Merge branch 'dev' of https://github.com/MoFox-Studio/MoFox_Bot into dev

src/chat/memory_system/memory_builder.py

@@ -32,7 +32,10 @@ import time
 from dataclasses import dataclass
 from datetime import datetime
 from enum import Enum
-from typing import Any
+from typing import Any, Type, TypeVar
+
+E = TypeVar("E", bound=Enum)
+
 
 import orjson
 
@@ -49,6 +52,21 @@ from src.llm_models.utils_model import LLMRequest
 logger = get_logger(__name__)
 
 
+CHINESE_TO_MEMORY_TYPE: dict[str, MemoryType] = {
+    "个人事实": MemoryType.PERSONAL_FACT,
+    "事件": MemoryType.EVENT,
+    "偏好": MemoryType.PREFERENCE,
+    "观点": MemoryType.OPINION,
+    "关系": MemoryType.RELATIONSHIP,
+    "情感": MemoryType.EMOTION,
+    "知识": MemoryType.KNOWLEDGE,
+    "技能": MemoryType.SKILL,
+    "目标": MemoryType.GOAL,
+    "经验": MemoryType.EXPERIENCE,
+    "上下文": MemoryType.CONTEXTUAL,
+}
+
+
 class ExtractionStrategy(Enum):
     """提取策略"""
 
@@ -428,7 +446,7 @@ class MemoryBuilder:
                     subject=normalized_subject,
                     predicate=predicate_value,
                     obj=object_value,
-                    memory_type=MemoryType(mem_data.get("type", "contextual")),
+                    memory_type=self._resolve_memory_type(mem_data.get("type")),
                     chat_id=context.get("chat_id"),
                     source_context=mem_data.get("reasoning", ""),
                     importance=importance_level,
@@ -459,7 +477,33 @@ class MemoryBuilder:
 
         return memories
 
-    def _parse_enum_value(self, enum_cls: type[Enum], raw_value: Any, default: Enum, field_name: str) -> Enum:
+    def _resolve_memory_type(self, type_str: Any) -> MemoryType:
+        """健壮地解析记忆类型，兼容中文和英文"""
+        if not isinstance(type_str, str) or not type_str.strip():
+            return MemoryType.CONTEXTUAL
+
+        cleaned_type = type_str.strip()
+
+        # 尝试中文映射
+        if cleaned_type in CHINESE_TO_MEMORY_TYPE:
+            return CHINESE_TO_MEMORY_TYPE[cleaned_type]
+
+        # 尝试直接作为枚举值解析
+        try:
+            return MemoryType(cleaned_type.lower().replace(" ", "_"))
+        except ValueError:
+            pass
+
+        # 尝试作为枚举名解析
+        try:
+            return MemoryType[cleaned_type.upper()]
+        except KeyError:
+            pass
+
+        logger.warning(f"无法解析未知的记忆类型 '{type_str}'，回退到上下文类型")
+        return MemoryType.CONTEXTUAL
+
+    def _parse_enum_value(self, enum_cls: Type[E], raw_value: Any, default: E, field_name: str) -> E:
         """解析枚举值，兼容数字/字符串表示"""
         if isinstance(raw_value, enum_cls):
             return raw_value

src/chat/memory_system/memory_system.py

@@ -162,7 +162,6 @@ class MemorySystem:
     async def initialize(self):
         """异步初始化记忆系统"""
         try:
-            logger.info("正在初始化记忆系统...")
 
             # 初始化LLM模型
             fallback_task = getattr(self.llm_model, "model_for_task", None) if self.llm_model else None
@@ -268,11 +267,8 @@ class MemorySystem:
                     logger.warning(f"海马体采样器初始化失败: {e}")
                     self.hippocampus_sampler = None
 
-            # 统一存储已经自动加载数据，无需额外加载
-            logger.info("✅ 简化版记忆系统初始化完成")
 
             self.status = MemorySystemStatus.READY
-            logger.info("✅ 记忆系统初始化完成")
 
         except Exception as e:
             self.status = MemorySystemStatus.ERROR
@@ -1425,16 +1421,6 @@ class MemorySystem:
     def _fingerprint_key(user_id: str, fingerprint: str) -> str:
         return f"{user_id!s}:{fingerprint}"
 
-    def get_system_stats(self) -> dict[str, Any]:
-        """获取系统统计信息"""
-        return {
-            "status": self.status.value,
-            "total_memories": self.total_memories,
-            "last_build_time": self.last_build_time,
-            "last_retrieval_time": self.last_retrieval_time,
-            "config": asdict(self.config),
-        }
-
     def _compute_memory_score(self, query_text: str, memory: MemoryChunk, context: dict[str, Any]) -> float:
         """根据查询和上下文为记忆计算匹配分数"""
         tokens_query = self._tokenize_text(query_text)
@@ -1542,7 +1528,7 @@ class MemorySystem:
 
             # 保存统一存储数据
             if self.unified_storage:
-                await self.unified_storage.cleanup()
+                self.unified_storage.cleanup()
 
             logger.info("✅ 简化记忆系统已关闭")
 

src/chat/memory_system/vector_memory_storage_v2.py

@@ -964,6 +964,11 @@ class VectorMemoryStorage:
 
         logger.info("Vector记忆存储系统已停止")
 
+    def cleanup(self):
+        """清理资源，兼容旧接口"""
+        logger.info("正在清理VectorMemoryStorage资源...")
+        self.stop()
+
 
 # 全局实例（可选）
 _global_vector_storage = None