短期记忆补丁

src/chat/message_manager/distribution_manager.py

@@ -121,7 +121,7 @@ async def conversation_loop(
         except asyncio.CancelledError:
             logger.info(f" [生成器] stream={stream_id[:8]}, 被取消")
             break
-        except Exception as e:  # noqa: BLE001
+        except Exception as e:
             logger.error(f" [生成器] stream={stream_id[:8]}, 出错: {e}")
             await asyncio.sleep(5.0)
 
@@ -151,10 +151,10 @@ async def run_chat_stream(
         # 创建生成器
         tick_generator = conversation_loop(
             stream_id=stream_id,
-            get_context_func=manager._get_stream_context,  # noqa: SLF001
+            get_context_func=manager._get_stream_context,
-            calculate_interval_func=manager._calculate_interval,  # noqa: SLF001
+            calculate_interval_func=manager._calculate_interval,
-            flush_cache_func=manager._flush_cached_messages_to_unread,  # noqa: SLF001
+            flush_cache_func=manager._flush_cached_messages_to_unread,
-            check_force_dispatch_func=manager._needs_force_dispatch_for_context,  # noqa: SLF001
+            check_force_dispatch_func=manager._needs_force_dispatch_for_context,
             is_running_func=lambda: manager.is_running,
         )
 
@@ -162,13 +162,13 @@ async def run_chat_stream(
         async for tick in tick_generator:
             try:
                 # 获取上下文
-                context = await manager._get_stream_context(stream_id)  # noqa: SLF001
+                context = await manager._get_stream_context(stream_id)
                 if not context:
                     continue
 
                 # 并发保护：检查是否正在处理
                 if context.is_chatter_processing:
-                    if manager._recover_stale_chatter_state(stream_id, context):  # noqa: SLF001
+                    if manager._recover_stale_chatter_state(stream_id, context):
                         logger.warning(f" [驱动器] stream={stream_id[:8]}, 处理标志残留已修复")
                     else:
                         logger.debug(f" [驱动器] stream={stream_id[:8]}, Chatter正在处理，跳过此Tick")
@@ -182,7 +182,7 @@ async def run_chat_stream(
 
                 # 更新能量值
                 try:
-                    await manager._update_stream_energy(stream_id, context)  # noqa: SLF001
+                    await manager._update_stream_energy(stream_id, context)
                 except Exception as e:
                     logger.debug(f"更新能量失败: {e}")
 
@@ -191,7 +191,7 @@ async def run_chat_stream(
                 try:
                     async with manager._processing_semaphore:
                         success = await asyncio.wait_for(
-                            manager._process_stream_messages(stream_id, context),  # noqa: SLF001
+                            manager._process_stream_messages(stream_id, context),
                             global_config.chat.thinking_timeout,
                         )
                 except asyncio.TimeoutError:
@@ -209,7 +209,7 @@ async def run_chat_stream(
 
             except asyncio.CancelledError:
                 raise
-            except Exception as e:  # noqa: BLE001
+            except Exception as e:
                 logger.error(f" [驱动器] stream={stream_id[:8]}, 处理Tick时出错: {e}")
                 manager.stats["total_failures"] += 1
 
@@ -222,7 +222,7 @@ async def run_chat_stream(
             if context and context.stream_loop_task:
                 context.stream_loop_task = None
                 logger.debug(f" [驱动器] stream={stream_id[:8]}, 清理任务记录")
-        except Exception as e:  # noqa: BLE001
+        except Exception as e:
             logger.debug(f"清理任务记录失败: {e}")
 
 

src/chat/message_manager/message_manager.py

@@ -110,10 +110,10 @@ class MessageManager:
             if not (context.stream_loop_task and not context.stream_loop_task.done()):
                 # 异步启动驱动器任务；避免在高并发下阻塞消息入队
                 await stream_loop_manager.start_stream_loop(stream_id)
-                
+
             # 检查并处理消息打断
             await self._check_and_handle_interruption(chat_stream, message)
-            
+
             # 入队消息
             await chat_stream.context.add_message(message)
 

src/config/config.py

@@ -1,8 +1,8 @@
 import os
 import shutil
 import sys
-import typing
 import types
+import typing
 from datetime import datetime
 from pathlib import Path
 from typing import Any, get_args, get_origin
@@ -30,8 +30,8 @@ from src.config.official_configs import (
     ExperimentalConfig,
     ExpressionConfig,
     InnerConfig,
-    LogConfig,
     KokoroFlowChatterConfig,
+    LogConfig,
     LPMMKnowledgeConfig,
     MemoryConfig,
     MessageBusConfig,
@@ -515,7 +515,7 @@ class Config(ValidatedConfigBase):
     )
 
     @property
-    def MMC_VERSION(self) -> str:  # noqa: N802
+    def MMC_VERSION(self) -> str:
         return MMC_VERSION
 
 

src/memory_graph/long_term_manager.py

@@ -66,6 +66,13 @@ class LongTermMemoryManager:
         self._similar_memory_cache: dict[str, list[Memory]] = {}
         self._cache_max_size = 100
 
