diff --git a/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py b/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py
index cfa59165a4..d79bac8f67 100644
--- a/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py
+++ b/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py
@@ -131,9 +131,8 @@ class TableStoreVector(BaseVector):
         filtered_list = None
         if document_ids_filter:
             filtered_list = ["document_id=" + item for item in document_ids_filter]
-        score_threshold = float(kwargs.get("score_threshold") or 0.0)
 
-        return self._search_by_full_text(query, filtered_list, top_k, score_threshold)
+        return self._search_by_full_text(query, filtered_list, top_k)
 
     def delete(self) -> None:
         self._delete_table_if_exist()
@@ -294,12 +293,22 @@ class TableStoreVector(BaseVector):
             search_query=search_query,
             columns_to_get=tablestore.ColumnsToGet(return_type=tablestore.ColumnReturnType.ALL_FROM_INDEX),
         )
+        documents = []
+        for search_hit in search_response.search_hits:
+            if search_hit.score > score_threshold:
+                metadata = json.loads(search_hit.row[1][0][1])
+                metadata["score"] = search_hit.score
+                documents.append(
+                    Document(
+                        page_content=search_hit.row[1][2][1],
+                        vector=json.loads(search_hit.row[1][3][1]),
+                        metadata=metadata,
+                    )
+                )
+        documents = sorted(documents, key=lambda x: x.metadata["score"] if x.metadata else 0, reverse=True)
+        return documents
 
-        return self._to_query_result(search_response, score_threshold)
-
-    def _search_by_full_text(
-        self, query: str, document_ids_filter: list[str], top_k: int, score_threshold: float
-    ) -> list[Document]:
+    def _search_by_full_text(self, query: str, document_ids_filter: list[str], top_k: int) -> list[Document]:
         bool_query = tablestore.BoolQuery()
         bool_query.must_queries.append(tablestore.MatchQuery(text=query, field_name=Field.CONTENT_KEY.value))
 
@@ -318,23 +327,15 @@ class TableStoreVector(BaseVector):
             columns_to_get=tablestore.ColumnsToGet(return_type=tablestore.ColumnReturnType.ALL_FROM_INDEX),
         )
 
-        return self._to_query_result(search_response, score_threshold)
-
-    @staticmethod
-    def _to_query_result(search_response: tablestore.SearchResponse, score_threshold: float) -> list[Document]:
         documents = []
         for search_hit in search_response.search_hits:
-            if search_hit.score > score_threshold:
-                metadata = json.loads(search_hit.row[1][0][1])
-                metadata["score"] = search_hit.score
-                documents.append(
-                    Document(
-                        page_content=search_hit.row[1][2][1],
-                        vector=json.loads(search_hit.row[1][3][1]),
-                        metadata=metadata,
-                    )
+            documents.append(
+                Document(
+                    page_content=search_hit.row[1][2][1],
+                    vector=json.loads(search_hit.row[1][3][1]),
+                    metadata=json.loads(search_hit.row[1][0][1]),
                 )
-        documents = sorted(documents, key=lambda x: x.metadata["score"] if x.metadata else 0, reverse=True)
+            )
         return documents