From bf5c3ccbbad42c5af62fd26cd42ec8f5eec7f068 Mon Sep 17 00:00:00 2001 From: 114514 <2514624910@qq.com> Date: Sat, 10 May 2025 21:21:25 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=A0=E9=99=A4=E5=A4=9A=E4=BD=99=E6=B3=A8?= =?UTF-8?q?=E9=87=8A=20=E5=BE=AE=E8=B0=83=E5=85=B3=E7=B3=BBprompy?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/plugins/PFC/conversation_info.py | 3 -- src/plugins/PFC/pfc_relationship.py | 2 +- src/plugins/PFC/pfc_utils.py | 51 +++++++++++----------------- 3 files changed, 21 insertions(+), 35 deletions(-) diff --git a/src/plugins/PFC/conversation_info.py b/src/plugins/PFC/conversation_info.py index 8bbf5ef5..41de0523 100644 --- a/src/plugins/PFC/conversation_info.py +++ b/src/plugins/PFC/conversation_info.py @@ -11,11 +11,8 @@ class ConversationInfo: self.last_reply_rejection_reason: Optional[str] = None # 用于存储上次回复被拒原因 self.last_rejected_reply_content: Optional[str] = None # 用于存储上次被拒的回复内容 self.my_message_count: int = 0 # 用于存储连续发送了多少条消息 - - # --- 新增字段 --- self.person_id: Optional[str] = None # 私聊对象的唯一ID self.relationship_text: Optional[str] = "你们还不熟悉。" # 与当前对话者的关系描述文本 self.current_emotion_text: Optional[str] = "心情平静。" # 机器人当前的情绪描述文本 self.current_instance_message_count: int = 0 # 当前私聊实例中的消息计数 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 - # --- 新增字段结束 --- diff --git a/src/plugins/PFC/pfc_relationship.py b/src/plugins/PFC/pfc_relationship.py index 3ebc0c1b..89c469c3 100644 --- a/src/plugins/PFC/pfc_relationship.py +++ b/src/plugins/PFC/pfc_relationship.py @@ -276,7 +276,7 @@ class PfcRepationshipTranslator: description = "普通" # 默认或错误情况 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'") - return f"你们的关系是：{description}。" + return f"{description}。" @staticmethod def _calculate_relationship_level_num(relationship_value: float, private_name: str) -> int: diff --git a/src/plugins/PFC/pfc_utils.py b/src/plugins/PFC/pfc_utils.py index f619fcea..56d6d9a8 100644 --- a/src/plugins/PFC/pfc_utils.py +++ b/src/plugins/PFC/pfc_utils.py @@ -3,30 +3,25 @@ import json import re import time from datetime import datetime -from typing import Dict, Any, Optional, Tuple, List, Union # 确保导入这些类型 - +from typing import Dict, Any, Optional, Tuple, List, Union from src.common.logger_manager import get_logger from src.config.config import global_config -from src.common.database import db # << 确认此路径 - -# --- 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 --- -from src.plugins.memory_system.Hippocampus import HippocampusManager # << 确认此路径 -from src.plugins.heartFC_chat.heartflow_prompt_builder import prompt_builder # << 确认此路径 -from src.plugins.chat.utils import get_embedding # << 确认此路径 -from src.plugins.utils.chat_message_builder import build_readable_messages # << 确认此路径 -# --- 依赖导入结束 --- - -from src.plugins.chat.chat_stream import ChatStream # 来自原始 pfc_utils.py -from ..person_info.person_info import person_info_manager # 来自原始 pfc_utils.py (相对导入) -import math # 来自原始 pfc_utils.py -from .observation_info import ObservationInfo # 来自原始 pfc_utils.py (相对导入) +from src.common.database import db +from src.plugins.memory_system.Hippocampus import HippocampusManager +from src.plugins.heartFC_chat.heartflow_prompt_builder import prompt_builder +from src.plugins.chat.utils import get_embedding +from src.plugins.utils.chat_message_builder import build_readable_messages +from src.plugins.chat.chat_stream import ChatStream +from ..person_info.person_info import person_info_manager +import math +from .observation_info import ObservationInfo logger = get_logger("pfc_utils") # ============================================================================== -# 新增：专门用于检索 PFC 私聊历史对话上下文的函数 +# 专门用于检索 PFC 私聊历史对话上下文的函数 # ============================================================================== async def find_most_relevant_historical_message( chat_id: str, @@ -325,7 +320,6 @@ async def retrieve_contextual_info( 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。") # --- 2. 相关知识检索 (来自 prompt_builder) --- - # (保持你原始 pfc_utils.py 中这部分的逻辑基本不变) knowledge_log_msg = f"开始知识检索 (基于文本: '{text[:30]}...')" if text and text.strip() and text != "还没有聊天记录。" and text != "[构建聊天记录出错]": try: @@ -355,7 +349,7 @@ async def retrieve_contextual_info( if query_for_historical_chat: try: - # ---- [新代码] 计算最终的、严格的搜索时间上限 ---- + # ---- 计算最终的、严格的搜索时间上限 ---- # 1. 设置一个基础的、较大的时间回溯窗口，例如2小时 (7200秒) # 这个值可以从全局配置读取，如果没配置则使用默认值 default_search_exclude_seconds = getattr( @@ -387,7 +381,7 @@ async def retrieve_contextual_info( query_text=query_for_historical_chat, similarity_threshold=0.5, # 您可以调整这个 # exclude_recent_seconds 不再直接使用，而是传递计算好的绝对时间上限 - absolute_search_time_limit=final_search_upper_limit_time, # <--- 传递计算好的绝对时间上限 + absolute_search_time_limit=final_search_upper_limit_time, ) if most_relevant_message_doc: @@ -457,9 +451,7 @@ async def retrieve_contextual_info( return retrieved_global_memory_str, retrieved_knowledge_str, retrieved_historical_chat_str -# ============================================================================== -# 你原始 pfc_utils.py 中的其他函数保持不变 -# ============================================================================== + def get_items_from_json( content: str, private_name: str, @@ -496,13 +488,13 @@ def get_items_from_json( json_array = json.loads(cleaned_content) if isinstance(json_array, list): valid_items_list: List[Dict[str, Any]] = [] - for item_json in json_array: # Renamed item to item_json to avoid conflict + for item_json in json_array: if not isinstance(item_json, dict): logger.warning(f"[私聊][{private_name}] JSON数组中的元素不是字典: {item_json}") continue current_item_result = default_result.copy() valid_item = True - for field in items: # items is args from function signature + for field in items: if field in item_json: current_item_result[field] = item_json[field] elif field not in default_result: @@ -610,16 +602,13 @@ async def get_person_id(private_name: str, chat_stream: ChatStream): """(保持你原始 pfc_utils.py 中的此函数代码不变)""" private_user_id_str: Optional[str] = None private_platform_str: Optional[str] = None - # 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 if chat_stream.user_info: private_user_id_str = str(chat_stream.user_info.user_id) private_platform_str = chat_stream.user_info.platform logger.debug( - 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 + 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}" ) - # elif chat_stream.group_info is None and private_name: # 这个 elif 条件体为空，可以移除 - # pass if private_user_id_str and private_platform_str: try: @@ -693,7 +682,7 @@ async def build_chat_history_text(observation_info: ObservationInfo, private_nam unread_messages = getattr(observation_info, "unprocessed_messages", []) if unread_count > 0 and unread_messages: bot_qq_str = str(global_config.BOT_QQ) if global_config.BOT_QQ else None # 安全获取 - if bot_qq_str: # 仅当 bot_qq_str 有效时进行过滤 + if bot_qq_str: other_unread_messages = [ msg for msg in unread_messages if msg.get("user_info", {}).get("user_id") != bot_qq_str ] @@ -701,12 +690,12 @@ async def build_chat_history_text(observation_info: ObservationInfo, private_nam if other_unread_count > 0: new_messages_str = await build_readable_messages( other_unread_messages, - replace_bot_name=True, # 这里是未处理消息，可能不需要替换机器人名字 + replace_bot_name=True, merge_messages=False, timestamp_mode="relative", read_mark=0.0, ) - chat_history_text += f"\n{new_messages_str}\n------\n" # 原始代码是加在末尾的 + chat_history_text += f"\n{new_messages_str}\n------\n" else: 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。")