mirror of https://github.com/Mai-with-u/MaiBot.git
删除多余注释 微调关系prompy
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e97b55b048
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@ -11,11 +11,8 @@ class ConversationInfo:
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self.last_reply_rejection_reason: Optional[str] = None # 用于存储上次回复被拒原因
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self.last_rejected_reply_content: Optional[str] = None # 用于存储上次被拒的回复内容
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self.my_message_count: int = 0 # 用于存储连续发送了多少条消息
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# --- 新增字段 ---
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self.person_id: Optional[str] = None # 私聊对象的唯一ID
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self.relationship_text: Optional[str] = "你们还不熟悉。" # 与当前对话者的关系描述文本
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self.current_emotion_text: Optional[str] = "心情平静。" # 机器人当前的情绪描述文本
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self.current_instance_message_count: int = 0 # 当前私聊实例中的消息计数
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self.other_new_messages_during_planning_count: int = 0 # 在计划阶段期间收到的其他新消息计数
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# --- 新增字段结束 ---
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@ -276,7 +276,7 @@ class PfcRepationshipTranslator:
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description = "普通" # 默认或错误情况
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logger.warning(f"[私聊][{self.private_name}] 计算出的 level_num ({level_num}) 无效，关系描述默认为 '普通'")
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return f"你们的关系是：{description}。"
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return f"{description}。"
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@staticmethod
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def _calculate_relationship_level_num(relationship_value: float, private_name: str) -> int:
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@ -3,30 +3,25 @@ import json
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import re
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import time
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from datetime import datetime
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from typing import Dict, Any, Optional, Tuple, List, Union # 确保导入这些类型
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from typing import Dict, Any, Optional, Tuple, List, Union
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from src.common.logger_manager import get_logger
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from src.config.config import global_config
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from src.common.database import db # << 确认此路径
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# --- 依赖于你项目结构的导入，请务必仔细检查并根据你的实际情况调整 ---
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from src.plugins.memory_system.Hippocampus import HippocampusManager # << 确认此路径
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from src.plugins.heartFC_chat.heartflow_prompt_builder import prompt_builder # << 确认此路径
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from src.plugins.chat.utils import get_embedding # << 确认此路径
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from src.plugins.utils.chat_message_builder import build_readable_messages # << 确认此路径
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# --- 依赖导入结束 ---
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from src.plugins.chat.chat_stream import ChatStream # 来自原始 pfc_utils.py
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from ..person_info.person_info import person_info_manager # 来自原始 pfc_utils.py (相对导入)
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import math # 来自原始 pfc_utils.py
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from .observation_info import ObservationInfo # 来自原始 pfc_utils.py (相对导入)
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from src.common.database import db
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from src.plugins.memory_system.Hippocampus import HippocampusManager
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from src.plugins.heartFC_chat.heartflow_prompt_builder import prompt_builder
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from src.plugins.chat.utils import get_embedding
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from src.plugins.utils.chat_message_builder import build_readable_messages
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from src.plugins.chat.chat_stream import ChatStream
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from ..person_info.person_info import person_info_manager
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import math
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from .observation_info import ObservationInfo
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logger = get_logger("pfc_utils")
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# ==============================================================================
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# 新增：专门用于检索 PFC 私聊历史对话上下文的函数
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# 专门用于检索 PFC 私聊历史对话上下文的函数
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# ==============================================================================
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async def find_most_relevant_historical_message(
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chat_id: str,
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@ -325,7 +320,6 @@ async def retrieve_contextual_info(
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logger.debug(f"[私聊][{private_name}] (retrieve_contextual_info) 无有效主查询文本，跳过全局压缩记忆检索。")
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# --- 2. 相关知识检索 (来自 prompt_builder) ---
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# (保持你原始 pfc_utils.py 中这部分的逻辑基本不变)
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knowledge_log_msg = f"开始知识检索 (基于文本: '{text[:30]}...')"
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if text and text.strip() and text != "还没有聊天记录。" and text != "[构建聊天记录出错]":
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try:
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@ -355,7 +349,7 @@ async def retrieve_contextual_info(
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if query_for_historical_chat:
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try:
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# ---- [新代码] 计算最终的、严格的搜索时间上限 ----
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# ---- 计算最终的、严格的搜索时间上限 ----
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# 1. 设置一个基础的、较大的时间回溯窗口，例如2小时 (7200秒)
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# 这个值可以从全局配置读取，如果没配置则使用默认值
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default_search_exclude_seconds = getattr(
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@ -387,7 +381,7 @@ async def retrieve_contextual_info(
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query_text=query_for_historical_chat,
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similarity_threshold=0.5, # 您可以调整这个
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# exclude_recent_seconds 不再直接使用，而是传递计算好的绝对时间上限
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absolute_search_time_limit=final_search_upper_limit_time, # <--- 传递计算好的绝对时间上限
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absolute_search_time_limit=final_search_upper_limit_time,
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)
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if most_relevant_message_doc:
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@ -457,9 +451,7 @@ async def retrieve_contextual_info(
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return retrieved_global_memory_str, retrieved_knowledge_str, retrieved_historical_chat_str
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# ==============================================================================
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# 你原始 pfc_utils.py 中的其他函数保持不变
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# ==============================================================================
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def get_items_from_json(
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content: str,
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private_name: str,
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@ -496,13 +488,13 @@ def get_items_from_json(
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json_array = json.loads(cleaned_content)
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if isinstance(json_array, list):
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valid_items_list: List[Dict[str, Any]] = []
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for item_json in json_array: # Renamed item to item_json to avoid conflict
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for item_json in json_array:
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if not isinstance(item_json, dict):
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logger.warning(f"[私聊][{private_name}] JSON数组中的元素不是字典: {item_json}")
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continue
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current_item_result = default_result.copy()
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valid_item = True
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for field in items: # items is args from function signature
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for field in items:
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if field in item_json:
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current_item_result[field] = item_json[field]
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elif field not in default_result:
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@ -610,16 +602,13 @@ async def get_person_id(private_name: str, chat_stream: ChatStream):
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"""(保持你原始 pfc_utils.py 中的此函数代码不变)"""
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private_user_id_str: Optional[str] = None
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private_platform_str: Optional[str] = None
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# private_nickname_str = private_name # 这行在你提供的代码中没有被使用，可以考虑移除
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if chat_stream.user_info:
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private_user_id_str = str(chat_stream.user_info.user_id)
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private_platform_str = chat_stream.user_info.platform
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logger.debug(
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f"[私聊][{private_name}] 从 ChatStream 获取到私聊对象信息: ID={private_user_id_str}, Platform={private_platform_str}, Name={private_name}" # 使用 private_name
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f"[私聊][{private_name}] 从 ChatStream 获取到私聊对象信息: ID={private_user_id_str}, Platform={private_platform_str}, Name={private_name}"
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)
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# elif chat_stream.group_info is None and private_name: # 这个 elif 条件体为空，可以移除
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# pass
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if private_user_id_str and private_platform_str:
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try:
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@ -693,7 +682,7 @@ async def build_chat_history_text(observation_info: ObservationInfo, private_nam
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unread_messages = getattr(observation_info, "unprocessed_messages", [])
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if unread_count > 0 and unread_messages:
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bot_qq_str = str(global_config.BOT_QQ) if global_config.BOT_QQ else None # 安全获取
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if bot_qq_str: # 仅当 bot_qq_str 有效时进行过滤
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if bot_qq_str:
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other_unread_messages = [
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msg for msg in unread_messages if msg.get("user_info", {}).get("user_id") != bot_qq_str
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]
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@ -701,12 +690,12 @@ async def build_chat_history_text(observation_info: ObservationInfo, private_nam
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if other_unread_count > 0:
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new_messages_str = await build_readable_messages(
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other_unread_messages,
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replace_bot_name=True, # 这里是未处理消息，可能不需要替换机器人名字
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replace_bot_name=True,
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merge_messages=False,
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timestamp_mode="relative",
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read_mark=0.0,
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)
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chat_history_text += f"\n{new_messages_str}\n------\n" # 原始代码是加在末尾的
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chat_history_text += f"\n{new_messages_str}\n------\n"
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else:
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logger.warning(f"[私聊][{private_name}] BOT_QQ 未配置，无法准确过滤未读消息中的机器人自身消息。")
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