diff --git a/src/backend/langflow/interface/custom_lists.py b/src/backend/langflow/interface/custom_lists.py
index f07b03f04..af453139b 100644
--- a/src/backend/langflow/interface/custom_lists.py
+++ b/src/backend/langflow/interface/custom_lists.py
@@ -60,11 +60,6 @@ embedding_type_to_cls_dict: dict[str, Any] = {
     for embedding_name in embeddings.__all__
 }
 
-## Vector Stores
-vectorstores_type_to_cls_dict: dict[str, Any] = {
-    vectorstore_name: import_class(f"langchain.vectorstores.{vectorstore_name}")
-    for vectorstore_name in vectorstores.__all__
-}
 
 ## Document Loaders
 documentloaders_type_to_cls_dict: dict[str, Any] = {
diff --git a/src/backend/langflow/interface/vector_store/base.py b/src/backend/langflow/interface/vector_store/base.py
index 425fa9559..d30563d7b 100644
--- a/src/backend/langflow/interface/vector_store/base.py
+++ b/src/backend/langflow/interface/vector_store/base.py
@@ -1,11 +1,13 @@
-from typing import Dict, List, Optional, Type
+from typing import Any, Dict, List, Optional, Type
+
+from langchain import vectorstores
 
 from langflow.interface.base import LangChainTypeCreator
-from langflow.interface.custom_lists import vectorstores_type_to_cls_dict
+from langflow.interface.importing.utils import import_class
 from langflow.settings import settings
 from langflow.template.nodes import VectorStoreFrontendNode
 from langflow.utils.logger import logger
-from langflow.utils.util import build_template_from_class, build_template_from_method
+from langflow.utils.util import build_template_from_method
 
 
 class VectorstoreCreator(LangChainTypeCreator):
@@ -17,36 +19,23 @@ class VectorstoreCreator(LangChainTypeCreator):
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return vectorstores_type_to_cls_dict
+        if self.type_dict is None:
+            self.type_dict: dict[str, Any] = {
+                vectorstore_name: import_class(
+                    f"langchain.vectorstores.{vectorstore_name}"
+                )
+                for vectorstore_name in vectorstores.__all__
+            }
+        return self.type_dict
 
     def get_signature(self, name: str) -> Optional[Dict]:
         """Get the signature of an embedding."""
         try:
-            signature = build_template_from_method(
+            return build_template_from_method(
                 name,
-                type_to_cls_dict=vectorstores_type_to_cls_dict,
+                type_to_cls_dict=self.type_to_loader_dict,
                 method_name="from_texts",
             )
-
-            # TODO: Use FrontendendNode class to build the signature
-            # signature["template"] = {
-            #     "documents": {
-            #         "type": "TextSplitter",
-            #         "required": True,
-            #         "show": True,
-            #         "name": "documents",
-            #         "display_name": "Text Splitter",
-            #     },
-            #     "embedding": {
-            #         "type": "Embeddings",
-            #         "required": True,
-            #         "show": True,
-            #         "name": "embedding",
-            #         "display_name": "Embedding",
-            #     },
-            # }
-            return signature
-
         except ValueError as exc:
             raise ValueError(f"Vector Store {name} not found") from exc
         except AttributeError as exc: