fix(dc): Fix pivot column name tuple issue for single value column

Problem:
- When selecting only 1 value column in Pivot (long-to-wide), column names
  were incorrectly formatted as 'FMA___('FMA', 'baseline')' instead of 'FMA___baseline'
- This occurred because pandas pivot_table() sometimes returns tuple column names
  even for single value columns, but the code didn't handle this case

Root Cause:
- Line 112-127 in pivot.py assumed single value columns always have simple
  string column names, without checking for tuples
- Multi-value column logic (line 129-145) correctly handled tuples with isinstance()

Solution:
- Add isinstance(col, tuple) check in single value column mode
- Extract pivot_value from tuple[1] if column name is a tuple
- Maintain backward compatibility for non-tuple column names

Testing:
- Single value column: FMA___ + tuple -> 'FMA___baseline' (fixed)
- Multiple value columns: Already working correctly (no change)

Impact: Fixes historical bug in Tool C Pivot feature

extraction_service/operations/pivot.py

@@ -110,7 +110,7 @@ def pivot_long_to_wide(
         
         # ✨ 修复：更健壮的列名展平逻辑
         if len(value_columns) == 1:
-            # 单个值列：列名是单层的 (pivot_value1, pivot_value2, ...)
+            # 单个值列：列名可能是单层的，也可能是元组
             print(f'📝 单值列模式：展平列名', flush=True)
             
             # 获取原始值列名（用于生成新列名）
@@ -119,8 +119,15 @@ def pivot_long_to_wide(
             # 生成新列名：值列名___透视值
             new_columns = []
             for col in df_pivot.columns:
-                # col 是透视列的某个值（如 0, 1, 2）
-                new_col_name = f'{value_col_name}___{col}'
+                # ✅ 修复：检查col是否是元组（pandas在某些情况下会返回元组）
+                if isinstance(col, tuple):
+                    # 如果是元组 (值列名, 透视值)，取第二个元素
+                    pivot_value = col[1]
+                    new_col_name = f'{value_col_name}___{pivot_value}'
+                else:
+                    # 如果不是元组，直接使用（兼容旧行为）
+                    new_col_name = f'{value_col_name}___{col}'
+                
                 new_columns.append(new_col_name)
                 print(f'  生成列: {new_col_name}', flush=True)