refactor(memory): 简化记忆系统架构，移除 MemoryManager

将 `get_message_collection_context` 方法从 `MemoryManager` 移动到 `MessageCollectionStorage`，并直接在 `MemorySystem` 中调用它。这一变更简化了依赖关系，并消除了 `MemoryManager` 类，使其职责更加清晰。主要变更： - 从 `MemoryManager` 中移除 `get_message_collection_context` 并将其功能迁移。 - 更新 `MemorySystem` 以直接使用 `MessageCollectionStorage` 来检索上下文。 - 移除 `MemoryManager` 的初始化和依赖，因为它不再需要。 - 将 `MemorySystem` 的初始化改为单例模式，以确保全局唯一实例。
2025-10-25 20:20:07 +08:00
parent 5a99442064
commit bb9c31e63a
3 changed files with 46 additions and 74 deletions
--- a/src/chat/memory_system/memory_manager.py
+++ b/src/chat/memory_system/memory_manager.py
@@ -7,8 +7,8 @@ import re
 from dataclasses import dataclass
 from typing import Any

-from src.chat.memory_system.memory_chunk import MemoryChunk, MemoryType, MessageCollection
-from src.chat.memory_system.memory_system import MemorySystem, initialize_memory_system
+from src.chat.memory_system.memory_chunk import MemoryChunk, MemoryType
+from src.chat.memory_system.memory_system import MemorySystem
 from src.chat.memory_system.message_collection_processor import MessageCollectionProcessor
 from src.chat.memory_system.message_collection_storage import MessageCollectionStorage
 from src.common.logger import get_logger
@@ -64,14 +64,9 @@ class MemoryManager:

            logger.info("正在初始化记忆系统...")

-            # 获取LLM模型
-            from src.config.config import model_config
-            from src.llm_models.utils_model import LLMRequest
-
-            llm_model = LLMRequest(model_set=model_config.model_task_config.utils, request_type="memory")
-
            # 初始化记忆系统
-            self.memory_system = await initialize_memory_system(llm_model)
+            from src.chat.memory_system.memory_system import get_memory_system
+            self.memory_system = get_memory_system()

            # 初始化消息集合系统
            self.message_collection_storage = MessageCollectionStorage()
@@ -500,60 +495,6 @@ class MemoryManager:
            return text
        return text[: max_length - 1] + "…"

-    async def get_relevant_message_collection(self, query_text: str, n_results: int = 3) -> list[MessageCollection]:
-        """获取相关的消息集合列表"""
-        if not self.is_initialized or not self.message_collection_storage:
-            return []
-
-        try:
-            return await self.message_collection_storage.get_relevant_collection(query_text, n_results=n_results)
-        except Exception as e:
-            logger.error(f"get_relevant_message_collection 失败: {e}")
-            return []
-
-    async def get_message_collection_context(self, query_text: str, chat_id: str) -> str:
-        """获取消息集合上下文，用于添加到 prompt 中。优先展示当前聊天的上下文。"""
-        if not self.is_initialized or not self.message_collection_storage:
-            return ""
-
-        try:
-            collections = await self.get_relevant_message_collection(query_text, n_results=3)
-            if not collections:
-                return ""
-
-            # 根据传入的 chat_id 对集合进行排序
-            collections.sort(key=lambda c: c.chat_id == chat_id, reverse=True)
-
-            context_parts = []
-            for collection in collections:
-                if not collection.combined_text:
-                    continue
-
-                header = "## 📝 相关对话上下文\n"
-                if collection.chat_id == chat_id:
-                    # 匹配的ID，使用更明显的标识
-                    context_parts.append(
-                        f"{header} [🔥 来自当前聊天的上下文]\n```\n{collection.combined_text}\n```"
-                    )
-                else:
-                    # 不匹配的ID
-                    context_parts.append(
-                        f"{header} [💡 来自其他聊天的相关上下文 (ID: {collection.chat_id})]\n```\n{collection.combined_text}\n```"
-                    )
-
-            if not context_parts:
-                return ""
-
-            # 格式化消息集合为 prompt 上下文
-            final_context = "\n\n---\n\n".join(context_parts) + "\n\n---"
-            
-            logger.info(f"🔗 为查询 '{query_text[:50]}...' 在聊天 '{chat_id}' 中找到 {len(collections)} 个相关消息集合上下文")
-            return f"\n{final_context}\n"
-
-        except Exception as e:
-            logger.error(f"get_message_collection_context 失败: {e}")
-            return ""
-
    async def shutdown(self):
        """关闭增强记忆系统"""
        if not self.is_initialized:
--- a/src/chat/memory_system/memory_system.py
+++ b/src/chat/memory_system/memory_system.py
@@ -18,7 +18,6 @@ import orjson
 from src.chat.memory_system.memory_builder import MemoryBuilder, MemoryExtractionError
 from src.chat.memory_system.memory_chunk import MemoryChunk
 from src.chat.memory_system.memory_fusion import MemoryFusionEngine
-from src.chat.memory_system.memory_manager import MemoryManager
 from src.chat.memory_system.memory_query_planner import MemoryQueryPlanner
 from src.chat.memory_system.message_collection_storage import MessageCollectionStorage

@@ -147,7 +146,6 @@ class MemorySystem:
        self.message_collection_storage: MessageCollectionStorage | None = None
        self.query_planner: MemoryQueryPlanner | None = None
        self.forgetting_engine: MemoryForgettingEngine | None = None
-        self.memory_manager: MemoryManager | None = None

        # LLM模型
        self.value_assessment_model: LLMRequest | None = None
@@ -173,10 +171,6 @@ class MemorySystem:
    async def initialize(self):
        """异步初始化记忆系统"""
        try:
-            # 初始化 MemoryManager
-            self.memory_manager = MemoryManager()
-            await self.memory_manager.initialize()
-
            # 初始化LLM模型
            fallback_task = getattr(self.llm_model, "model_for_task", None) if self.llm_model else None

@@ -942,13 +936,10 @@ class MemorySystem:

    async def _retrieve_instant_memories(self, query_text: str, chat_id: str | None) -> list[MemoryChunk]:
        """检索瞬时记忆（消息集合）并转换为MemoryChunk"""
-        if not self.memory_manager:
+        if not self.message_collection_storage or not chat_id:
            return []

-        if not chat_id:
-            return []
-
-        context_text = await self.memory_manager.get_message_collection_context(query_text, chat_id=chat_id)
+        context_text = await self.message_collection_storage.get_message_collection_context(query_text, chat_id=chat_id)
        if not context_text:
            return []

--- a/src/chat/memory_system/message_collection_storage.py
+++ b/src/chat/memory_system/message_collection_storage.py
@@ -131,6 +131,46 @@ class MessageCollectionStorage:
            logger.error(f"检索相关消息集合失败: {e}", exc_info=True)
            return []

+    async def get_message_collection_context(self, query_text: str, chat_id: str) -> str:
+        """获取消息集合上下文，用于添加到 prompt 中。优先展示当前聊天的上下文。"""
+        try:
+            collections = await self.get_relevant_collection(query_text, n_results=5)
+            if not collections:
+                return ""
+
+            # 根据传入的 chat_id 对集合进行排序
+            collections.sort(key=lambda c: c.chat_id == chat_id, reverse=True)
+
+            context_parts = []
+            for collection in collections:
+                if not collection.combined_text:
+                    continue
+
+                header = "## 📝 相关对话上下文\n"
+                if collection.chat_id == chat_id:
+                    # 匹配的ID，使用更明显的标识
+                    context_parts.append(
+                        f"{header} [🔥 来自当前聊天的上下文]\n```\n{collection.combined_text}\n```"
+                    )
+                else:
+                    # 不匹配的ID
+                    context_parts.append(
+                        f"{header} [💡 来自其他聊天的相关上下文 (ID: {collection.chat_id})]\n```\n{collection.combined_text}\n```"
+                    )
+
+            if not context_parts:
+                return ""
+
+            # 格式化消息集合为 prompt 上下文
+            final_context = "\n\n---\n\n".join(context_parts) + "\n\n---"
+            
+            logger.info(f"🔗 为查询 '{query_text[:50]}...' 在聊天 '{chat_id}' 中找到 {len(collections)} 个相关消息集合上下文")
+            return f"\n{final_context}\n"
+
+        except Exception as e:
+            logger.error(f"get_message_collection_context 失败: {e}")
+            return ""
+
    def clear_all(self):
        """清空所有消息集合"""
        try: