diff --git a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py
index 095752ea8e..6f3e15d166 100644
--- a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py
+++ b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py
@@ -233,6 +233,12 @@ class AnalyticdbVectorOpenAPI:
     def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
         from alibabacloud_gpdb20160503 import models as gpdb_20160503_models
 
+        document_ids_filter = kwargs.get("document_ids_filter")
+        where_clause = ""
+        if document_ids_filter:
+            document_ids = ", ".join(f"'{id}'" for id in document_ids_filter)
+            where_clause += f"metadata_->>'document_id' IN ({document_ids})"
+
         score_threshold = kwargs.get("score_threshold") or 0.0
         request = gpdb_20160503_models.QueryCollectionDataRequest(
             dbinstance_id=self.config.instance_id,
@@ -245,7 +251,7 @@ class AnalyticdbVectorOpenAPI:
             vector=query_vector,
             content=None,
             top_k=kwargs.get("top_k", 4),
-            filter=None,
+            filter=where_clause,
         )
         response = self._client.query_collection_data(request)
         documents = []
@@ -265,6 +271,11 @@ class AnalyticdbVectorOpenAPI:
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
         from alibabacloud_gpdb20160503 import models as gpdb_20160503_models
 
+        document_ids_filter = kwargs.get("document_ids_filter")
+        where_clause = ""
+        if document_ids_filter:
+            document_ids = ", ".join(f"'{id}'" for id in document_ids_filter)
+            where_clause += f"metadata_->>'document_id' IN ({document_ids})"
         score_threshold = float(kwargs.get("score_threshold") or 0.0)
         request = gpdb_20160503_models.QueryCollectionDataRequest(
             dbinstance_id=self.config.instance_id,
@@ -277,7 +288,7 @@ class AnalyticdbVectorOpenAPI:
             vector=None,
             content=query,
             top_k=kwargs.get("top_k", 4),
-            filter=None,
+            filter=where_clause,
         )
         response = self._client.query_collection_data(request)
         documents = []