+        # 错误/重试统计与配置
+        self._max_process_retries = 2
+        self._retry_backoff = 0.5
+        self._total_processed = 0
+        self._failed_single_memory_count = 0
+        self._retry_attempts = 0
+
         logger.info(
             f"长期记忆管理器已创建 (batch_size={batch_size}, "
             f"search_top_k={search_top_k}, decay_factor={long_term_decay_factor:.2f})"
@@ -202,6 +209,10 @@ class LongTermMemoryManager:
             else:
                 result["failed_count"] += 1
 
+        # 更新全局计数
+        self._total_processed += result["processed_count"]
+        self._failed_single_memory_count += result["failed_count"]
+
         # 处理完批次后，批量生成embeddings
         await self._flush_pending_embeddings()
 
@@ -217,26 +228,45 @@ class LongTermMemoryManager:
         Returns:
             处理结果或None（如果失败）
         """
-        try:
+        # 增加重试机制以应对 LLM/执行的临时失败
-            # 步骤1: 在长期记忆中检索相似记忆
+        attempt = 0
-            similar_memories = await self._search_similar_long_term_memories(stm)
+        last_exc: Exception | None = None
+        while attempt <= self._max_process_retries:
+            try:
+                # 步骤1: 在长期记忆中检索相似记忆
+                similar_memories = await self._search_similar_long_term_memories(stm)
 
-            # 步骤2: LLM 决策如何更新图结构
+                # 步骤2: LLM 决策如何更新图结构
-            operations = await self._decide_graph_operations(stm, similar_memories)
+                operations = await self._decide_graph_operations(stm, similar_memories)
 
-            # 步骤3: 执行图操作
+                # 步骤3: 执行图操作
-            success = await self._execute_graph_operations(operations, stm)
+                success = await self._execute_graph_operations(operations, stm)
 
-            if success:
+                if success:
-                return {
+                    return {
-                    "success": True,
+                        "success": True,
-                    "operations": [op.operation_type for op in operations]
+                        "operations": [op.operation_type for op in operations]
-                }
+                    }
-            return None
 
-        except Exception as e:
+                # 如果执行返回 False，视为一次失败，准备重试
-            logger.error(f"处理短期记忆 {stm.id} 失败: {e}")
+                last_exc = RuntimeError("_execute_graph_operations 返回 False")
-            return None
+                raise last_exc
+
+            except Exception as e:
+                last_exc = e
+                attempt += 1
+                if attempt <= self._max_process_retries:
+                    self._retry_attempts += 1
+                    backoff = self._retry_backoff * attempt
+                    logger.warning(
+                        f"处理短期记忆 {stm.id} 时发生可恢复错误，重试 {attempt}/{self._max_process_retries}，等待 {backoff}s: {e}"
+                    )
+                    await asyncio.sleep(backoff)
+                    continue
+                # 超过重试次数，记录失败并返回 None
+                logger.error(f"处理短期记忆 {stm.id} 最终失败: {last_exc}")
+                self._failed_single_memory_count += 1
+                return None
 
     async def _search_similar_long_term_memories(
         self, stm: ShortTermMemory

src/memory_graph/short_term_manager.py

@@ -648,15 +648,15 @@ class ShortTermMemoryManager:
             else:
                 low_importance_memories.append(mem)
 
-        # 如果低重要性记忆数量超过了上限（说明积压严重）
+        # 如果总体记忆数量超过了上限，优先清理低重要性最早创建的记忆
-        # 我们需要清理掉一部分，而不是转移它们
+        if len(self.memories) > self.max_memories:
-        if len(low_importance_memories) > self.max_memories:
             # 目标保留数量（降至上限的 90%）
             target_keep_count = int(self.max_memories * 0.9)
-            num_to_remove = len(low_importance_memories) - target_keep_count
+            # 需要删除的数量（从当前总数降到 target_keep_count）
+            num_to_remove = len(self.memories) - target_keep_count
 
-            if num_to_remove > 0:
+            if num_to_remove > 0 and low_importance_memories:
-                # 按创建时间排序，删除最早的
+                # 按创建时间排序，删除最早的低重要性记忆
                 low_importance_memories.sort(key=lambda x: x.created_at)
                 to_remove = low_importance_memories[:num_to_remove]
 
@@ -664,7 +664,7 @@ class ShortTermMemoryManager:
                 remove_ids = {mem.id for mem in to_remove}
                 self.memories = [mem for mem in self.memories if mem.id not in remove_ids]
                 for mem_id in remove_ids:
-                    del self._memory_id_index[mem_id]
+                    self._memory_id_index.pop(mem_id, None)
                     self._similarity_cache.pop(mem_id, None)
 
                 logger.info(
@@ -675,6 +675,16 @@ class ShortTermMemoryManager:
                 # 触发保存
                 asyncio.create_task(self._save_to_disk())
 
+        # 优先返回高重要性候选
+        if candidates:
+            return candidates
+
+        # 如果没有高重要性候选但总体超过上限，返回按创建时间最早的低重要性记忆作为后备转移候选
+        if len(self.memories) > self.max_memories:
+            needed = len(self.memories) - self.max_memories + 1
+            low_importance_memories.sort(key=lambda x: x.created_at)
+            return low_importance_memories[:needed]
+
         return candidates
 
     async def clear_transferred_memories(self, memory_ids: list[str]) -> None: