diff --git a/libs/vertexai/langchain_google_vertexai/vectorstores/vectorstores.py b/libs/vertexai/langchain_google_vertexai/vectorstores/vectorstores.py
index ea0be4422..de3b782d5 100644
--- a/libs/vertexai/langchain_google_vertexai/vectorstores/vectorstores.py
+++ b/libs/vertexai/langchain_google_vertexai/vectorstores/vectorstores.py
@@ -1,6 +1,6 @@
 import uuid
 import warnings
-from typing import TYPE_CHECKING, Any, Iterable, List, Optional, Tuple, Type, Union
+from typing import Any, Iterable, List, Optional, Tuple, Type, Union
 
 from google.cloud.aiplatform.matching_engine.matching_engine_index_endpoint import (
     Namespace,
@@ -19,9 +19,6 @@
     Searcher,
 )
 
-if TYPE_CHECKING:
-    from langchain_community.embeddings import TensorflowHubEmbeddings
-
 
 class _BaseVertexAIVectorStore(VectorStore):
     """Represents a base vector store based on VertexAI."""
@@ -189,7 +186,7 @@ def from_texts(
         )
 
     @classmethod
-    def _get_default_embeddings(cls) -> "TensorflowHubEmbeddings":
+    def _get_default_embeddings(cls) -> Embeddings:
         """This function returns the default embedding.
         Returns:
             Default TensorflowHubEmbeddings to use.
@@ -205,12 +202,10 @@ def _get_default_embeddings(cls) -> "TensorflowHubEmbeddings":
         )
 
         # TODO: Change to vertexai embbedingss
-
-        from langchain_community.embeddings import (
-            TensorflowHubEmbeddings,  # type: ignore
-        )
-
-        return TensorflowHubEmbeddings()
+        # type: ignore[import-not-found]
+        from langchain_community import embeddings
+g
+        return embeddings.TensorflowHubEmbeddings()
 
     def _generate_unique_ids(self, number: int) -> List[str]:
         """Generates a list of unique ids of length `number`