diff --git a/dsRag/Milvus/Utils/MilvusCollectionManager.py b/dsRag/Milvus/Utils/MilvusCollectionManager.py
index 389b7e3a..fdfce8d7 100644
--- a/dsRag/Milvus/Utils/MilvusCollectionManager.py
+++ b/dsRag/Milvus/Utils/MilvusCollectionManager.py
@@ -71,7 +71,7 @@ class MilvusCollectionManager:
             # 使用 Milvus 的 query 方法查询指定 ID 的记录
             results = self.collection.query(
                 expr=f"id == {id}",  # 查询条件
-                output_fields=["id", "document_id", "user_input", "timestamp"]  # 返回的字段
+                output_fields=["id", "tags", "user_input", "timestamp"]  # 返回的字段
             )
             if results:
                 return results[0]  # 返回第一条记录
diff --git a/dsRag/Milvus/Utils/__pycache__/MilvusCollectionManager.cpython-310.pyc b/dsRag/Milvus/Utils/__pycache__/MilvusCollectionManager.cpython-310.pyc
index b42a2a2b..99ebc8ab 100644
Binary files a/dsRag/Milvus/Utils/__pycache__/MilvusCollectionManager.cpython-310.pyc and b/dsRag/Milvus/Utils/__pycache__/MilvusCollectionManager.cpython-310.pyc differ
diff --git a/dsRag/Milvus/X1_create_collection.py b/dsRag/Milvus/X1_create_collection.py
index f1a33d1d..6d7372b9 100644
--- a/dsRag/Milvus/X1_create_collection.py
+++ b/dsRag/Milvus/X1_create_collection.py
@@ -32,7 +32,7 @@ fields = [
     FieldSchema(name="timestamp", dtype=DataType.VARCHAR, max_length=32),
     FieldSchema(name="embedding", dtype=DataType.FLOAT_VECTOR, dim=MS_DIMENSION)
 ]
-schema_description = "Chat records collection with document_id , user_input, and timestamp"
+schema_description = "Chat records collection with tags , user_input, and timestamp"
 
 # 6. 创建集合
 print(f"正在创建集合 '{collection_name}'...")
diff --git a/dsRag/Milvus/X6_search_near_data.py b/dsRag/Milvus/X6_search_near_data.py
index 0546c5cd..37ec1c4a 100644
--- a/dsRag/Milvus/X6_search_near_data.py
+++ b/dsRag/Milvus/X6_search_near_data.py
@@ -54,8 +54,7 @@ search_params = {
 }
 # 哪些文档查询，哪些不查询，我说了算！
 # 这样的话，我就可以打多个标签了！
-# expr = "document_id in ['MATH_DATA_1', 'MATH_DATA_2']"
-expr = "tags['tags'] == 'MATH_DATA_1'"
+expr = "array_contains(tags['tags'], 'MATH_DATA_1')"
 results = collection_manager.search(
     current_embedding,
     search_params,