diff --git a/datasource/flask_server.py b/datasource/flask_server.py
index bac4226..ff739ea 100644
--- a/datasource/flask_server.py
+++ b/datasource/flask_server.py
@@ -460,12 +460,12 @@ def build_premium_result(premium_series: pd.Series) -> Dict:
     }
 
 
-def build_premium_result_from_attrs(premium_data: Dict) -> Dict:
+def build_premium_result_from_attrs(premium_data) -> Dict:
     """
-    从 attrs 格式构建溢价率返回结果
+    从 attrs 格式构建溢价率返回结果（兼容 Series 对象和字典格式）
     
     Args:
-        premium_data: attrs 中的溢价率数据，格式为：
+        premium_data: pd.Series 对象或字典格式：
             {
                 'type': 'series',
                 'data': {date_str: premium_value, ...},
@@ -475,16 +475,25 @@ def build_premium_result_from_attrs(premium_data: Dict) -> Dict:
     Returns:
         包含 premium_series, latest_premium, premium_date, premium_stats 的字典
     """
-    if not premium_data or premium_data.get('type') != 'series':
+    # 处理 None
+    if premium_data is None:
         return {}
     
-    # 从 dict 恢复为 Series
-    premium_dict = premium_data.get('data', {})
-    if not premium_dict:
+    # 如果是 pd.Series 对象（pickle 反序列化后）
+    if isinstance(premium_data, pd.Series):
+        premium_series = premium_data
+    # 如果是字典格式（旧 JSON 序列化格式）
+    elif isinstance(premium_data, dict):
+        if premium_data.get('type') != 'series':
+            return {}
+        premium_dict = premium_data.get('data', {})
+        if not premium_dict:
+            return {}
+        premium_series = pd.Series(premium_dict)
+        premium_series.index = pd.to_datetime(premium_series.index)
+    else:
         return {}
     
-    premium_series = pd.Series(premium_dict)
-    premium_series.index = pd.to_datetime(premium_series.index)
     premium_series.index.name = 'date'
     
     # 转换为日期-溢价率列表
@@ -735,13 +744,49 @@ def get_ohlcv():
         
         # 提取净值到顶层（方便调用方使用）
         if 'nav' in attrs:
-            result['nav'] = attrs['nav']
+            nav_df = attrs['nav']
+            if isinstance(nav_df, pd.DataFrame):
+                # 将 DataFrame 转换为列表格式（JSON 可序列化）
+                nav_df_copy = nav_df.reset_index().copy()
+                nav_df_copy['date'] = nav_df_copy['date'].dt.strftime('%Y-%m-%d')
+                nav_dict = {
+                    'data': nav_df_copy.to_dict(orient='records'),
+                    'count': len(nav_df_copy)
+                }
+                result['nav'] = nav_dict
+            else:
+                result['nav'] = nav_df
         
         # 提取溢价率到顶层（调用业务函数处理格式）
         if 'premium' in attrs:
             premium_result = build_premium_result_from_attrs(attrs['premium'])
             if premium_result:
                 result.update(premium_result)
+        
+        # 将 attrs 中的 DataFrame/Series 转换为字典格式（用于 JSON 序列化）
+        attrs_serializable = {}
+        for key, value in attrs.items():
+            if isinstance(value, pd.DataFrame):
+                df_copy = value.reset_index().copy()
+                if 'date' in df_copy.columns:
+                    df_copy['date'] = df_copy['date'].dt.strftime('%Y-%m-%d')
+                attrs_serializable[key] = {
+                    'data': df_copy.to_dict(orient='records'),
+                    'count': len(df_copy)
+                }
+            elif isinstance(value, pd.Series):
+                # 将 Series 索引转换为字符串
+                series_copy = value.copy()
+                series_copy.index = series_copy.index.strftime('%Y-%m-%d')
+                attrs_serializable[key] = {
+                    'type': 'series',
+                    'data': series_copy.to_dict(),
+                    'name': value.name
+                }
+            else:
+                attrs_serializable[key] = value
+        
+        result['attrs'] = attrs_serializable
     
     # 如果用户指定了类型但与自动检测不同，显示提示
     if asset_type_param and detected_type != final_type: