fix: 构建记忆时重复读取同一段消息，导致token消耗暴增

src/plugins/memory_system/memory.py

@@ -178,33 +178,80 @@ class Hippocampus:
         nodes = sorted([source, target])
         return hash(f"{nodes[0]}:{nodes[1]}")
 
+    def random_get_msg_snippet(self, target_timestamp: float, chat_size: int, max_memorized_time_per_msg: int) -> list:
+        """随机抽取一段时间内的消息片段
+        Args:
+            - target_timestamp: 目标时间戳
+            - chat_size: 抽取的消息数量
+            - max_memorized_time_per_msg: 每条消息的最大记忆次数
+        
+        Returns:
+            - list: 抽取出的消息记录列表
+            
+        """
+        try_count = 0
+        # 最多尝试三次抽取
+        while try_count < 3:
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=target_timestamp)
+            if messages:
+                # 检查messages是否均没有达到记忆次数限制
+                for message in messages:
+                    if message["memorized_times"] >= max_memorized_time_per_msg:
+                        messages = None
+                        break
+                if messages:
+                    # 成功抽取短期消息样本
+                    # 数据写回：增加记忆次数
+                    for message in messages:
+                        db.messages.update_one({"_id": message["_id"]}, {"$set": {"memorized_times": message["memorized_times"] + 1}})                 
+                    return messages
+            try_count += 1
+        # 三次尝试均失败
+        return None
+        
     def get_memory_sample(self, chat_size=20, time_frequency: dict = {'near': 2, 'mid': 4, 'far': 3}):
         """获取记忆样本
         
         Returns:
             list: 消息记录列表，每个元素是一个消息记录字典列表
         """
+        # 硬编码：每条消息最大记忆次数
+        # 如有需求可写入global_config
+        max_memorized_time_per_msg = 3
+        
         current_timestamp = datetime.datetime.now().timestamp()
         chat_samples = []
 
         # 短期：1h   中期：4h   长期：24h
-        for _ in range(time_frequency.get('near')):
+        logger.debug(f"正在抽取短期消息样本")
+        for i in range(time_frequency.get('near')):
             random_time = current_timestamp - random.randint(1, 3600)
-            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
+            messages = self.random_get_msg_snippet(random_time, chat_size, max_memorized_time_per_msg)
             if messages:
+                logger.debug(f"成功抽取短期消息样本{len(messages)}条")
                 chat_samples.append(messages)
+            else:
+                logger.warning(f"第{i}次短期消息样本抽取失败")
 
-        for _ in range(time_frequency.get('mid')):
+        logger.debug(f"正在抽取中期消息样本")
+        for i in range(time_frequency.get('mid')):
             random_time = current_timestamp - random.randint(3600, 3600 * 4)
-            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
+            messages = self.random_get_msg_snippet(random_time, chat_size, max_memorized_time_per_msg)
             if messages:
+                logger.debug(f"成功抽取中期消息样本{len(messages)}条")
                 chat_samples.append(messages)
+            else:
+                logger.warning(f"第{i}次中期消息样本抽取失败")
 
-        for _ in range(time_frequency.get('far')):
+        logger.debug(f"正在抽取长期消息样本")
+        for i in range(time_frequency.get('far')):
             random_time = current_timestamp - random.randint(3600 * 4, 3600 * 24)
-            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
+            messages = self.random_get_msg_snippet(random_time, chat_size, max_memorized_time_per_msg)
             if messages:
+                logger.debug(f"成功抽取长期消息样本{len(messages)}条")
                 chat_samples.append(messages)
+            else:
+                logger.warning(f"第{i}次长期消息样本抽取失败")
 
         return chat_samples