270 lines
12 KiB
Python
270 lines
12 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.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.person_info.relationship_manager import relationship_manager
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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：\n我是{bot_name}，我想，{current_thinking_info}\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 += "\n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 += "现在请你根据刚刚的想法继续思考，思考时可以想想如何对群聊内容进行回复，要不要对群里的话题进行回复，关注新话题，可以适当转换话题，大家正在说的话才是聊天的主题。\n"
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prompt += "回复的要求是：平淡一些，简短一些，说中文，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。不要回复自己的发言，尽量不要说你说过的话。"
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prompt += "现在请你{hf_do_next}，不要分点输出,生成内心想法，文字不要浮夸"
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Prompt(prompt, "sub_heartflow_prompt_before")
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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=800,
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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.bot_name = global_config.BOT_NICKNAME
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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(
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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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)
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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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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_thinking_before_reply(
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self,
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extra_info: str,
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obs_id: list[str] = None, # 修改 obs_id 类型为 list[str]
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):
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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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# --- 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(
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f"[{self.subheartflow_id}] Error getting observe info with IDs {obs_id}: {e}. Falling back."
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)
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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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# 添加随机性格侧面
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if individuality.personality.personality_sides:
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random_side = random.choice(individuality.personality.personality_sides)
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prompt_personality += f"，{random_side}"
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# 添加随机身份细节
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if individuality.identity.identity_detail:
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random_detail = random.choice(individuality.identity.identity_detail)
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prompt_personality += f"，{random_detail}"
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time_now = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
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# 创建局部Random对象避免影响全局随机状态
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local_random = random.Random()
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current_minute = int(time.strftime("%M"))
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local_random.seed(current_minute) # 用分钟作为种子确保每分钟内选择一致
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hf_options = [
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("继续生成你在这个聊天中的想法，在原来想法的基础上继续思考", 0.7),
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("生成你在这个聊天中的想法，在原来的想法上尝试新的话题", 0.1),
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("生成你在这个聊天中的想法，不要太深入", 0.1),
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("继续生成你在这个聊天中的想法，进行深入思考", 0.1),
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]
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hf_do_next = local_random.choices(
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[option[0] for option in hf_options], weights=[option[1] for option in hf_options], k=1
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)[0]
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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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bot_name=self.bot_name,
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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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hf_do_next=hf_do_next,
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# sender_name=sender_name_sign,
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# message_txt=message_txt,
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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}] 心流思考prompt:\n{prompt}\n")
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try:
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response, reasoning_content = await self.llm_model.generate_response_async(prompt)
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logger.debug(f"[{self.subheartflow_id}] 心流思考结果:\n{response}\n")
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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 返回空结果，思考失败。")
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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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def update_current_mind(self, response):
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self.past_mind.append(self.current_mind)
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self.current_mind = response
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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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init_prompt()
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# subheartflow = SubHeartflow()
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