diff --git a/backend/open_webui/retrieval/utils.py b/backend/open_webui/retrieval/utils.py
index dead8458cb..b3dc52d7b2 100644
--- a/backend/open_webui/retrieval/utils.py
+++ b/backend/open_webui/retrieval/utils.py
@@ -432,13 +432,14 @@ def get_embedding_function(
             if isinstance(query, list):
                 embeddings = []
                 for i in range(0, len(query), embedding_batch_size):
-                    embeddings.extend(
-                        func(
-                            query[i : i + embedding_batch_size],
-                            prefix=prefix,
-                            user=user,
-                        )
+                    batch_embeddings = func(
+                        query[i : i + embedding_batch_size],
+                        prefix=prefix,
+                        user=user,
                     )
+
+                    if isinstance(batch_embeddings, list):
+                        embeddings.extend(batch_embeddings)
                 return embeddings
             else:
                 return func(query, prefix, user)
diff --git a/backend/open_webui/routers/retrieval.py b/backend/open_webui/routers/retrieval.py
index dd5e2d5bc4..9c3566ab2b 100644
--- a/backend/open_webui/routers/retrieval.py
+++ b/backend/open_webui/routers/retrieval.py
@@ -1334,7 +1334,7 @@ def save_docs_to_vector_db(
                 )
                 return True
 
-        log.info(f"adding to collection {collection_name}")
+        log.info(f"generating embeddings for {collection_name}")
         embedding_function = get_embedding_function(
             request.app.state.config.RAG_EMBEDDING_ENGINE,
             request.app.state.config.RAG_EMBEDDING_MODEL,
@@ -1381,11 +1381,18 @@ def save_docs_to_vector_db(
             for idx, text in enumerate(texts)
         ]
 
+        log.info(f"adding to collection {collection_name}")
         VECTOR_DB_CLIENT.insert(
             collection_name=collection_name,
             items=items,
         )
 
+        # Validate the number of items inserted
+        result = VECTOR_DB_CLIENT.query(
+            collection_name=collection_name,
+            filter={"metadata": metadata} if metadata else None,
+        )
+
         return True
     except Exception as e:
         log.exception(e)