diff --git a/ai/integrations/vector-search-integrate-with-langchain.md b/ai/integrations/vector-search-integrate-with-langchain.md
index b66cc877e9a8f..8c2e1da0f3489 100644
--- a/ai/integrations/vector-search-integrate-with-langchain.md
+++ b/ai/integrations/vector-search-integrate-with-langchain.md
@@ -15,7 +15,7 @@ This tutorial demonstrates how to integrate [TiDB Vector Search](/ai/concepts/ve
 
 > **Tip**
 >
-> You can view the complete [sample code](https://docs.langchain.com/oss/python/integrations/vectorstores/tidb_vector) in LangChain documentation.
+> You can view the complete sample code in <place-holder-url>.
 
 ## Prerequisites
 
diff --git a/ticdc/ticdc-debezium.md b/ticdc/ticdc-debezium.md
index f5b4ab2cc36a2..05a580652e11b 100644
--- a/ticdc/ticdc-debezium.md
+++ b/ticdc/ticdc-debezium.md
@@ -781,7 +781,7 @@ The key fields of the preceding JSON data are explained as follows:
 
 ### Data type mapping
 
-The data format mapping in the TiCDC Debezium message basically follows the [Debezium data type mapping rules](https://debezium.io/documentation/reference/2.4/connectors/mysql.html#mysql-data-types), which is generally consistent with the native message of the Debezium Connector for MySQL. However, for some data types, the following differences exist between TiCDC Debezium and Debezium Connector messages:
+The data format mapping in the TiCDC Debezium message basically follows the [Debezium data type mapping rules](https://debezium.io/documentation/reference/stable/connectors/mysql.html#mysql-data-types), which is generally consistent with the native message of the Debezium Connector for MySQL. However, for some data types, the following differences exist between TiCDC Debezium and Debezium Connector messages:
 
 - Currently, TiDB does not support spatial data types, including GEOMETRY, LINESTRING, POLYGON, MULTIPOINT, MULTILINESTRING, MULTIPOLYGON, and GEOMETRYCOLLECTION.