写"
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prompt += "记得结合上述的消息，生成内心想法，文字不要浮夸，注意{bot_name}指的就是你。"
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Prompt(prompt, "sub_heartflow_prompt_after_observe")
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class CurrentState:
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def __init__(self):
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self.willing = 0
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self.current_state_info = ""
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self.mood_manager = MoodManager()
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self.mood = self.mood_manager.get_prompt()
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def update_current_state_info(self):
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self.current_state_info = self.mood_manager.get_current_mood()
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class SubHeartflow:
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def __init__(self, subheartflow_id):
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self.subheartflow_id = subheartflow_id
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self.current_mind = ""
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self.past_mind = []
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self.current_state: CurrentState = CurrentState()
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self.llm_model = LLMRequest(
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model=global_config.llm_sub_heartflow,
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temperature=global_config.llm_sub_heartflow["temp"],
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max_tokens=600,
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request_type="sub_heart_flow",
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)
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self.main_heartflow_info = ""
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self.last_reply_time = time.time()
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self.last_active_time = time.time() # 添加最后激活时间
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if not self.current_mind:
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self.current_mind = "你什么也没想"
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self.is_active = False
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self.observations: list[ChattingObservation] = []
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self.running_knowledges = []
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self._thinking_lock = asyncio.Lock() # 添加思考锁，防止并发思考
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self.bot_name = global_config.BOT_NICKNAME
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def add_observation(self, observation: Observation):
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"""添加一个新的observation对象到列表中，如果已存在相同id的observation则不添加"""
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# 查找是否存在相同id的observation
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for existing_obs in self.observations:
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if existing_obs.observe_id == observation.observe_id:
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# 如果找到相同id的observation，直接返回
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return
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# 如果没有找到相同id的observation，则添加新的
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self.observations.append(observation)
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def remove_observation(self, observation: Observation):
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"""从列表中移除一个observation对象"""
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if observation in self.observations:
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self.observations.remove(observation)
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def get_all_observations(self) -> list[Observation]:
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"""获取所有observation对象"""
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return self.observations
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def clear_observations(self):
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"""清空所有observation对象"""
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self.observations.clear()
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def _get_primary_observation(self) -> Optional[ChattingObservation]:
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"""获取主要的（通常是第一个）ChattingObservation实例"""
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if self.observations and isinstance(self.observations[0], ChattingObservation):
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return self.observations[0]
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logger.warning(f"SubHeartflow {self.subheartflow_id} 没有找到有效的 ChattingObservation")
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return None
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async def subheartflow_start_working(self):
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while True:
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current_time = time.time()
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# --- 调整后台任务逻辑 --- #
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# 这个后台循环现在主要负责检查是否需要自我销毁
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# 不再主动进行思考或状态更新，这些由 HeartFC_Chat 驱动
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# 检查是否需要冻结（这个逻辑可能需要重新审视，因为激活状态现在由外部驱动）
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# if current_time - self.last_reply_time > global_config.sub_heart_flow_freeze_time:
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# self.is_active = False
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# else:
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# self.is_active = True
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# self.last_active_time = current_time # 由外部调用（如 thinking）更新
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# 检查是否超过指定时间没有激活 (例如，没有被调用进行思考)
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if current_time - self.last_active_time > global_config.sub_heart_flow_stop_time: # 例如 5 分钟
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logger.info(f"子心流 {self.subheartflow_id} 超过 {global_config.sub_heart_flow_stop_time} 秒没有激活，正在销毁..."
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f" (Last active: {datetime.fromtimestamp(self.last_active_time).strftime('%Y-%m-%d %H:%M:%S')})")
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# 在这里添加实际的销毁逻辑，例如从主 Heartflow 管理器中移除自身
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# heartflow.remove_subheartflow(self.subheartflow_id) # 假设有这样的方法
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break # 退出循环以停止任务
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# 不再需要内部驱动的状态更新和思考
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# self.current_state.update_current_state_info()
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# await self.do_a_thinking()
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# await self.judge_willing()
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await asyncio.sleep(global_config.sub_heart_flow_update_interval) # 定期检查销毁条件
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async def ensure_observed(self):
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"""确保在思考前执行了观察"""
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observation = self._get_primary_observation()
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if observation:
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try:
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await observation.observe()
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logger.trace(f"[{self.subheartflow_id}] Observation updated before thinking.")
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except Exception as e:
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logger.error(f"[{self.subheartflow_id}] Error during pre-thinking observation: {e}")
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logger.error(traceback.format_exc())
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async def do_observe(self):
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# 现在推荐使用 ensure_observed()，但保留此方法以兼容旧用法（或特定场景）
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observation = self._get_primary_observation()
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if observation:
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await observation.observe()
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else:
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logger.error(f"[{self.subheartflow_id}] do_observe called but no valid observation found.")
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async def do_thinking_before_reply(
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self, chat_stream: ChatStream, extra_info: str, obs_id: list[str] = None # 修改 obs_id 类型为 list[str]
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):
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async with self._thinking_lock: # 获取思考锁
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# --- 在思考前确保观察已执行 --- #
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await self.ensure_observed()
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self.last_active_time = time.time() # 更新最后激活时间戳
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current_thinking_info = self.current_mind
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mood_info = self.current_state.mood
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observation = self._get_primary_observation()
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if not observation:
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logger.error(f"[{self.subheartflow_id}] Cannot perform thinking without observation.")
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return "", [] # 返回空结果
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# --- 获取观察信息 --- #
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chat_observe_info = ""
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if obs_id:
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try:
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chat_observe_info = observation.get_observe_info(obs_id)
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logger.debug(f"[{self.subheartflow_id}] Using specific observation IDs: {obs_id}")
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except Exception as e:
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logger.error(f"[{self.subheartflow_id}] Error getting observe info with IDs {obs_id}: {e}. Falling back.")
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chat_observe_info = observation.get_observe_info() # 出错时回退到默认观察
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else:
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chat_observe_info = observation.get_observe_info()
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logger.debug(f"[{self.subheartflow_id}] Using default observation info.")
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# --- 构建 Prompt (基本逻辑不变) --- #
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extra_info_prompt = ""
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if extra_info:
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for tool_name, tool_data in extra_info.items():
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extra_info_prompt += f"{tool_name} 相关信息:\n"
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for item in tool_data:
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extra_info_prompt += f"- {item['name']}: {item['content']}\n"
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else:
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extra_info_prompt = "无工具信息。\n" # 提供默认值
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individuality = Individuality.get_instance()
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prompt_personality = f"你的名字是{self.bot_name},你"
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prompt_personality += individuality.personality.personality_core
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personality_sides = individuality.personality.personality_sides
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if personality_sides: random.shuffle(personality_sides); prompt_personality += f",{personality_sides[0]}"
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identity_detail = individuality.identity.identity_detail
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if identity_detail: random.shuffle(identity_detail); prompt_personality += f",{identity_detail[0]}"
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# who_chat_in_group = [
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# (chat_stream.platform, sender_info.user_id, sender_info.user_nickname) # 先添加当前发送者
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# ]
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# # 获取最近发言者，排除当前发送者，避免重复
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# recent_speakers = get_recent_group_speaker(
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# chat_stream.stream_id,
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# (chat_stream.platform, sender_info.user_id),
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# limit=global_config.MAX_CONTEXT_SIZE -1 # 减去当前发送者
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# )
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# who_chat_in_group.extend(recent_speakers)
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# relation_prompt = ""
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# unique_speakers = set() # 确保人物信息不重复
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# for person_tuple in who_chat_in_group:
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# person_key = (person_tuple[0], person_tuple[1]) # 使用 platform+id 作为唯一标识
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# if person_key not in unique_speakers:
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# relation_prompt += await relationship_manager.build_relationship_info(person_tuple)
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# unique_speakers.add(person_key)
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# relation_prompt_all = (await global_prompt_manager.get_prompt_async("relationship_prompt")).format(
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# relation_prompt, sender_info.user_nickname
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# )
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# sender_name_sign = (
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# f"<{chat_stream.platform}:{sender_info.user_id}:{sender_info.user_nickname}:{sender_info.user_cardname or 'NoCard'}>"
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# )
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time_now = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
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prompt = (await global_prompt_manager.get_prompt_async("sub_heartflow_prompt_before")).format(
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extra_info=extra_info_prompt,
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# relation_prompt_all=relation_prompt_all,
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prompt_personality=prompt_personality,
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current_thinking_info=current_thinking_info,
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time_now=time_now,
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chat_observe_info=chat_observe_info,
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mood_info=mood_info,
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# sender_name=sender_name_sign,
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# message_txt=message_txt,
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bot_name=self.bot_name,
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)
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prompt = await relationship_manager.convert_all_person_sign_to_person_name(prompt)
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prompt = parse_text_timestamps(prompt, mode="lite")
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logger.debug(f"[{self.subheartflow_id}] Thinking Prompt:\n{prompt}")
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try:
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response, reasoning_content = await self.llm_model.generate_response_async(prompt)
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if not response: # 如果 LLM 返回空，给一个默认想法
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response = "(不知道该想些什么...)"
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logger.warning(f"[{self.subheartflow_id}] LLM returned empty response for thinking.")
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except Exception as e:
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logger.error(f"[{self.subheartflow_id}] 内心独白获取失败: {e}")
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response = "(思考时发生错误...)" # 错误时的默认想法
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self.update_current_mind(response)
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# self.current_mind 已经在 update_current_mind 中更新
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logger.info(f"[{self.subheartflow_id}] 思考前脑内状态：{self.current_mind}")
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return self.current_mind, self.past_mind
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async def do_thinking_after_observe(
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self, message_txt: str, sender_info: UserInfo, chat_stream: ChatStream, extra_info: str, obs_id: int = None
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):
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current_thinking_info = self.current_mind
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mood_info = self.current_state.mood
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# mood_info = "你很生气，很愤怒"
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observation = self.observations[0]
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if obs_id:
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print(f"11111111111有id,开始获取观察信息{obs_id}")
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chat_observe_info = observation.get_observe_info(obs_id)
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else:
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chat_observe_info = observation.get_observe_info()
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extra_info_prompt = ""
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for tool_name, tool_data in extra_info.items():
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extra_info_prompt += f"{tool_name} 相关信息:\n"
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for item in tool_data:
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extra_info_prompt += f"- {item['name']}: {item['content']}\n"
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# 开始构建prompt
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prompt_personality = f"你的名字是{self.bot_name},你"
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# person
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individuality = Individuality.get_instance()
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personality_core = individuality.personality.personality_core
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prompt_personality += personality_core
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personality_sides = individuality.personality.personality_sides
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random.shuffle(personality_sides)
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prompt_personality += f",{personality_sides[0]}"
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identity_detail = individuality.identity.identity_detail
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random.shuffle(identity_detail)
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prompt_personality += f",{identity_detail[0]}"
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# 关系
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who_chat_in_group = [
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(chat_stream.user_info.platform, chat_stream.user_info.user_id, chat_stream.user_info.user_nickname)
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]
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who_chat_in_group += get_recent_group_speaker(
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chat_stream.stream_id,
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(chat_stream.user_info.platform, chat_stream.user_info.user_id),
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limit=global_config.MAX_CONTEXT_SIZE,
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)
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relation_prompt = ""
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for person in who_chat_in_group:
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relation_prompt += await relationship_manager.build_relationship_info(person)
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# relation_prompt_all = (
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# f"{relation_prompt}关系等级越大，关系越好，请分析聊天记录，"
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# f"根据你和说话者{sender_name}的关系和态度进行回复，明确你的立场和情感。"
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# )
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relation_prompt_all = (await global_prompt_manager.get_prompt_async("relationship_prompt")).format(
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relation_prompt, sender_info.user_nickname
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)
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sender_name_sign = (
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f"<{chat_stream.platform}:{sender_info.user_id}:{sender_info.user_nickname}:{sender_info.user_cardname}>"
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)
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time_now = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
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prompt = (await global_prompt_manager.get_prompt_async("sub_heartflow_prompt_after_observe")).format(
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extra_info_prompt,
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# prompt_schedule,
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relation_prompt_all,
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prompt_personality,
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current_thinking_info,
|
||
time_now,
|
||
chat_observe_info,
|
||
mood_info,
|
||
sender_name_sign,
|
||
message_txt,
|
||
self.bot_name,
|
||
)
|
||
|
||
prompt = await relationship_manager.convert_all_person_sign_to_person_name(prompt)
|
||
prompt = parse_text_timestamps(prompt, mode="lite")
|
||
|
||
try:
|
||
response, reasoning_content = await self.llm_model.generate_response_async(prompt)
|
||
except Exception as e:
|
||
logger.error(f"回复前内心独白获取失败: {e}")
|
||
response = ""
|
||
self.update_current_mind(response)
|
||
|
||
self.current_mind = response
|
||
|
||
logger.info(f"prompt:\n{prompt}\n")
|
||
logger.info(f"麦麦的思考前脑内状态：{self.current_mind}")
|
||
return self.current_mind, self.past_mind
|
||
|
||
# async def do_thinking_after_reply(self, reply_content, chat_talking_prompt, extra_info):
|
||
# # print("麦麦回复之后脑袋转起来了")
|
||
|
||
# # 开始构建prompt
|
||
# prompt_personality = f"你的名字是{self.bot_name},你"
|
||
# # person
|
||
# individuality = Individuality.get_instance()
|
||
|
||
# personality_core = individuality.personality.personality_core
|
||
# prompt_personality += personality_core
|
||
|
||
# extra_info_prompt = ""
|
||
# for tool_name, tool_data in extra_info.items():
|
||
# extra_info_prompt += f"{tool_name} 相关信息:\n"
|
||
# for item in tool_data:
|
||
# extra_info_prompt += f"- {item['name']}: {item['content']}\n"
|
||
|
||
# personality_sides = individuality.personality.personality_sides
|
||
# random.shuffle(personality_sides)
|
||
# prompt_personality += f",{personality_sides[0]}"
|
||
|
||
# identity_detail = individuality.identity.identity_detail
|
||
# random.shuffle(identity_detail)
|
||
# prompt_personality += f",{identity_detail[0]}"
|
||
|
||
# current_thinking_info = self.current_mind
|
||
# mood_info = self.current_state.mood
|
||
|
||
# observation = self.observations[0]
|
||
# chat_observe_info = observation.observe_info
|
||
|
||
# message_new_info = chat_talking_prompt
|
||
# reply_info = reply_content
|
||
|
||
# time_now = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
|
||
|
||
# prompt = (await global_prompt_manager.get_prompt_async("sub_heartflow_prompt_after")).format(
|
||
# extra_info_prompt,
|
||
# prompt_personality,
|
||
# time_now,
|
||
# chat_observe_info,
|
||
# current_thinking_info,
|
||
# message_new_info,
|
||
# reply_info,
|
||
# mood_info,
|
||
# )
|
||
|
||
# prompt = await relationship_manager.convert_all_person_sign_to_person_name(prompt)
|
||
# prompt = parse_text_timestamps(prompt, mode="lite")
|
||
|
||
# try:
|
||
# response, reasoning_content = await self.llm_model.generate_response_async(prompt)
|
||
# except Exception as e:
|
||
# logger.error(f"回复后内心独白获取失败: {e}")
|
||
# response = ""
|
||
# self.update_current_mind(response)
|
||
|
||
# self.current_mind = response
|
||
# logger.info(f"麦麦回复后的脑内状态：{self.current_mind}")
|
||
|
||
# self.last_reply_time = time.time()
|
||
|
||
def update_current_mind(self, response):
|
||
self.past_mind.append(self.current_mind)
|
||
self.current_mind = response
|
||
|
||
async def check_reply_trigger(self) -> bool:
|
||
"""根据观察到的信息和内部状态，判断是否应该触发一次回复。
|
||
TODO: 实现具体的判断逻辑。
|
||
例如：检查 self.observations[0].now_message_info 是否包含提及、问题，
|
||
或者 self.current_mind 中是否包含强烈的回复意图等。
|
||
"""
|
||
# Placeholder: 目前始终返回 False，需要后续实现
|
||
logger.trace(f"[{self.subheartflow_id}] check_reply_trigger called. (Logic Pending)")
|
||
# --- 实现触发逻辑 --- #
|
||
# 示例：如果观察到的最新消息包含自己的名字，则有一定概率触发
|
||
# observation = self._get_primary_observation()
|
||
# if observation and self.bot_name in observation.now_message_info[-100:]: # 检查最后100个字符
|
||
# if random.random() < 0.3: # 30% 概率触发
|
||
# logger.info(f"[{self.subheartflow_id}] Triggering reply based on mention.")
|
||
# return True
|
||
# ------------------ #
|
||
return False # 默认不触发
|
||
|
||
|
||
init_prompt()
|
||
# subheartflow = SubHeartflow()
|