ref：调整文件位置和命名，结构更清晰
This commit is contained in:
SengokuCola
@@ -1,135 +0,0 @@
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import time
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import os
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from typing import Optional, Dict, Any
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from src.common.logger import get_logger
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import json
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logger = get_logger("hfc") # Logger Name Changed
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log_dir = "log/log_cycle_debug/"
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class CycleDetail:
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"""循环信息记录类"""
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def __init__(self, cycle_id: int):
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self.cycle_id = cycle_id
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self.prefix = ""
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self.thinking_id = ""
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self.start_time = time.time()
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self.end_time: Optional[float] = None
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self.timers: Dict[str, float] = {}
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# 新字段
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self.loop_observation_info: Dict[str, Any] = {}
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self.loop_processor_info: Dict[str, Any] = {} # 前处理器信息
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self.loop_plan_info: Dict[str, Any] = {}
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self.loop_action_info: Dict[str, Any] = {}
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def to_dict(self) -> Dict[str, Any]:
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"""将循环信息转换为字典格式"""
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def convert_to_serializable(obj, depth=0, seen=None):
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if seen is None:
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seen = set()
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# 防止递归过深
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if depth > 5: # 降低递归深度限制
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return str(obj)
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# 防止循环引用
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obj_id = id(obj)
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if obj_id in seen:
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return str(obj)
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seen.add(obj_id)
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try:
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if hasattr(obj, "to_dict"):
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# 对于有to_dict方法的对象，直接调用其to_dict方法
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return obj.to_dict()
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elif isinstance(obj, dict):
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# 对于字典，只保留基本类型和可序列化的值
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return {
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k: convert_to_serializable(v, depth + 1, seen)
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for k, v in obj.items()
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if isinstance(k, (str, int, float, bool))
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}
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elif isinstance(obj, (list, tuple)):
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# 对于列表和元组，只保留可序列化的元素
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return [
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convert_to_serializable(item, depth + 1, seen)
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for item in obj
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if not isinstance(item, (dict, list, tuple))
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or isinstance(item, (str, int, float, bool, type(None)))
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]
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elif isinstance(obj, (str, int, float, bool, type(None))):
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return obj
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else:
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return str(obj)
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finally:
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seen.remove(obj_id)
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return {
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"cycle_id": self.cycle_id,
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"start_time": self.start_time,
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"end_time": self.end_time,
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"timers": self.timers,
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"thinking_id": self.thinking_id,
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"loop_observation_info": convert_to_serializable(self.loop_observation_info),
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"loop_processor_info": convert_to_serializable(self.loop_processor_info),
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"loop_plan_info": convert_to_serializable(self.loop_plan_info),
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"loop_action_info": convert_to_serializable(self.loop_action_info),
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}
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def complete_cycle(self):
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"""完成循环，记录结束时间"""
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self.end_time = time.time()
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# 处理 prefix，只保留中英文字符和基本标点
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if not self.prefix:
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self.prefix = "group"
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else:
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# 只保留中文、英文字母、数字和基本标点
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allowed_chars = set("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789-_")
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self.prefix = (
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"".join(char for char in self.prefix if "\u4e00" <= char <= "\u9fff" or char in allowed_chars)
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or "group"
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)
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# current_time_minute = time.strftime("%Y%m%d_%H%M", time.localtime())
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# try:
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# self.log_cycle_to_file(
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# log_dir + self.prefix + f"/{current_time_minute}_cycle_" + str(self.cycle_id) + ".json"
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# )
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# except Exception as e:
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# logger.warning(f"写入文件日志，可能是群名称包含非法字符: {e}")
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def log_cycle_to_file(self, file_path: str):
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"""将循环信息写入文件"""
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# 如果目录不存在，则创建目
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dir_name = os.path.dirname(file_path)
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# 去除特殊字符，保留字母、数字、下划线、中划线和中文
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dir_name = "".join(
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char for char in dir_name if char.isalnum() or char in ["_", "-", "/"] or "\u4e00" <= char <= "\u9fff"
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)
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# print("dir_name:", dir_name)
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if dir_name and not os.path.exists(dir_name):
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os.makedirs(dir_name, exist_ok=True)
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# 写入文件
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file_path = os.path.join(dir_name, os.path.basename(file_path))
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# print("file_path:", file_path)
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with open(file_path, "a", encoding="utf-8") as f:
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f.write(json.dumps(self.to_dict(), ensure_ascii=False) + "\n")
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def set_thinking_id(self, thinking_id: str):
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"""设置思考消息ID"""
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self.thinking_id = thinking_id
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def set_loop_info(self, loop_info: Dict[str, Any]):
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"""设置循环信息"""
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self.loop_observation_info = loop_info["loop_observation_info"]
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self.loop_processor_info = loop_info["loop_processor_info"]
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self.loop_plan_info = loop_info["loop_plan_info"]
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self.loop_action_info = loop_info["loop_action_info"]
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@@ -9,17 +9,14 @@ from rich.traceback import install
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from src.chat.utils.prompt_builder import global_prompt_manager
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from src.common.logger import get_logger
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from src.chat.utils.timer_calculator import Timer
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from src.chat.heart_flow.observation.observation import Observation
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from src.chat.focus_chat.heartFC_Cycleinfo import CycleDetail
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from src.chat.focus_chat.observation.observation import Observation
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from src.chat.focus_chat.info.info_base import InfoBase
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from src.chat.focus_chat.info_processors.chattinginfo_processor import ChattingInfoProcessor
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from src.chat.focus_chat.info_processors.working_memory_processor import WorkingMemoryProcessor
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from src.chat.heart_flow.observation.hfcloop_observation import HFCloopObservation
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from src.chat.heart_flow.observation.working_observation import WorkingMemoryObservation
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from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
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from src.chat.heart_flow.observation.actions_observation import ActionObservation
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from src.chat.focus_chat.memory_activator import MemoryActivator
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from src.chat.focus_chat.observation.hfcloop_observation import HFCloopObservation
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from src.chat.focus_chat.observation.working_observation import WorkingMemoryObservation
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from src.chat.focus_chat.observation.chatting_observation import ChattingObservation
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from src.chat.focus_chat.observation.actions_observation import ActionObservation
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from src.chat.focus_chat.info_processors.base_processor import BaseProcessor
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from src.chat.planner_actions.planner_focus import ActionPlanner
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from src.chat.planner_actions.action_modifier import ActionModifier
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@@ -28,6 +25,7 @@ from src.config.config import global_config
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from src.chat.focus_chat.hfc_performance_logger import HFCPerformanceLogger
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from src.chat.focus_chat.hfc_version_manager import get_hfc_version
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from src.person_info.relationship_builder_manager import relationship_builder_manager
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from src.chat.focus_chat.hfc_utils import CycleDetail
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install(extra_lines=3)
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@@ -76,8 +74,6 @@ class HeartFChatting:
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self.chat_stream = get_chat_manager().get_stream(self.stream_id)
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self.log_prefix = f"[{get_chat_manager().get_stream_name(self.stream_id) or self.stream_id}]"
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self.memory_activator = MemoryActivator()
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self.relationship_builder = relationship_builder_manager.get_or_create_builder(self.stream_id)
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# 新增：消息计数器和疲惫阈值
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@@ -1,152 +0,0 @@
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from src.chat.memory_system.Hippocampus import hippocampus_manager
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from src.config.config import global_config
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from src.chat.message_receive.message import MessageRecv
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from src.chat.message_receive.storage import MessageStorage
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from src.chat.heart_flow.heartflow import heartflow
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from src.chat.message_receive.chat_stream import get_chat_manager
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from src.chat.utils.utils import is_mentioned_bot_in_message
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from src.chat.utils.timer_calculator import Timer
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from src.common.logger import get_logger
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import re
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import math
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import traceback
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from typing import Optional, Tuple
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from src.person_info.relationship_manager import get_relationship_manager
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# from ..message_receive.message_buffer import message_buffer
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logger = get_logger("chat")
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async def _handle_error(error: Exception, context: str, message: Optional[MessageRecv] = None) -> None:
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"""统一的错误处理函数
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Args:
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error: 捕获到的异常
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context: 错误发生的上下文描述
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message: 可选的消息对象，用于记录相关消息内容
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"""
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logger.error(f"{context}: {error}")
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logger.error(traceback.format_exc())
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if message and hasattr(message, "raw_message"):
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logger.error(f"相关消息原始内容: {message.raw_message}")
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async def _process_relationship(message: MessageRecv) -> None:
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"""处理用户关系逻辑
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Args:
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message: 消息对象，包含用户信息
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"""
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platform = message.message_info.platform
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user_id = message.message_info.user_info.user_id
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nickname = message.message_info.user_info.user_nickname
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cardname = message.message_info.user_info.user_cardname or nickname
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relationship_manager = get_relationship_manager()
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is_known = await relationship_manager.is_known_some_one(platform, user_id)
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if not is_known:
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logger.info(f"首次认识用户: {nickname}")
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await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname)
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async def _calculate_interest(message: MessageRecv) -> Tuple[float, bool]:
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"""计算消息的兴趣度
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Args:
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message: 待处理的消息对象
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Returns:
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Tuple[float, bool]: (兴趣度, 是否被提及)
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"""
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is_mentioned, _ = is_mentioned_bot_in_message(message)
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interested_rate = 0.0
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if global_config.memory.enable_memory:
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with Timer("记忆激活"):
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interested_rate = await hippocampus_manager.get_activate_from_text(
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message.processed_plain_text,
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fast_retrieval=True,
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)
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logger.debug(f"记忆激活率: {interested_rate:.2f}")
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text_len = len(message.processed_plain_text)
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# 根据文本长度调整兴趣度，长度越大兴趣度越高，但增长率递减，最低0.01，最高0.05
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# 采用对数函数实现递减增长
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base_interest = 0.01 + (0.05 - 0.01) * (math.log10(text_len + 1) / math.log10(1000 + 1))
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base_interest = min(max(base_interest, 0.01), 0.05)
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interested_rate += base_interest
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if is_mentioned:
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interest_increase_on_mention = 1
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interested_rate += interest_increase_on_mention
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return interested_rate, is_mentioned
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class HeartFCMessageReceiver:
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"""心流处理器，负责处理接收到的消息并计算兴趣度"""
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def __init__(self):
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"""初始化心流处理器，创建消息存储实例"""
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self.storage = MessageStorage()
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async def process_message(self, message: MessageRecv) -> None:
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"""处理接收到的原始消息数据
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主要流程:
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1. 消息解析与初始化
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2. 消息缓冲处理
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3. 过滤检查
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4. 兴趣度计算
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5. 关系处理
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Args:
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message_data: 原始消息字符串
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"""
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try:
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# 1. 消息解析与初始化
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groupinfo = message.message_info.group_info
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userinfo = message.message_info.user_info
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messageinfo = message.message_info
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chat = await get_chat_manager().get_or_create_stream(
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platform=messageinfo.platform,
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user_info=userinfo,
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group_info=groupinfo,
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)
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await self.storage.store_message(message, chat)
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subheartflow = await heartflow.get_or_create_subheartflow(chat.stream_id)
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message.update_chat_stream(chat)
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# 6. 兴趣度计算与更新
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interested_rate, is_mentioned = await _calculate_interest(message)
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subheartflow.add_message_to_normal_chat_cache(message, interested_rate, is_mentioned)
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# 7. 日志记录
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mes_name = chat.group_info.group_name if chat.group_info else "私聊"
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# current_time = time.strftime("%H:%M:%S", time.localtime(message.message_info.time))
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current_talk_frequency = global_config.chat.get_current_talk_frequency(chat.stream_id)
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# 如果消息中包含图片标识，则日志展示为图片
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picid_match = re.search(r"\[picid:([^\]]+)\]", message.processed_plain_text)
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if picid_match:
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logger.info(f"[{mes_name}]{userinfo.user_nickname}: [图片] [当前回复频率: {current_talk_frequency}]")
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else:
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logger.info(
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f"[{mes_name}]{userinfo.user_nickname}:{message.processed_plain_text}[当前回复频率: {current_talk_frequency}]"
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)
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# 8. 关系处理
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if global_config.relationship.enable_relationship:
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await _process_relationship(message)
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except Exception as e:
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await _handle_error(e, "消息处理失败", message)
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@@ -5,9 +5,143 @@ from src.chat.message_receive.chat_stream import ChatStream
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from src.chat.message_receive.message import UserInfo
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from src.common.logger import get_logger
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import json
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import time
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import os
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from typing import Optional, Dict, Any
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from src.common.logger import get_logger
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import json
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logger = get_logger(__name__)
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log_dir = "log/log_cycle_debug/"
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class CycleDetail:
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"""循环信息记录类"""
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def __init__(self, cycle_id: int):
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self.cycle_id = cycle_id
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self.prefix = ""
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self.thinking_id = ""
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self.start_time = time.time()
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self.end_time: Optional[float] = None
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self.timers: Dict[str, float] = {}
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# 新字段
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self.loop_observation_info: Dict[str, Any] = {}
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self.loop_processor_info: Dict[str, Any] = {} # 前处理器信息
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self.loop_plan_info: Dict[str, Any] = {}
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self.loop_action_info: Dict[str, Any] = {}
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def to_dict(self) -> Dict[str, Any]:
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"""将循环信息转换为字典格式"""
|
||||
|
||||
def convert_to_serializable(obj, depth=0, seen=None):
|
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if seen is None:
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seen = set()
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# 防止递归过深
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if depth > 5: # 降低递归深度限制
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return str(obj)
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# 防止循环引用
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obj_id = id(obj)
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if obj_id in seen:
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return str(obj)
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seen.add(obj_id)
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try:
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if hasattr(obj, "to_dict"):
|
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# 对于有to_dict方法的对象，直接调用其to_dict方法
|
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return obj.to_dict()
|
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elif isinstance(obj, dict):
|
||||
# 对于字典，只保留基本类型和可序列化的值
|
||||
return {
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k: convert_to_serializable(v, depth + 1, seen)
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for k, v in obj.items()
|
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if isinstance(k, (str, int, float, bool))
|
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}
|
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elif isinstance(obj, (list, tuple)):
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# 对于列表和元组，只保留可序列化的元素
|
||||
return [
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convert_to_serializable(item, depth + 1, seen)
|
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for item in obj
|
||||
if not isinstance(item, (dict, list, tuple))
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or isinstance(item, (str, int, float, bool, type(None)))
|
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]
|
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elif isinstance(obj, (str, int, float, bool, type(None))):
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return obj
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else:
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return str(obj)
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finally:
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seen.remove(obj_id)
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return {
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"cycle_id": self.cycle_id,
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"start_time": self.start_time,
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"end_time": self.end_time,
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"timers": self.timers,
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"thinking_id": self.thinking_id,
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"loop_observation_info": convert_to_serializable(self.loop_observation_info),
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"loop_processor_info": convert_to_serializable(self.loop_processor_info),
|
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"loop_plan_info": convert_to_serializable(self.loop_plan_info),
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||||
"loop_action_info": convert_to_serializable(self.loop_action_info),
|
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}
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||||
|
||||
def complete_cycle(self):
|
||||
"""完成循环，记录结束时间"""
|
||||
self.end_time = time.time()
|
||||
|
||||
# 处理 prefix，只保留中英文字符和基本标点
|
||||
if not self.prefix:
|
||||
self.prefix = "group"
|
||||
else:
|
||||
# 只保留中文、英文字母、数字和基本标点
|
||||
allowed_chars = set("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789-_")
|
||||
self.prefix = (
|
||||
"".join(char for char in self.prefix if "\u4e00" <= char <= "\u9fff" or char in allowed_chars)
|
||||
or "group"
|
||||
)
|
||||
|
||||
# current_time_minute = time.strftime("%Y%m%d_%H%M", time.localtime())
|
||||
|
||||
# try:
|
||||
# self.log_cycle_to_file(
|
||||
# log_dir + self.prefix + f"/{current_time_minute}_cycle_" + str(self.cycle_id) + ".json"
|
||||
# )
|
||||
# except Exception as e:
|
||||
# logger.warning(f"写入文件日志，可能是群名称包含非法字符: {e}")
|
||||
|
||||
def log_cycle_to_file(self, file_path: str):
|
||||
"""将循环信息写入文件"""
|
||||
# 如果目录不存在，则创建目
|
||||
dir_name = os.path.dirname(file_path)
|
||||
# 去除特殊字符，保留字母、数字、下划线、中划线和中文
|
||||
dir_name = "".join(
|
||||
char for char in dir_name if char.isalnum() or char in ["_", "-", "/"] or "\u4e00" <= char <= "\u9fff"
|
||||
)
|
||||
# print("dir_name:", dir_name)
|
||||
if dir_name and not os.path.exists(dir_name):
|
||||
os.makedirs(dir_name, exist_ok=True)
|
||||
# 写入文件
|
||||
|
||||
file_path = os.path.join(dir_name, os.path.basename(file_path))
|
||||
# print("file_path:", file_path)
|
||||
with open(file_path, "a", encoding="utf-8") as f:
|
||||
f.write(json.dumps(self.to_dict(), ensure_ascii=False) + "\n")
|
||||
|
||||
def set_thinking_id(self, thinking_id: str):
|
||||
"""设置思考消息ID"""
|
||||
self.thinking_id = thinking_id
|
||||
|
||||
def set_loop_info(self, loop_info: Dict[str, Any]):
|
||||
"""设置循环信息"""
|
||||
self.loop_observation_info = loop_info["loop_observation_info"]
|
||||
self.loop_processor_info = loop_info["loop_processor_info"]
|
||||
self.loop_plan_info = loop_info["loop_plan_info"]
|
||||
self.loop_action_info = loop_info["loop_action_info"]
|
||||
|
||||
|
||||
|
||||
async def create_empty_anchor_message(
|
||||
platform: str, group_info: dict, chat_stream: ChatStream
|
||||
|
||||
@@ -1,97 +0,0 @@
|
||||
from typing import Dict, Optional
|
||||
from dataclasses import dataclass
|
||||
from .info_base import InfoBase
|
||||
|
||||
|
||||
@dataclass
|
||||
class ChatInfo(InfoBase):
|
||||
"""聊天信息类
|
||||
|
||||
用于记录和管理聊天相关的信息，包括聊天ID、名称和类型等。
|
||||
继承自 InfoBase 类，使用字典存储具体数据。
|
||||
|
||||
Attributes:
|
||||
type (str): 信息类型标识符，固定为 "chat"
|
||||
|
||||
Data Fields:
|
||||
chat_id (str): 聊天的唯一标识符
|
||||
chat_name (str): 聊天的名称
|
||||
chat_type (str): 聊天的类型
|
||||
"""
|
||||
|
||||
type: str = "chat"
|
||||
|
||||
def set_chat_id(self, chat_id: str) -> None:
|
||||
"""设置聊天ID
|
||||
|
||||
Args:
|
||||
chat_id (str): 聊天的唯一标识符
|
||||
"""
|
||||
self.data["chat_id"] = chat_id
|
||||
|
||||
def set_chat_name(self, chat_name: str) -> None:
|
||||
"""设置聊天名称
|
||||
|
||||
Args:
|
||||
chat_name (str): 聊天的名称
|
||||
"""
|
||||
self.data["chat_name"] = chat_name
|
||||
|
||||
def set_chat_type(self, chat_type: str) -> None:
|
||||
"""设置聊天类型
|
||||
|
||||
Args:
|
||||
chat_type (str): 聊天的类型
|
||||
"""
|
||||
self.data["chat_type"] = chat_type
|
||||
|
||||
def get_chat_id(self) -> Optional[str]:
|
||||
"""获取聊天ID
|
||||
|
||||
Returns:
|
||||
Optional[str]: 聊天的唯一标识符，如果未设置则返回 None
|
||||
"""
|
||||
return self.get_info("chat_id")
|
||||
|
||||
def get_chat_name(self) -> Optional[str]:
|
||||
"""获取聊天名称
|
||||
|
||||
Returns:
|
||||
Optional[str]: 聊天的名称，如果未设置则返回 None
|
||||
"""
|
||||
return self.get_info("chat_name")
|
||||
|
||||
def get_chat_type(self) -> Optional[str]:
|
||||
"""获取聊天类型
|
||||
|
||||
Returns:
|
||||
Optional[str]: 聊天的类型，如果未设置则返回 None
|
||||
"""
|
||||
return self.get_info("chat_type")
|
||||
|
||||
def get_type(self) -> str:
|
||||
"""获取信息类型
|
||||
|
||||
Returns:
|
||||
str: 当前信息对象的类型标识符
|
||||
"""
|
||||
return self.type
|
||||
|
||||
def get_data(self) -> Dict[str, str]:
|
||||
"""获取所有信息数据
|
||||
|
||||
Returns:
|
||||
Dict[str, str]: 包含所有信息数据的字典
|
||||
"""
|
||||
return self.data
|
||||
|
||||
def get_info(self, key: str) -> Optional[str]:
|
||||
"""获取特定属性的信息
|
||||
|
||||
Args:
|
||||
key: 要获取的属性键名
|
||||
|
||||
Returns:
|
||||
Optional[str]: 属性值，如果键不存在则返回 None
|
||||
"""
|
||||
return self.data.get(key)
|
||||
@@ -1,7 +1,7 @@
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import List, Any
|
||||
from src.chat.focus_chat.info.info_base import InfoBase
|
||||
from src.chat.heart_flow.observation.observation import Observation
|
||||
from src.chat.focus_chat.observation.observation import Observation
|
||||
from src.common.logger import get_logger
|
||||
|
||||
logger = get_logger("base_processor")
|
||||
|
||||
@@ -1,10 +1,10 @@
|
||||
from typing import List, Any
|
||||
from src.chat.focus_chat.info.obs_info import ObsInfo
|
||||
from src.chat.heart_flow.observation.observation import Observation
|
||||
from src.chat.focus_chat.observation.observation import Observation
|
||||
from src.chat.focus_chat.info.info_base import InfoBase
|
||||
from .base_processor import BaseProcessor
|
||||
from src.common.logger import get_logger
|
||||
from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
|
||||
from src.chat.focus_chat.observation.chatting_observation import ChattingObservation
|
||||
from datetime import datetime
|
||||
from src.llm_models.utils_model import LLMRequest
|
||||
from src.config.config import global_config
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
|
||||
from src.chat.heart_flow.observation.observation import Observation
|
||||
from src.chat.focus_chat.observation.chatting_observation import ChattingObservation
|
||||
from src.chat.focus_chat.observation.observation import Observation
|
||||
from src.llm_models.utils_model import LLMRequest
|
||||
from src.config.config import global_config
|
||||
import time
|
||||
@@ -9,7 +9,7 @@ from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
from .base_processor import BaseProcessor
|
||||
from typing import List
|
||||
from src.chat.heart_flow.observation.working_observation import WorkingMemoryObservation
|
||||
from src.chat.focus_chat.observation.working_observation import WorkingMemoryObservation
|
||||
from src.chat.focus_chat.working_memory.working_memory import WorkingMemory
|
||||
from src.chat.focus_chat.info.info_base import InfoBase
|
||||
from json_repair import repair_json
|
||||
|
||||
@@ -1,154 +0,0 @@
|
||||
from src.llm_models.utils_model import LLMRequest
|
||||
from src.config.config import global_config
|
||||
from src.common.logger import get_logger
|
||||
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
|
||||
from datetime import datetime
|
||||
from src.chat.memory_system.Hippocampus import hippocampus_manager
|
||||
from typing import List, Dict
|
||||
import difflib
|
||||
import json
|
||||
from json_repair import repair_json
|
||||
|
||||
|
||||
logger = get_logger("memory_activator")
|
||||
|
||||
|
||||
def get_keywords_from_json(json_str):
|
||||
"""
|
||||
从JSON字符串中提取关键词列表
|
||||
|
||||
Args:
|
||||
json_str: JSON格式的字符串
|
||||
|
||||
Returns:
|
||||
List[str]: 关键词列表
|
||||
"""
|
||||
try:
|
||||
# 使用repair_json修复JSON格式
|
||||
fixed_json = repair_json(json_str)
|
||||
|
||||
# 如果repair_json返回的是字符串，需要解析为Python对象
|
||||
if isinstance(fixed_json, str):
|
||||
result = json.loads(fixed_json)
|
||||
else:
|
||||
# 如果repair_json直接返回了字典对象，直接使用
|
||||
result = fixed_json
|
||||
|
||||
# 提取关键词
|
||||
keywords = result.get("keywords", [])
|
||||
return keywords
|
||||
except Exception as e:
|
||||
logger.error(f"解析关键词JSON失败: {e}")
|
||||
return []
|
||||
|
||||
|
||||
def init_prompt():
|
||||
# --- Group Chat Prompt ---
|
||||
memory_activator_prompt = """
|
||||
你是一个记忆分析器，你需要根据以下信息来进行回忆
|
||||
以下是一段聊天记录，请根据这些信息，总结出几个关键词作为记忆回忆的触发词
|
||||
|
||||
聊天记录:
|
||||
{obs_info_text}
|
||||
你想要回复的消息:
|
||||
{target_message}
|
||||
|
||||
历史关键词（请避免重复提取这些关键词）：
|
||||
{cached_keywords}
|
||||
|
||||
请输出一个json格式，包含以下字段：
|
||||
{{
|
||||
"keywords": ["关键词1", "关键词2", "关键词3",......]
