diff --git a/src/backend/langflow/api/v1/validate.py b/src/backend/langflow/api/v1/validate.py
index d7ba8c15e..959273a00 100644
--- a/src/backend/langflow/api/v1/validate.py
+++ b/src/backend/langflow/api/v1/validate.py
@@ -1,5 +1,3 @@
-import json
-
 from fastapi import APIRouter, HTTPException
 
 from langflow.api.v1.base import (
@@ -9,8 +7,6 @@ from langflow.api.v1.base import (
     PromptValidationResponse,
     validate_prompt,
 )
-from langflow.graph.vertex.types import VectorStoreVertex
-from langflow.graph import Graph
 from langflow.utils.logger import logger
 from langflow.utils.validate import validate_code
 
@@ -37,26 +33,3 @@ def post_validate_prompt(prompt: Prompt):
     except Exception as e:
         logger.exception(e)
         raise HTTPException(status_code=500, detail=str(e)) from e
-
-
-# validate node
-@router.post("/node/{node_id}", status_code=200)
-def post_validate_node(node_id: str, data: dict):
-    try:
-        # build graph
-        graph = Graph.from_payload(data)
-        # validate node
-        node = graph.get_node(node_id)
-        if node is None:
-            raise ValueError(f"Node {node_id} not found")
-        if not isinstance(node, VectorStoreVertex):
-            node.build()
-        return json.dumps(
-            {
-                "valid": True,
-                "params": f"{str(node._built_object_repr())[:300]}...",
-            }
-        )
-    except Exception as e:
-        logger.exception(e)
-        return json.dumps({"valid": False, "params": str(e)})
diff --git a/src/backend/langflow/graph/vertex/base.py b/src/backend/langflow/graph/vertex/base.py
index a86e51d25..87a09d604 100644
--- a/src/backend/langflow/graph/vertex/base.py
+++ b/src/backend/langflow/graph/vertex/base.py
@@ -1,5 +1,5 @@
 from langflow.graph.vertex.constants import DIRECT_TYPES
-from langflow.interface import loading
+from langflow.interface.initialize import loading
 from langflow.interface.listing import ALL_TYPES_DICT
 from langflow.utils.logger import logger
 from langflow.utils.util import sync_to_async
diff --git a/src/backend/langflow/interface/initialize/vector_store.py b/src/backend/langflow/interface/initialize/vector_store.py
new file mode 100644
index 000000000..f3a10d0ba
--- /dev/null
+++ b/src/backend/langflow/interface/initialize/vector_store.py
@@ -0,0 +1,75 @@
+from typing import Any
+
+
+def docs_in_params(params: dict) -> bool:
+    """Check if params has documents OR texts and one of them is not an empty list"""
+    return ("documents" in params and params["documents"] != []) or (
+        "texts" in params and params["texts"] != []
+    )
+
+
+def initialize_pinecone(class_object: Any, params: dict):
+    """Initialize pinecone and return the class object"""
+    PINECONE_API_KEY = params.get("pinecone_api_key")
+    PINECONE_ENV = params.get("pinecone_env")
+
+    if PINECONE_API_KEY is None or PINECONE_ENV is None:
+        raise ValueError(
+            "Pinecone API key and environment must be provided in the params"
+        )
+
+    if not docs_in_params(params):
+        import pinecone
+
+        # initialize pinecone
+        pinecone.init(
+            api_key=PINECONE_API_KEY,  # find at app.pinecone.io
+            environment=PINECONE_ENV,  # next to api key in console
+        )
+        # If there are docs in the index, delete them
+        return class_object.from_existing_index(**params)
+    # If there are docs in the params, create a new index
+    if "texts" in params:
+        params["documents"] = params.pop("texts")
+    return class_object.from_documents(**params)
+
+
+def initialize_chroma(class_object, params):
+    """Initialize a ChromaDB object from the params"""
+    persist = params.pop("persist", False)
+    if not docs_in_params(params):
+        if "texts" in params:
+            params["documents"] = params.pop("texts")
+        for doc in params["documents"]:
+            if doc.metadata is None:
+                doc.metadata = {}
+            for key, value in doc.metadata.items():
+                if value is None:
+                    doc.metadata[key] = ""
+        chromadb = class_object.from_documents(**params)
+    else:
+        chromadb = class_object(**params)
+    if persist:
+        chromadb.persist()
+    return chromadb
+
+
+def initialize_qdrant(class_object, params):
+    if not docs_in_params(params):
+        if "location" not in params and "api_key" not in params:
+            raise ValueError("Location and API key must be provided in the params")
+        from qdrant_client import QdrantClient
+
+        client_params = {
+            "location": params.pop("location"),
+            "api_key": params.pop("api_key"),
+        }
+        lc_params = {
+            "collection_name": params.pop("collection_name"),
+            "embeddings": params.pop("embedding"),
+        }
+        client = QdrantClient(**client_params)
+
+        return class_object(client=client, **lc_params)
+
+    return class_object.from_documents(**params)