重构数据库访问，替换为统一的数据库实例引用

src/plugins/memory_system/draw_memory.py

@@ -13,7 +13,7 @@ from loguru import logger
 root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
 sys.path.append(root_path)
 
-from src.common.database import Database  # 使用正确的导入语法
+from src.common.database import db  # 使用正确的导入语法
 
 # 加载.env.dev文件
 env_path = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))), '.env.dev')
@@ -23,7 +23,6 @@ load_dotenv(env_path)
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
 
     def connect_dot(self, concept1, concept2):
         self.G.add_edge(concept1, concept2)
@@ -96,7 +95,7 @@ class Memory_graph:
             dot_data = {
                 "concept": node
             }
-            self.db.store_memory_dots.insert_one(dot_data)
+            db.store_memory_dots.insert_one(dot_data)
 
     @property
     def dots(self):
@@ -106,7 +105,7 @@ class Memory_graph:
     def get_random_chat_from_db(self, length: int, timestamp: str):
         # 从数据库中根据时间戳获取离其最近的聊天记录
         chat_text = ''
-        closest_record = self.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])  # 调试输出
+        closest_record = db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])  # 调试输出
         logger.info(
             f"距离time最近的消息时间: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(int(closest_record['time'])))}")
 
@@ -115,7 +114,7 @@ class Memory_graph:
             group_id = closest_record['group_id']  # 获取groupid
             # 获取该时间戳之后的length条消息，且groupid相同
             chat_record = list(
-                self.db.messages.find({"time": {"$gt": closest_time}, "group_id": group_id}).sort('time', 1).limit(
+                db.messages.find({"time": {"$gt": closest_time}, "group_id": group_id}).sort('time', 1).limit(
                     length))
             for record in chat_record:
                 time_str = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(int(record['time'])))
@@ -130,50 +129,39 @@ class Memory_graph:
 
     def save_graph_to_db(self):
         # 清空现有的图数据
-        self.db.graph_data.delete_many({})
+        db.graph_data.delete_many({})
         # 保存节点
         for node in self.G.nodes(data=True):
             node_data = {
                 'concept': node[0],
                 'memory_items': node[1].get('memory_items', [])  # 默认为空列表
             }
-            self.db.graph_data.nodes.insert_one(node_data)
+            db.graph_data.nodes.insert_one(node_data)
         # 保存边
         for edge in self.G.edges():
             edge_data = {
                 'source': edge[0],
                 'target': edge[1]
             }
-            self.db.graph_data.edges.insert_one(edge_data)
+            db.graph_data.edges.insert_one(edge_data)
 
     def load_graph_from_db(self):
         # 清空当前图
         self.G.clear()
         # 加载节点
-        nodes = self.db.graph_data.nodes.find()
+        nodes = db.graph_data.nodes.find()
         for node in nodes:
             memory_items = node.get('memory_items', [])
             if not isinstance(memory_items, list):
                 memory_items = [memory_items] if memory_items else []
             self.G.add_node(node['concept'], memory_items=memory_items)
         # 加载边
-        edges = self.db.graph_data.edges.find()
+        edges = db.graph_data.edges.find()
         for edge in edges:
             self.G.add_edge(edge['source'], edge['target'])
 
 
 def main():
-    # 初始化数据库
-    Database.initialize(
-        uri=os.getenv("MONGODB_URI"),
-        host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-        port=int(os.getenv("MONGODB_PORT", "27017")),
-        db_name=os.getenv("DATABASE_NAME", "MegBot"),
-        username=os.getenv("MONGODB_USERNAME"),
-        password=os.getenv("MONGODB_PASSWORD"),
-        auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-    )
-
     memory_graph = Memory_graph()
     memory_graph.load_graph_from_db()
 

src/plugins/memory_system/memory.py

@@ -10,7 +10,7 @@ import networkx as nx
 
 from loguru import logger
 from nonebot import get_driver
-from ...common.database import Database  # 使用正确的导入语法
+from ...common.database import db  # 使用正确的导入语法
 from ..chat.config import global_config
 from ..chat.utils import (
     calculate_information_content,
@@ -23,7 +23,6 @@ from ..models.utils_model import LLM_request
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
 
     def connect_dot(self, concept1, concept2):
         # 避免自连接
@@ -191,19 +190,19 @@ class Hippocampus:
         # 短期：1h   中期：4h   长期：24h
         for _ in range(time_frequency.get('near')):
             random_time = current_timestamp - random.randint(1, 3600)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
 
         for _ in range(time_frequency.get('mid')):
             random_time = current_timestamp - random.randint(3600, 3600 * 4)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
 
         for _ in range(time_frequency.get('far')):
             random_time = current_timestamp - random.randint(3600 * 4, 3600 * 24)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
 
@@ -349,7 +348,7 @@ class Hippocampus:
     def sync_memory_to_db(self):
         """检查并同步内存中的图结构与数据库"""
         # 获取数据库中所有节点和内存中所有节点
-        db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        db_nodes = list(db.graph_data.nodes.find())
         memory_nodes = list(self.memory_graph.G.nodes(data=True))
 
         # 转换数据库节点为字典格式,方便查找
@@ -377,7 +376,7 @@ class Hippocampus:
                     'created_time': created_time,
                     'last_modified': last_modified
                 }
-                self.memory_graph.db.graph_data.nodes.insert_one(node_data)
+                db.graph_data.nodes.insert_one(node_data)
             else:
                 # 获取数据库中节点的特征值
                 db_node = db_nodes_dict[concept]
@@ -385,7 +384,7 @@ class Hippocampus:
 
                 # 如果特征值不同,则更新节点
                 if db_hash != memory_hash:
-                    self.memory_graph.db.graph_data.nodes.update_one(
+                    db.graph_data.nodes.update_one(
                         {'concept': concept},
                         {'$set': {
                             'memory_items': memory_items,
@@ -396,7 +395,7 @@ class Hippocampus:
                     )
 
         # 处理边的信息
-        db_edges = list(self.memory_graph.db.graph_data.edges.find())
+        db_edges = list(db.graph_data.edges.find())
         memory_edges = list(self.memory_graph.G.edges(data=True))
 
         # 创建边的哈希值字典
@@ -428,11 +427,11 @@ class Hippocampus:
                     'created_time': created_time,
                     'last_modified': last_modified
                 }
-                self.memory_graph.db.graph_data.edges.insert_one(edge_data)
+                db.graph_data.edges.insert_one(edge_data)
             else:
                 # 检查边的特征值是否变化
                 if db_edge_dict[edge_key]['hash'] != edge_hash:
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {
                             'hash': edge_hash,
@@ -451,7 +450,7 @@ class Hippocampus:
         self.memory_graph.G.clear()
 
         # 从数据库加载所有节点
-        nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        nodes = list(db.graph_data.nodes.find())
         for node in nodes:
             concept = node['concept']
             memory_items = node.get('memory_items', [])
@@ -468,7 +467,7 @@ class Hippocampus:
                 if 'last_modified' not in node:
                     update_data['last_modified'] = current_time
                 
-                self.memory_graph.db.graph_data.nodes.update_one(
+                db.graph_data.nodes.update_one(
                     {'concept': concept},
                     {'$set': update_data}
                 )
@@ -485,7 +484,7 @@ class Hippocampus:
                                        last_modified=last_modified)
 
         # 从数据库加载所有边
-        edges = list(self.memory_graph.db.graph_data.edges.find())
+        edges = list(db.graph_data.edges.find())
         for edge in edges:
             source = edge['source']
             target = edge['target']
@@ -501,7 +500,7 @@ class Hippocampus:
                 if 'last_modified' not in edge:
                     update_data['last_modified'] = current_time
                 
-                self.memory_graph.db.graph_data.edges.update_one(
+                db.graph_data.edges.update_one(
                     {'source': source, 'target': target},
                     {'$set': update_data}
                 )

src/plugins/memory_system/memory_manual_build.py

@@ -19,7 +19,7 @@ import jieba
 root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
 sys.path.append(root_path)
 
-from src.common.database import Database
+from src.common.database import db
 from src.plugins.memory_system.offline_llm import LLMModel
 
 # 获取当前文件的目录
@@ -49,7 +49,7 @@ def calculate_information_content(text):
     
     return entropy
 
-def get_cloest_chat_from_db(db, length: int, timestamp: str):
+def get_cloest_chat_from_db(length: int, timestamp: str):
     """从数据库中获取最接近指定时间戳的聊天记录，并记录读取次数
     
     Returns:
@@ -91,7 +91,6 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
         
     def connect_dot(self, concept1, concept2):
         # 如果边已存在，增加 strength
@@ -186,19 +185,19 @@ class Hippocampus:
         # 短期：1h   中期：4h   长期：24h
         for _ in range(time_frequency.get('near')):
             random_time = current_timestamp - random.randint(1, 3600*4)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('mid')):
             random_time = current_timestamp - random.randint(3600*4, 3600*24)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('far')):
             random_time = current_timestamp - random.randint(3600*24, 3600*24*7)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
@@ -323,7 +322,7 @@ class Hippocampus:
         self.memory_graph.G.clear()
         
         # 从数据库加载所有节点
-        nodes = self.memory_graph.db.graph_data.nodes.find()
+        nodes = db.graph_data.nodes.find()
         for node in nodes:
             concept = node['concept']
             memory_items = node.get('memory_items', [])
@@ -334,7 +333,7 @@ class Hippocampus:
             self.memory_graph.G.add_node(concept, memory_items=memory_items)
             
         # 从数据库加载所有边
-        edges = self.memory_graph.db.graph_data.edges.find()
+        edges = db.graph_data.edges.find()
         for edge in edges:
             source = edge['source']
             target = edge['target']
@@ -371,7 +370,7 @@ class Hippocampus:
         使用特征值(哈希值)快速判断是否需要更新
         """
         # 获取数据库中所有节点和内存中所有节点
-        db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        db_nodes = list(db.graph_data.nodes.find())
         memory_nodes = list(self.memory_graph.G.nodes(data=True))
         
         # 转换数据库节点为字典格式，方便查找
@@ -394,7 +393,7 @@ class Hippocampus:
                     'memory_items': memory_items,
                     'hash': memory_hash
                 }
-                self.memory_graph.db.graph_data.nodes.insert_one(node_data)
+                db.graph_data.nodes.insert_one(node_data)
             else:
                 # 获取数据库中节点的特征值
                 db_node = db_nodes_dict[concept]
@@ -403,7 +402,7 @@ class Hippocampus:
                 # 如果特征值不同，则更新节点
                 if db_hash != memory_hash:
                     # logger.info(f"更新节点内容: {concept}")
-                    self.memory_graph.db.graph_data.nodes.update_one(
+                    db.graph_data.nodes.update_one(
                         {'concept': concept},
                         {'$set': {
                             'memory_items': memory_items,
@@ -416,10 +415,10 @@ class Hippocampus:
         for db_node in db_nodes:
             if db_node['concept'] not in memory_concepts:
                 # logger.info(f"删除多余节点: {db_node['concept']}")
-                self.memory_graph.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
+                db.graph_data.nodes.delete_one({'concept': db_node['concept']})
                 
         # 处理边的信息
-        db_edges = list(self.memory_graph.db.graph_data.edges.find())
+        db_edges = list(db.graph_data.edges.find())
         memory_edges = list(self.memory_graph.G.edges())
         
         # 创建边的哈希值字典
@@ -445,12 +444,12 @@ class Hippocampus:
                     'num': 1,
                     'hash': edge_hash
                 }
-                self.memory_graph.db.graph_data.edges.insert_one(edge_data)
+                db.graph_data.edges.insert_one(edge_data)
             else:
                 # 检查边的特征值是否变化
                 if db_edge_dict[edge_key]['hash'] != edge_hash:
                     logger.info(f"更新边: {source} - {target}")
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {'hash': edge_hash}}
                     )
@@ -461,7 +460,7 @@ class Hippocampus:
             if edge_key not in memory_edge_set:
                 source, target = edge_key
                 logger.info(f"删除多余边: {source} - {target}")
-                self.memory_graph.db.graph_data.edges.delete_one({
+                db.graph_data.edges.delete_one({
                     'source': source,
                     'target': target
                 })
@@ -487,9 +486,9 @@ class Hippocampus:
             topic: 要删除的节点概念
         """
         # 删除节点
-        self.memory_graph.db.graph_data.nodes.delete_one({'concept': topic})
+        db.graph_data.nodes.delete_one({'concept': topic})
         # 删除所有涉及该节点的边
-        self.memory_graph.db.graph_data.edges.delete_many({
+        db.graph_data.edges.delete_many({
             '$or': [
                 {'source': topic},
                 {'target': topic}
@@ -902,17 +901,6 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
     plt.show()
 
 async def main():
-    # 初始化数据库
-    logger.info("正在初始化数据库连接...")
-    Database.initialize(
-        uri=os.getenv("MONGODB_URI"),
-        host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-        port=int(os.getenv("MONGODB_PORT", "27017")),
-        db_name=os.getenv("DATABASE_NAME", "MegBot"),
-        username=os.getenv("MONGODB_USERNAME"),
-        password=os.getenv("MONGODB_PASSWORD"),
-        auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-    )
     start_time = time.time()
 
     test_pare = {'do_build_memory':False,'do_forget_topic':False,'do_visualize_graph':True,'do_query':False,'do_merge_memory':False}

src/plugins/memory_system/memory_test1.py

@@ -38,7 +38,7 @@ import jieba
 
 # from chat.config import global_config
 sys.path.append("C:/GitHub/MaiMBot")  # 添加项目根目录到 Python 路径
-from src.common.database import Database
+from src.common.database import db
 from src.plugins.memory_system.offline_llm import LLMModel
 
 # 获取当前文件的目录
@@ -56,45 +56,6 @@ else:
     logger.warning(f"未找到环境变量文件: {env_path}")
     logger.info("将使用默认配置")
 
-class Database:
-    _instance = None
-    db = None
-    
-    @classmethod
-    def get_instance(cls):
-        if cls._instance is None:
-            cls._instance = cls()
-        return cls._instance
-    
-    def __init__(self):
-        if not Database.db:
-            Database.initialize(
-                    uri=os.getenv("MONGODB_URI"),
-                    host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-                    port=int(os.getenv("MONGODB_PORT", "27017")),
-                    db_name=os.getenv("DATABASE_NAME", "MegBot"),
-                    username=os.getenv("MONGODB_USERNAME"),
-                    password=os.getenv("MONGODB_PASSWORD"),
-                    auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-                )
-            
-    @classmethod
-    def initialize(cls, host, port, db_name, username=None, password=None, auth_source="admin"):
-        try:
-            if username and password:
-                uri = f"mongodb://{username}:{password}@{host}:{port}/{db_name}?authSource={auth_source}"
-            else:
-                uri = f"mongodb://{host}:{port}"
-                
-            client = pymongo.MongoClient(uri)
-            cls.db = client[db_name]
-            # 测试连接
-            client.server_info()
-            logger.success("MongoDB连接成功!")
-            
-        except Exception as e:
-            logger.error(f"初始化MongoDB失败: {str(e)}")
-            raise
 
 def calculate_information_content(text):
     """计算文本的信息量（熵）"""
@@ -108,7 +69,7 @@ def calculate_information_content(text):
     
     return entropy
 
-def get_cloest_chat_from_db(db, length: int, timestamp: str):
+def get_cloest_chat_from_db(length: int, timestamp: str):
     """从数据库中获取最接近指定时间戳的聊天记录，并记录读取次数
     
     Returns:
@@ -163,7 +124,7 @@ class Memory_cortex:
         default_time = datetime.datetime.now().timestamp()
         
         # 从数据库加载所有节点
-        nodes = self.memory_graph.db.graph_data.nodes.find()
+        nodes = db.graph_data.nodes.find()
         for node in nodes:
             concept = node['concept']
             memory_items = node.get('memory_items', [])
@@ -180,7 +141,7 @@ class Memory_cortex:
                 created_time = default_time
                 last_modified = default_time
                 # 更新数据库中的节点
-                self.memory_graph.db.graph_data.nodes.update_one(
+                db.graph_data.nodes.update_one(
                     {'concept': concept},
                     {'$set': {
                         'created_time': created_time,
@@ -196,7 +157,7 @@ class Memory_cortex:
                                        last_modified=last_modified)
             
         # 从数据库加载所有边
-        edges = self.memory_graph.db.graph_data.edges.find()
+        edges = db.graph_data.edges.find()
         for edge in edges:
             source = edge['source']
             target = edge['target']
@@ -212,7 +173,7 @@ class Memory_cortex:
                     created_time = default_time
                     last_modified = default_time
                     # 更新数据库中的边
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {
                             'created_time': created_time,
@@ -256,7 +217,7 @@ class Memory_cortex:
         current_time = datetime.datetime.now().timestamp()
         
         # 获取数据库中所有节点和内存中所有节点
-        db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        db_nodes = list(db.graph_data.nodes.find())
         memory_nodes = list(self.memory_graph.G.nodes(data=True))
         
         # 转换数据库节点为字典格式，方便查找
@@ -280,7 +241,7 @@ class Memory_cortex:
                     'created_time': data.get('created_time', current_time),
                     'last_modified': data.get('last_modified', current_time)
                 }
-                self.memory_graph.db.graph_data.nodes.insert_one(node_data)
+                db.graph_data.nodes.insert_one(node_data)
             else:
                 # 获取数据库中节点的特征值
                 db_node = db_nodes_dict[concept]
@@ -288,7 +249,7 @@ class Memory_cortex:
                 
                 # 如果特征值不同，则更新节点
                 if db_hash != memory_hash:
-                    self.memory_graph.db.graph_data.nodes.update_one(
+                    db.graph_data.nodes.update_one(
                         {'concept': concept},
                         {'$set': {
                             'memory_items': memory_items,
@@ -301,10 +262,10 @@ class Memory_cortex:
         memory_concepts = set(node[0] for node in memory_nodes)
         for db_node in db_nodes:
             if db_node['concept'] not in memory_concepts:
-                self.memory_graph.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
+                db.graph_data.nodes.delete_one({'concept': db_node['concept']})
                 
         # 处理边的信息
-        db_edges = list(self.memory_graph.db.graph_data.edges.find())
+        db_edges = list(db.graph_data.edges.find())
         memory_edges = list(self.memory_graph.G.edges(data=True))
         
         # 创建边的哈希值字典
@@ -332,11 +293,11 @@ class Memory_cortex:
                     'created_time': data.get('created_time', current_time),
                     'last_modified': data.get('last_modified', current_time)
                 }
-                self.memory_graph.db.graph_data.edges.insert_one(edge_data)
+                db.graph_data.edges.insert_one(edge_data)
             else:
                 # 检查边的特征值是否变化
                 if db_edge_dict[edge_key]['hash'] != edge_hash:
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {
                             'hash': edge_hash,
@@ -350,7 +311,7 @@ class Memory_cortex:
         for edge_key in db_edge_dict:
             if edge_key not in memory_edge_set:
                 source, target = edge_key
-                self.memory_graph.db.graph_data.edges.delete_one({
+                db.graph_data.edges.delete_one({
                     'source': source,
                     'target': target
                 })
@@ -365,9 +326,9 @@ class Memory_cortex:
             topic: 要删除的节点概念
         """
         # 删除节点
-        self.memory_graph.db.graph_data.nodes.delete_one({'concept': topic})
+        db.graph_data.nodes.delete_one({'concept': topic})
         # 删除所有涉及该节点的边
-        self.memory_graph.db.graph_data.edges.delete_many({
+        db.graph_data.edges.delete_many({
             '$or': [
                 {'source': topic},
                 {'target': topic}
@@ -377,7 +338,6 @@ class Memory_cortex:
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
         
     def connect_dot(self, concept1, concept2):
         # 避免自连接
@@ -492,19 +452,19 @@ class Hippocampus:
         # 短期：1h   中期：4h   长期：24h
         for _ in range(time_frequency.get('near')):
             random_time = current_timestamp - random.randint(1, 3600*4)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('mid')):
             random_time = current_timestamp - random.randint(3600*4, 3600*24)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('far')):
             random_time = current_timestamp - random.randint(3600*24, 3600*24*7)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_cloest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
@@ -1134,7 +1094,6 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
 async def main():
     # 初始化数据库
     logger.info("正在初始化数据库连接...")
-    db = Database.get_instance()
     start_time = time.time()
     
     test_pare = {'do_build_memory':True,'do_forget_topic':False,'do_visualize_graph':True,'do_query':False,'do_merge_memory':False}