mirror of https://github.com/Mai-with-u/MaiBot.git
fix
114514
parent
fe4990c731
commit
c9e6cf2140
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@ -32,7 +32,7 @@ async def find_most_relevant_historical_message(
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chat_id: str,
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query_text: str,
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similarity_threshold: float = 0.3, # 相似度阈值，可以根据效果调整
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exclude_recent_seconds: int = 900 # 新增参数：排除最近多少秒内的消息（例如5分钟）
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absolute_search_time_limit: Optional[float] = None # 新增参数：排除最近多少秒内的消息（例如5分钟）
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) -> Optional[Dict[str, Any]]:
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"""
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根据查询文本，在指定 chat_id 的历史消息中查找最相关的消息。
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@ -50,15 +50,30 @@ async def find_most_relevant_historical_message(
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logger.warning(f"[{chat_id}] (私聊历史)未能为查询文本 '{query_text[:50]}...' 生成嵌入向量。")
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return None
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current_timestamp = time.time() # 获取当前时间戳
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excluded_time_threshold = current_timestamp - exclude_recent_seconds
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effective_search_upper_limit: float
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log_source_of_limit: str = ""
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if absolute_search_time_limit is not None:
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effective_search_upper_limit = absolute_search_time_limit
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log_source_of_limit = "传入的绝对时间上限"
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else:
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# 如果没有传入绝对时间上限，可以设置一个默认的回退逻辑
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fallback_exclude_seconds = getattr(global_config, "pfc_historical_fallback_exclude_seconds", 7200) # 默认2小时
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effective_search_upper_limit = time.time() - fallback_exclude_seconds
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log_source_of_limit = f"回退逻辑 (排除最近 {fallback_exclude_seconds} 秒)"
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logger.debug(f"[{chat_id}] (私聊历史) find_most_relevant_historical_message: "
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f"将使用时间上限 {effective_search_upper_limit} "
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f"(可读: {datetime.fromtimestamp(effective_search_upper_limit).strftime('%Y-%m-%d %H:%M:%S')}) "
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f"进行历史消息锚点搜索。来源: {log_source_of_limit}")
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# --- [新代码结束] ---
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pipeline = [
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{
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"$match": {
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"chat_id": chat_id,
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"embedding_vector": {"$exists": True, "$ne": None, "$not": {"$size": 0}},
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"time": {"$lt": excluded_time_threshold}
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"time": {"$lt": effective_search_upper_limit} # <--- 使用新的 effective_search_upper_limit
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}
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},
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{
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@ -90,13 +105,13 @@ async def find_most_relevant_historical_message(
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cursor = db.messages.aggregate(pipeline) # PyMongo 的 aggregate 返回一个 CommandCursor
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results = list(cursor) # 直接将 CommandCursor 转换为列表
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if not results:
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logger.info(f"[{chat_id}] (私聊历史) find_most_relevant_historical_message: 在时间点 {excluded_time_threshold} ({exclude_recent_seconds} 秒前) 之前，未能找到任何与 '{query_text[:30]}...' 相关的历史消息。")
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logger.info(f"[{chat_id}] (私聊历史) find_most_relevant_historical_message: 在时间点 {effective_search_upper_limit} 之前，未能找到任何与 '{query_text[:30]}...' 相关的历史消息。")
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else:
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logger.info(f"[{chat_id}] (私聊历史) find_most_relevant_historical_message: 在时间点 {excluded_time_threshold} ({exclude_recent_seconds} 秒前) 之前，找到了 {len(results)} 条候选历史消息。最相关的一条是：")
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for res_msg in results: # 最多只打印我们 limit 的那几条
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logger.info(f"[{chat_id}] (私聊历史) find_most_relevant_historical_message: 在时间点 {effective_search_upper_limit} 之前，找到了 {len(results)} 条候选历史消息。最相关的一条是：")
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for res_msg in results:
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msg_time_readable = datetime.fromtimestamp(res_msg.get('time',0)).strftime('%Y-%m-%d %H:%M:%S')
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logger.info(f" - MsgID: {res_msg.get('message_id')}, Time: {msg_time_readable} (原始: {res_msg.get('time')}), Sim: {res_msg.get('similarity'):.4f}, Text: '{res_msg.get('processed_plain_text','')[:50]}...'")
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# --- 新增日志结束 ---
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# --- [修改结束] ---
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# --- 修改结束 ---
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if results and len(results) > 0:
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@ -182,7 +197,8 @@ async def retrieve_contextual_info(
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text: str, # 用于全局记忆和知识检索的主查询文本 (通常是短期聊天记录)
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private_name: str, # 用于日志
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chat_id: str, # 用于特定私聊历史的检索
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historical_chat_query_text: Optional[str] = None # 专门为私聊历史检索准备的查询文本 (例如最新的N条消息合并)
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historical_chat_query_text: Optional[str] = None,
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current_short_term_history_earliest_time: Optional[float] = None # <--- 新增参数
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) -> Tuple[str, str, str]: # 返回: 全局记忆, 知识, 私聊历史回忆
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"""
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检索三种类型的上下文信息：全局压缩记忆、知识库知识、当前私聊的特定历史对话。
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@ -253,38 +269,68 @@ 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，跳过知识检索。")
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# --- 3. 当前私聊的特定历史对话上下文检索 (新增逻辑) ---
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# --- 3. 当前私聊的特定历史对话上下文检索 ---
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query_for_historical_chat = historical_chat_query_text if historical_chat_query_text and historical_chat_query_text.strip() else None
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historical_chat_log_msg = f"开始私聊历史检索 (查询文本: '{str(query_for_historical_chat)[:30]}...')"
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# historical_chat_log_msg 的初始化可以移到 try 块之后，根据实际情况赋值
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if query_for_historical_chat:
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try:
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# 获取 find_most_relevant_historical_message 调用时实际使用的 exclude_recent_seconds 值
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actual_exclude_seconds_for_find = 900 # 根据您对 find_most_relevant_historical_message 的调用
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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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# 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(global_config, "pfc_historical_search_default_exclude_seconds", 7200) # 默认2小时
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base_excluded_time_limit = time.time() - default_search_exclude_seconds
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final_search_upper_limit_time = base_excluded_time_limit
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if current_short_term_history_earliest_time is not None:
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# 我们希望找到的消息严格早于 short_term_history 的开始，减去一个小量确保不包含边界
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limit_from_short_term = current_short_term_history_earliest_time - 0.001
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final_search_upper_limit_time = min(base_excluded_time_limit, limit_from_short_term)
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log_earliest_time_str = "未提供"
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if current_short_term_history_earliest_time is not None:
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try:
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log_earliest_time_str = f"{current_short_term_history_earliest_time} (即 {datetime.fromtimestamp(current_short_term_history_earliest_time).strftime('%Y-%m-%d %H:%M:%S')})"
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except:
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log_earliest_time_str = str(current_short_term_history_earliest_time)
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logger.debug(f"[{private_name}] (私聊历史) retrieve_contextual_info: "
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f"最终用于历史搜索的时间上限: {final_search_upper_limit_time} "
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f"(可读: {datetime.fromtimestamp(final_search_upper_limit_time).strftime('%Y-%m-%d %H:%M:%S')}). "
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f"基于默认排除 {default_search_exclude_seconds}s 和 '最近记录'片段开始时间: {log_earliest_time_str}")
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most_relevant_message_doc = await find_most_relevant_historical_message(
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chat_id=chat_id,
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query_text=query_for_historical_chat,
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similarity_threshold=0.5,
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exclude_recent_seconds=actual_exclude_seconds_for_find
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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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)
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if most_relevant_message_doc:
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anchor_id = most_relevant_message_doc.get("message_id")
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anchor_time = most_relevant_message_doc.get("time")
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if anchor_id and anchor_time is not None:
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# 计算传递给 retrieve_chat_context_window 的时间上限
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# 这个上限应该与 find_most_relevant_historical_message 的排除点一致
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time_limit_for_window_after = time.time() - actual_exclude_seconds_for_find
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anchor_time = most_relevant_message_doc.get("time")
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# 校验锚点时间是否真的符合我们的硬性上限 (理论上 find_most_relevant_historical_message 内部已保证)
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if anchor_time is not None and anchor_time >= final_search_upper_limit_time:
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logger.warning(f"[{private_name}] (私聊历史) find_most_relevant_historical_message 返回的锚点时间 {anchor_time} "
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f"并未严格小于最终搜索上限 {final_search_upper_limit_time}。可能导致重叠。跳过构建上下文。")
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historical_chat_log_msg = "检索到的锚点不符合最终时间要求，可能导致重叠。"
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# 直接进入下一个分支 (else)，使得 retrieved_historical_chat_str 保持默认值
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elif anchor_id and anchor_time is not None:
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# 构建上下文窗口时，其“未来”消息的上限也应该是 final_search_upper_limit_time
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# 因为我们不希望历史回忆的上下文窗口延伸到“最近聊天记录”的范围内或更近
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time_limit_for_context_window_after = final_search_upper_limit_time
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logger.debug(f"[{private_name}] (私聊历史) 调用 retrieve_chat_context_window "
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f"with anchor_time: {anchor_time}, "
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f"excluded_time_threshold_for_window: {time_limit_for_window_after}")
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f"excluded_time_threshold_for_window: {time_limit_for_context_window_after}")
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context_window_messages = await retrieve_chat_context_window(
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chat_id=chat_id,
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anchor_message_id=anchor_id,
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anchor_message_time=anchor_time,
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excluded_time_threshold_for_window=time_limit_for_window_after, # <--- 传递这个值
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anchor_message_time=anchor_time,
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excluded_time_threshold_for_window=time_limit_for_context_window_after,
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window_size_before=7,
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window_size_after=7
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)
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@ -1,7 +1,8 @@
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import random
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import asyncio
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from datetime import datetime
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from .pfc_utils import retrieve_contextual_info
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from typing import Optional
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from src.common.logger_manager import get_logger
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from ..models.utils_model import LLMRequest
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from ...config.config import global_config
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@ -224,6 +225,51 @@ class ReplyGenerator:
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else:
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goals_str = "- 目前没有明确对话目标\n"
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chat_history_for_prompt_builder: list = []
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recent_history_start_time_for_exclusion: Optional[float] = None
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# 我们需要知道 build_chat_history_text 函数大致会用 observation_info.chat_history 的多少条记录
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# 或者 build_chat_history_text 内部的逻辑。
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# 假设 build_chat_history_text 主要依赖 observation_info.chat_history_str，
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# 而 observation_info.chat_history_str 是基于 observation_info.chat_history 的最后一部分（比如20条）生成的。
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# 为了准确，我们应该直接从 observation_info.chat_history 中获取这个片段的起始时间。
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# 请确保这里的 MAX_RECENT_HISTORY_FOR_PROMPT 与 observation_info.py 或 build_chat_history_text 中
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# 用于生成 chat_history_str 的消息数量逻辑大致吻合。
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# 如果 build_chat_history_text 总是用 observation_info.chat_history 的最后 N 条，那么这个 N 就是这里的数字。
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# 如果 observation_info.chat_history_str 是由 observation_info.py 中的 update_from_message 等方法维护的，
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# 并且总是代表一个固定长度（比如最后30条）的聊天记录字符串，那么我们就需要从 observation_info.chat_history
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# 取出这部分原始消息来确定起始时间。
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# 我们先做一个合理的假设： “最近聊天记录” 字符串 chat_history_text 是基于
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# observation_info.chat_history 的一个有限的尾部片段生成的。
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# 假设这个片段的长度由 global_config.pfc_recent_history_display_count 控制，默认为20条。
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recent_history_display_count = getattr(global_config, "pfc_recent_history_display_count", 20)
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if observation_info and observation_info.chat_history and len(observation_info.chat_history) > 0:
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# 获取用于生成“最近聊天记录”的实际消息片段
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# 如果 observation_info.chat_history 长度小于 display_count，则取全部
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start_index = max(0, len(observation_info.chat_history) - recent_history_display_count)
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chat_history_for_prompt_builder = observation_info.chat_history[start_index:]
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if chat_history_for_prompt_builder: # 如果片段不为空
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try:
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first_message_in_display_slice = chat_history_for_prompt_builder[0]
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recent_history_start_time_for_exclusion = first_message_in_display_slice.get('time')
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if recent_history_start_time_for_exclusion:
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# 导入 datetime (如果 reply_generator.py 文件顶部没有的话)
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# from datetime import datetime # 通常建议放在文件顶部
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logger.debug(f"[{self.private_name}] (ReplyGenerator) “最近聊天记录”片段(共{len(chat_history_for_prompt_builder)}条)的最早时间戳: "
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f"{recent_history_start_time_for_exclusion} "
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f"(即 {datetime.fromtimestamp(recent_history_start_time_for_exclusion).strftime('%Y-%m-%d %H:%M:%S')})")
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else:
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logger.warning(f"[{self.private_name}] (ReplyGenerator) “最近聊天记录”片段的首条消息无时间戳。")
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except (IndexError, KeyError, TypeError) as e:
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logger.warning(f"[{self.private_name}] (ReplyGenerator) 获取“最近聊天记录”起始时间失败: {e}")
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recent_history_start_time_for_exclusion = None
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else:
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logger.debug(f"[{self.private_name}] (ReplyGenerator) observation_info.chat_history 为空，无法确定“最近聊天记录”起始时间。")
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# --- [新代码结束] ---
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chat_history_text = await build_chat_history_text(observation_info, self.private_name)
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sender_name_str = self.private_name
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@ -276,7 +322,8 @@ class ReplyGenerator:
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text=retrieval_context_for_global_and_knowledge, # 用于全局记忆和知识
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private_name=self.private_name,
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chat_id=current_chat_id, # << 传递 chat_id
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historical_chat_query_text=historical_chat_query # << 传递专门的查询文本
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historical_chat_query_text=historical_chat_query, # << 传递专门的查询文本
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current_short_term_history_earliest_time=recent_history_start_time_for_exclusion # <--- 新增传递的参数
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)
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# === 调用修改结束 ===
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