diff --git a/src/backend/base/langflow/components/vectorstores/AstraDB.py b/src/backend/base/langflow/components/vectorstores/AstraDB.py
index 71b58444a..13532d266 100644
--- a/src/backend/base/langflow/components/vectorstores/AstraDB.py
+++ b/src/backend/base/langflow/components/vectorstores/AstraDB.py
@@ -1,19 +1,11 @@
-from langflow.custom import Component
-from langflow.inputs import (
-    StrInput,
-    IntInput,
-    BoolInput,
-    DropdownInput,
-    MultilineInput,
-    HandleInput,
-)
-from langflow.schema import Data
-from langflow.template import Output
-
 from loguru import logger
 
+from langflow.base.vectorstores.model import LCVectorStoreComponent
+from langflow.inputs import BoolInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput
+from langflow.schema import Data
 
-class AstraVectorStoreComponent(Component):
+
+class AstraVectorStoreComponent(LCVectorStoreComponent):
     display_name: str = "Astra DB Vector Store"
     description: str = "Implementation of Vector Store using Astra DB with search capabilities"
     documentation: str = "https://python.langchain.com/docs/integrations/vectorstores/astradb"
@@ -25,21 +17,17 @@ class AstraVectorStoreComponent(Component):
             display_name="Collection Name",
             info="The name of the collection within Astra DB where the vectors will be stored.",
         ),
-        StrInput(
+        SecretStrInput(
             name="token",
             display_name="Astra DB Application Token",
             info="Authentication token for accessing Astra DB.",
-            password=True,
+            value="ASTRA_DB_APPLICATION_TOKEN",
         ),
-        StrInput(
+        SecretStrInput(
             name="api_endpoint",
             display_name="API Endpoint",
             info="API endpoint URL for the Astra DB service.",
-        ),
-        StrInput(
-            name="code",
-            display_name="Code",
-            advanced=True,
+            value="ASTRA_DB_API_ENDPOINT",
         ),
         HandleInput(
             name="vector_store_inputs",
@@ -95,6 +83,7 @@ class AstraVectorStoreComponent(Component):
             info="Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.",
             options=["Sync", "Async", "Off"],
             advanced=True,
+            value="Sync",
         ),
         BoolInput(
             name="pre_delete_collection",
@@ -144,24 +133,6 @@ class AstraVectorStoreComponent(Component):
         ),
     ]
 
-    outputs = [
-        Output(
-            display_name="Vector Store",
-            name="vector_store",
-            method="build_vector_store",
-        ),
-        Output(
-            display_name="Base Retriever",
-            name="base_retriever",
-            method="build_base_retriever",
-        ),
-        Output(
-            display_name="Search Results",
-            name="search_results",
-            method="search_documents",
-        ),
-    ]
-
     def build_vector_store(self):
         try:
             from langchain_astradb import AstraDBVectorStore
@@ -173,6 +144,9 @@ class AstraVectorStoreComponent(Component):
             )
 
         try:
+            if not self.setup_mode:
+                self.setup_mode = self._inputs["setup_mode"].options[0]
+
             setup_mode_value = SetupMode[self.setup_mode.upper()]
         except KeyError:
             raise ValueError(f"Invalid setup mode: {self.setup_mode}")
@@ -182,14 +156,14 @@ class AstraVectorStoreComponent(Component):
             "collection_name": self.collection_name,
             "token": self.token,
             "api_endpoint": self.api_endpoint,
-            "namespace": self.namespace,
-            "metric": self.metric,
-            "batch_size": self.batch_size,
-            "bulk_insert_batch_concurrency": self.bulk_insert_batch_concurrency,
-            "bulk_insert_overwrite_concurrency": self.bulk_insert_overwrite_concurrency,
-            "bulk_delete_concurrency": self.bulk_delete_concurrency,
+            "namespace": self.namespace or None,
+            "metric": self.metric or None,
+            "batch_size": self.batch_size or None,
+            "bulk_insert_batch_concurrency": self.bulk_insert_batch_concurrency or None,
+            "bulk_insert_overwrite_concurrency": self.bulk_insert_overwrite_concurrency or None,
+            "bulk_delete_concurrency": self.bulk_delete_concurrency or None,
             "setup_mode": setup_mode_value,
-            "pre_delete_collection": self.pre_delete_collection,
+            "pre_delete_collection": self.pre_delete_collection or False,
         }
 
         if self.metadata_indexing_include:
@@ -207,11 +181,12 @@ class AstraVectorStoreComponent(Component):
         if self.add_to_vector_store:
             self._add_documents_to_vector_store(vector_store)
 
-        self.status = self._astradb_collection_to_data(vector_store.collection)
         return vector_store
 
     def build_base_retriever(self):
-        return self.build_vector_store()
+        vector_store = self.build_vector_store()
+        self.status = self._astradb_collection_to_data(vector_store.collection)
+        return vector_store
 
     def _add_documents_to_vector_store(self, vector_store):
         documents = []
@@ -256,7 +231,7 @@ class AstraVectorStoreComponent(Component):
 
             logger.debug(f"Retrieved documents: {len(docs)}")
 
-            data = self._docs_to_data(docs)
+            data = [Data.from_document(doc) for doc in docs]
             logger.debug(f"Converted documents to data: {len(data)}")
             self.status = data
             return data
@@ -266,12 +241,10 @@ class AstraVectorStoreComponent(Component):
 
     def _astradb_collection_to_data(self, collection):
         data = []
-        for item in collection["data"]:
+        data_dict = collection.find()
+        if data_dict and "data" in data_dict:
+            data_dict = data_dict["data"].get("documents", [])
+
+        for item in data_dict:
             data.append(Data(content=item["content"]))
         return data
-
-    def _docs_to_data(self, docs):
-        data = []
-        for doc in docs:
-            data.append(Data(content=doc.page_content))
-        return data