|
||||
}}
|
||||
不要输出其他多余内容，只输出json格式就好
|
||||
"""
|
||||
|
||||
Prompt(memory_activator_prompt, "memory_activator_prompt")
|
||||
|
||||
|
||||
class MemoryActivator:
|
||||
def __init__(self):
|
||||
# TODO: API-Adapter修改标记
|
||||
self.summary_model = LLMRequest(
|
||||
model=global_config.model.memory_summary,
|
||||
temperature=0.7,
|
||||
request_type="memory_activator",
|
||||
)
|
||||
self.running_memory = []
|
||||
self.cached_keywords = set() # 用于缓存历史关键词
|
||||
|
||||
async def activate_memory_with_chat_history(self, target_message, chat_history_prompt) -> List[Dict]:
|
||||
"""
|
||||
激活记忆
|
||||
|
||||
Args:
|
||||
observations: 现有的进行观察后的 观察列表
|
||||
|
||||
Returns:
|
||||
List[Dict]: 激活的记忆列表
|
||||
"""
|
||||
# 如果记忆系统被禁用，直接返回空列表
|
||||
if not global_config.memory.enable_memory:
|
||||
return []
|
||||
|
||||
# 将缓存的关键词转换为字符串，用于prompt
|
||||
cached_keywords_str = ", ".join(self.cached_keywords) if self.cached_keywords else "暂无历史关键词"
|
||||
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
"memory_activator_prompt",
|
||||
obs_info_text=chat_history_prompt,
|
||||
target_message=target_message,
|
||||
cached_keywords=cached_keywords_str,
|
||||
)
|
||||
|
||||
# logger.debug(f"prompt: {prompt}")
|
||||
|
||||
response, (reasoning_content, model_name) = await self.summary_model.generate_response_async(prompt)
|
||||
|
||||
keywords = list(get_keywords_from_json(response))
|
||||
|
||||
# 更新关键词缓存
|
||||
if keywords:
|
||||
# 限制缓存大小，最多保留10个关键词
|
||||
if len(self.cached_keywords) > 10:
|
||||
# 转换为列表，移除最早的关键词
|
||||
cached_list = list(self.cached_keywords)
|
||||
self.cached_keywords = set(cached_list[-8:])
|
||||
|
||||
# 添加新的关键词到缓存
|
||||
self.cached_keywords.update(keywords)
|
||||
|
||||
|
||||
# 调用记忆系统获取相关记忆
|
||||
related_memory = await hippocampus_manager.get_memory_from_topic(
|
||||
valid_keywords=keywords, max_memory_num=3, max_memory_length=2, max_depth=3
|
||||
)
|
||||
|
||||
logger.info(f"当前记忆关键词: {self.cached_keywords} 。获取到的记忆: {related_memory}")
|
||||
|
||||
# 激活时，所有已有记忆的duration+1，达到3则移除
|
||||
for m in self.running_memory[:]:
|
||||
m["duration"] = m.get("duration", 1) + 1
|
||||
self.running_memory = [m for m in self.running_memory if m["duration"] < 3]
|
||||
|
||||
if related_memory:
|
||||
for topic, memory in related_memory:
|
||||
# 检查是否已存在相同topic或相似内容（相似度>=0.7）的记忆
|
||||
exists = any(
|
||||
m["topic"] == topic or difflib.SequenceMatcher(None, m["content"], memory).ratio() >= 0.7
|
||||
for m in self.running_memory
|
||||
)
|
||||
if not exists:
|
||||
self.running_memory.append(
|
||||
{"topic": topic, "content": memory, "timestamp": datetime.now().isoformat(), "duration": 1}
|
||||
)
|
||||
logger.debug(f"添加新记忆: {topic} - {memory}")
|
||||
|
||||
# 限制同时加载的记忆条数，最多保留最后3条
|
||||
if len(self.running_memory) > 3:
|
||||
self.running_memory = self.running_memory[-3:]
|
||||
|
||||
return self.running_memory
|
||||
|
||||
|
||||
init_prompt()
|
||||
46
src/chat/focus_chat/observation/actions_observation.py
Normal file
46
src/chat/focus_chat/observation/actions_observation.py
Normal file
@@ -0,0 +1,46 @@
|
||||
# 定义了来自外部世界的信息
|
||||
# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
|
||||
from datetime import datetime
|
||||
from src.common.logger import get_logger
|
||||
from src.chat.planner_actions.action_manager import ActionManager
|
||||
|
||||
logger = get_logger("observation")
|
||||
|
||||
|
||||
# 特殊的观察，专门用于观察动作
|
||||
# 所有观察的基类
|
||||
class ActionObservation:
|
||||
def __init__(self, observe_id):
|
||||
self.observe_info = ""
|
||||
self.observe_id = observe_id
|
||||
self.last_observe_time = datetime.now().timestamp() # 初始化为当前时间
|
||||
self.action_manager: ActionManager = None
|
||||
|
||||
self.all_actions = {}
|
||||
self.all_using_actions = {}
|
||||
|
||||
def get_observe_info(self):
|
||||
return self.observe_info
|
||||
|
||||
def set_action_manager(self, action_manager: ActionManager):
|
||||
self.action_manager = action_manager
|
||||
self.all_actions = self.action_manager.get_registered_actions()
|
||||
|
||||
async def observe(self):
|
||||
action_info_block = ""
|
||||
self.all_using_actions = self.action_manager.get_using_actions()
|
||||
for action_name, action_info in self.all_using_actions.items():
|
||||
action_info_block += f"\n{action_name}: {action_info.get('description', '')}"
|
||||
action_info_block += "\n注意，除了上面动作选项之外，你在群聊里不能做其他任何事情，这是你能力的边界\n"
|
||||
|
||||
self.observe_info = action_info_block
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将观察对象转换为可序列化的字典"""
|
||||
return {
|
||||
"observe_info": self.observe_info,
|
||||
"observe_id": self.observe_id,
|
||||
"last_observe_time": self.last_observe_time,
|
||||
"all_actions": self.all_actions,
|
||||
"all_using_actions": self.all_using_actions,
|
||||
}
|
||||
183
src/chat/focus_chat/observation/chatting_observation.py
Normal file
183
src/chat/focus_chat/observation/chatting_observation.py
Normal file
@@ -0,0 +1,183 @@
|
||||
from datetime import datetime
|
||||
from src.config.config import global_config
|
||||
from src.chat.utils.chat_message_builder import (
|
||||
get_raw_msg_before_timestamp_with_chat,
|
||||
build_readable_messages,
|
||||
get_raw_msg_by_timestamp_with_chat,
|
||||
num_new_messages_since,
|
||||
get_person_id_list,
|
||||
)
|
||||
from src.chat.utils.prompt_builder import global_prompt_manager, Prompt
|
||||
from src.chat.focus_chat.observation.observation import Observation
|
||||
from src.common.logger import get_logger
|
||||
from src.chat.utils.utils import get_chat_type_and_target_info
|
||||
|
||||
logger = get_logger("observation")
|
||||
|
||||
# 定义提示模板
|
||||
Prompt(
|
||||
"""这是{chat_type_description}，请总结以下聊天记录的主题：
|
||||
{chat_logs}
|
||||
请概括这段聊天记录的主题和主要内容
|
||||
主题：简短的概括，包括时间，人物和事件，不要超过20个字
|
||||
内容：具体的信息内容，包括人物、事件和信息，不要超过200个字，不要分点。
|
||||
|
||||
请用json格式返回，格式如下：
|
||||
{{
|
||||
"theme": "主题，例如 2025-06-14 10:00:00 群聊 麦麦 和 网友 讨论了 游戏 的话题",
|
||||
"content": "内容，可以是对聊天记录的概括，也可以是聊天记录的详细内容"
|
||||
}}
|
||||
""",
|
||||
"chat_summary_prompt",
|
||||
)
|
||||
|
||||
|
||||
class ChattingObservation(Observation):
|
||||
def __init__(self, chat_id):
|
||||
super().__init__(chat_id)
|
||||
self.chat_id = chat_id
|
||||
self.platform = "qq"
|
||||
|
||||
self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_id)
|
||||
|
||||
self.talking_message = []
|
||||
self.talking_message_str = ""
|
||||
self.talking_message_str_truncate = ""
|
||||
self.talking_message_str_short = ""
|
||||
self.talking_message_str_truncate_short = ""
|
||||
self.name = global_config.bot.nickname
|
||||
self.nick_name = global_config.bot.alias_names
|
||||
self.max_now_obs_len = global_config.chat.max_context_size
|
||||
self.overlap_len = global_config.focus_chat.compressed_length
|
||||
self.person_list = []
|
||||
self.compressor_prompt = ""
|
||||
self.oldest_messages = []
|
||||
self.oldest_messages_str = ""
|
||||
|
||||
self.last_observe_time = datetime.now().timestamp()
|
||||
initial_messages = get_raw_msg_before_timestamp_with_chat(self.chat_id, self.last_observe_time, 10)
|
||||
initial_messages_short = get_raw_msg_before_timestamp_with_chat(self.chat_id, self.last_observe_time, 5)
|
||||
self.last_observe_time = initial_messages[-1]["time"] if initial_messages else self.last_observe_time
|
||||
self.talking_message = initial_messages
|
||||
self.talking_message_short = initial_messages_short
|
||||
self.talking_message_str = build_readable_messages(self.talking_message, show_actions=True)
|
||||
self.talking_message_str_truncate = build_readable_messages(
|
||||
self.talking_message, show_actions=True, truncate=True
|
||||
)
|
||||
self.talking_message_str_short = build_readable_messages(self.talking_message_short, show_actions=True)
|
||||
self.talking_message_str_truncate_short = build_readable_messages(
|
||||
self.talking_message_short, show_actions=True, truncate=True
|
||||
)
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将观察对象转换为可序列化的字典"""
|
||||
return {
|
||||
"chat_id": self.chat_id,
|
||||
"platform": self.platform,
|
||||
"is_group_chat": self.is_group_chat,
|
||||
"chat_target_info": self.chat_target_info,
|
||||
"talking_message_str": self.talking_message_str,
|
||||
"talking_message_str_truncate": self.talking_message_str_truncate,
|
||||
"talking_message_str_short": self.talking_message_str_short,
|
||||
"talking_message_str_truncate_short": self.talking_message_str_truncate_short,
|
||||
"name": self.name,
|
||||
"nick_name": self.nick_name,
|
||||
"last_observe_time": self.last_observe_time,
|
||||
}
|
||||
|
||||
def get_observe_info(self, ids=None):
|
||||
return self.talking_message_str
|
||||
|
||||
async def observe(self):
|
||||
# 自上一次观察的新消息
|
||||
new_messages_list = get_raw_msg_by_timestamp_with_chat(
|
||||
chat_id=self.chat_id,
|
||||
timestamp_start=self.last_observe_time,
|
||||
timestamp_end=datetime.now().timestamp(),
|
||||
limit=self.max_now_obs_len,
|
||||
limit_mode="latest",
|
||||
)
|
||||
|
||||
# print(f"new_messages_list: {new_messages_list}")
|
||||
|
||||
last_obs_time_mark = self.last_observe_time
|
||||
if new_messages_list:
|
||||
self.last_observe_time = new_messages_list[-1]["time"]
|
||||
self.talking_message.extend(new_messages_list)
|
||||
|
||||
if len(self.talking_message) > self.max_now_obs_len:
|
||||
# 计算需要移除的消息数量，保留最新的 max_now_obs_len 条
|
||||
messages_to_remove_count = len(self.talking_message) - self.max_now_obs_len
|
||||
oldest_messages = self.talking_message[:messages_to_remove_count]
|
||||
self.talking_message = self.talking_message[messages_to_remove_count:]
|
||||
|
||||
# 构建压缩提示
|
||||
oldest_messages_str = build_readable_messages(
|
||||
messages=oldest_messages, timestamp_mode="normal_no_YMD", read_mark=0, show_actions=True
|
||||
)
|
||||
|
||||
# 根据聊天类型选择提示模板
|
||||
prompt_template_name = "chat_summary_prompt"
|
||||
if self.is_group_chat:
|
||||
chat_type_description = "qq群聊的聊天记录"
|
||||
else:
|
||||
chat_target_name = "对方"
|
||||
if self.chat_target_info:
|
||||
chat_target_name = (
|
||||
self.chat_target_info.get("person_name")
|
||||
or self.chat_target_info.get("user_nickname")
|
||||
or chat_target_name
|
||||
)
|
||||
chat_type_description = f"你和{chat_target_name}的私聊记录"
|
||||
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
prompt_template_name,
|
||||
chat_type_description=chat_type_description,
|
||||
chat_logs=oldest_messages_str,
|
||||
)
|
||||
|
||||
self.compressor_prompt = prompt
|
||||
|
||||
# 构建当前消息
|
||||
self.talking_message_str = build_readable_messages(
|
||||
messages=self.talking_message,
|
||||
timestamp_mode="lite",
|
||||
read_mark=last_obs_time_mark,
|
||||
show_actions=True,
|
||||
)
|
||||
self.talking_message_str_truncate = build_readable_messages(
|
||||
messages=self.talking_message,
|
||||
timestamp_mode="normal_no_YMD",
|
||||
read_mark=last_obs_time_mark,
|
||||
truncate=True,
|
||||
show_actions=True,
|
||||
)
|
||||
|
||||
# 构建简短版本 - 使用最新一半的消息
|
||||
half_count = len(self.talking_message) // 2
|
||||
recent_messages = self.talking_message[-half_count:] if half_count > 0 else self.talking_message
|
||||
|
||||
self.talking_message_str_short = build_readable_messages(
|
||||
messages=recent_messages,
|
||||
timestamp_mode="lite",
|
||||
read_mark=last_obs_time_mark,
|
||||
show_actions=True,
|
||||
)
|
||||
self.talking_message_str_truncate_short = build_readable_messages(
|
||||
messages=recent_messages,
|
||||
timestamp_mode="normal_no_YMD",
|
||||
read_mark=last_obs_time_mark,
|
||||
truncate=True,
|
||||
show_actions=True,
|
||||
)
|
||||
|
||||
self.person_list = await get_person_id_list(self.talking_message)
|
||||
|
||||
# logger.debug(
|
||||
# f"Chat {self.chat_id} - 现在聊天内容：{self.talking_message_str}"
|
||||
# )
|
||||
|
||||
async def has_new_messages_since(self, timestamp: float) -> bool:
|
||||
"""检查指定时间戳之后是否有新消息"""
|
||||
count = num_new_messages_since(chat_id=self.chat_id, timestamp_start=timestamp)
|
||||
return count > 0
|
||||
128
src/chat/focus_chat/observation/hfcloop_observation.py
Normal file
128
src/chat/focus_chat/observation/hfcloop_observation.py
Normal file
@@ -0,0 +1,128 @@
|
||||
# 定义了来自外部世界的信息
|
||||
# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
|
||||
from datetime import datetime
|
||||
from src.common.logger import get_logger
|
||||
from src.chat.focus_chat.hfc_utils import CycleDetail
|
||||
from typing import List
|
||||
# Import the new utility function
|
||||
|
||||
logger = get_logger("observation")
|
||||
|
||||
|
||||
# 所有观察的基类
|
||||
class HFCloopObservation:
|
||||
def __init__(self, observe_id):
|
||||
self.observe_info = ""
|
||||
self.observe_id = observe_id
|
||||
self.last_observe_time = datetime.now().timestamp() # 初始化为当前时间
|
||||
self.history_loop: List[CycleDetail] = []
|
||||
|
||||
def get_observe_info(self):
|
||||
return self.observe_info
|
||||
|
||||
def add_loop_info(self, loop_info: CycleDetail):
|
||||
self.history_loop.append(loop_info)
|
||||
|
||||
async def observe(self):
|
||||
recent_active_cycles: List[CycleDetail] = []
|
||||
for cycle in reversed(self.history_loop):
|
||||
# 只关心实际执行了动作的循环
|
||||
# action_taken = cycle.loop_action_info["action_taken"]
|
||||
# if action_taken:
|
||||
recent_active_cycles.append(cycle)
|
||||
if len(recent_active_cycles) == 5:
|
||||
break
|
||||
|
||||
cycle_info_block = ""
|
||||
action_detailed_str = ""
|
||||
consecutive_text_replies = 0
|
||||
responses_for_prompt = []
|
||||
|
||||
cycle_last_reason = ""
|
||||
|
||||
# 检查这最近的活动循环中有多少是连续的文本回复 (从最近的开始看)
|
||||
for cycle in recent_active_cycles:
|
||||
action_result = cycle.loop_plan_info.get("action_result", {})
|
||||
action_type = action_result.get("action_type", "unknown")
|
||||
action_reasoning = action_result.get("reasoning", "未提供理由")
|
||||
is_taken = cycle.loop_action_info.get("action_taken", False)
|
||||
action_taken_time = cycle.loop_action_info.get("taken_time", 0)
|
||||
action_taken_time_str = (
|
||||
datetime.fromtimestamp(action_taken_time).strftime("%H:%M:%S") if action_taken_time > 0 else "未知时间"
|
||||
)
|
||||
# print(action_type)
|
||||
# print(action_reasoning)
|
||||
# print(is_taken)
|
||||
# print(action_taken_time_str)
|
||||
# print("--------------------------------")
|
||||
if action_reasoning != cycle_last_reason:
|
||||
cycle_last_reason = action_reasoning
|
||||
action_reasoning_str = f"你选择这个action的原因是:{action_reasoning}"
|
||||
else:
|
||||
action_reasoning_str = ""
|
||||
|
||||
if action_type == "reply":
|
||||
consecutive_text_replies += 1
|
||||
response_text = cycle.loop_action_info.get("reply_text", "")
|
||||
responses_for_prompt.append(response_text)
|
||||
|
||||
if is_taken:
|
||||
action_detailed_str += f"{action_taken_time_str}时，你选择回复(action:{action_type},内容是:'{response_text}')。{action_reasoning_str}\n"
|
||||
else:
|
||||
action_detailed_str += f"{action_taken_time_str}时，你选择回复(action:{action_type},内容是:'{response_text}')，但是动作失败了。{action_reasoning_str}\n"
|
||||
elif action_type == "no_reply":
|
||||
# action_detailed_str += (
|
||||
# f"{action_taken_time_str}时，你选择不回复(action:{action_type})，{action_reasoning_str}\n"
|
||||
# )
|
||||
pass
|
||||
else:
|
||||
if is_taken:
|
||||
action_detailed_str += (
|
||||
f"{action_taken_time_str}时，你选择执行了(action:{action_type})，{action_reasoning_str}\n"
|
||||
)
|
||||
else:
|
||||
action_detailed_str += f"{action_taken_time_str}时，你选择执行了(action:{action_type})，但是动作失败了。{action_reasoning_str}\n"
|
||||
|
||||
if action_detailed_str:
|
||||
cycle_info_block = f"\n你最近做的事：\n{action_detailed_str}\n"
|
||||
else:
|
||||
cycle_info_block = "\n"
|
||||
|
||||
# 根据连续文本回复的数量构建提示信息
|
||||
if consecutive_text_replies >= 3: # 如果最近的三个活动都是文本回复
|
||||
cycle_info_block = f'你已经连续回复了三条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"，第三近: "{responses_for_prompt[2]}"）。你回复的有点多了，请注意'
|
||||
elif consecutive_text_replies == 2: # 如果最近的两个活动是文本回复
|
||||
cycle_info_block = f'你已经连续回复了两条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"），请注意'
|
||||
|
||||
# 包装提示块，增加可读性，即使没有连续回复也给个标记
|
||||
# if cycle_info_block:
|
||||
# cycle_info_block = f"\n你最近的回复\n{cycle_info_block}\n"
|
||||
# else:
|
||||
# cycle_info_block = "\n"
|
||||
|
||||
# 获取history_loop中最新添加的
|
||||
if self.history_loop:
|
||||
last_loop = self.history_loop[0]
|
||||
start_time = last_loop.start_time
|
||||
end_time = last_loop.end_time
|
||||
if start_time is not None and end_time is not None:
|
||||
time_diff = int(end_time - start_time)
|
||||
if time_diff > 60:
|
||||
cycle_info_block += f"距离你上一次阅读消息并思考和规划，已经过去了{int(time_diff / 60)}分钟\n"
|
||||
else:
|
||||
cycle_info_block += f"距离你上一次阅读消息并思考和规划，已经过去了{time_diff}秒\n"
|
||||
else:
|
||||
cycle_info_block += "你还没看过消息\n"
|
||||
|
||||
self.observe_info = cycle_info_block
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将观察对象转换为可序列化的字典"""
|
||||
# 只序列化基本信息，避免循环引用
|
||||
return {
|
||||
"observe_info": self.observe_info,
|
||||
"observe_id": self.observe_id,
|
||||
"last_observe_time": self.last_observe_time,
|
||||
# 不序列化history_loop，避免循环引用
|
||||
"history_loop_count": len(self.history_loop),
|
||||
}
|
||||
25
src/chat/focus_chat/observation/observation.py
Normal file
25
src/chat/focus_chat/observation/observation.py
Normal file
@@ -0,0 +1,25 @@
|
||||
# 定义了来自外部世界的信息
|
||||
# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
|
||||
from datetime import datetime
|
||||
from src.common.logger import get_logger
|
||||
|
||||
logger = get_logger("observation")
|
||||
|
||||
|
||||
# 所有观察的基类
|
||||
class Observation:
|
||||
def __init__(self, observe_id):
|
||||
self.observe_info = ""
|
||||
self.observe_id = observe_id
|
||||
self.last_observe_time = datetime.now().timestamp() # 初始化为当前时间
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将观察对象转换为可序列化的字典"""
|
||||
return {
|
||||
"observe_info": self.observe_info,
|
||||
"observe_id": self.observe_id,
|
||||
"last_observe_time": self.last_observe_time,
|
||||
}
|
||||
|
||||
async def observe(self):
|
||||
pass
|
||||
34
src/chat/focus_chat/observation/working_observation.py
Normal file
34
src/chat/focus_chat/observation/working_observation.py
Normal file
@@ -0,0 +1,34 @@
|
||||
# 定义了来自外部世界的信息
|
||||
# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
|
||||
from datetime import datetime
|
||||
from src.common.logger import get_logger
|
||||
from src.chat.focus_chat.working_memory.working_memory import WorkingMemory
|
||||
from src.chat.focus_chat.working_memory.memory_item import MemoryItem
|
||||
from typing import List
|
||||
# Import the new utility function
|
||||
|
||||
logger = get_logger("observation")
|
||||
|
||||
|
||||
# 所有观察的基类
|
||||
class WorkingMemoryObservation:
|
||||
def __init__(self, observe_id):
|
||||
self.observe_info = ""
|
||||
self.observe_id = observe_id
|
||||
self.last_observe_time = datetime.now().timestamp()
|
||||
|
||||
self.working_memory = WorkingMemory(chat_id=observe_id)
|
||||
|
||||
self.retrieved_working_memory = []
|
||||
|
||||
def get_observe_info(self):
|
||||
return self.working_memory
|
||||
|
||||
def add_retrieved_working_memory(self, retrieved_working_memory: List[MemoryItem]):
|
||||
self.retrieved_working_memory.append(retrieved_working_memory)
|
||||
|
||||
def get_retrieved_working_memory(self):
|
||||
return self.retrieved_working_memory
|
||||
|
||||
async def observe(self):
|
||||
pass
|
||||
Reference in New Issue
Block a user