diff --git a/swarms/memory/qdrant.py b/swarms/memory/qdrant.py
index 56596965..83ff5593 100644
--- a/swarms/memory/qdrant.py
+++ b/swarms/memory/qdrant.py
@@ -1,5 +1,6 @@
 import subprocess
 from typing import List
+
 from httpx import RequestError
 
 try:
@@ -15,8 +16,8 @@ try:
     from qdrant_client import QdrantClient
     from qdrant_client.http.models import (
         Distance,
-        VectorParams,
         PointStruct,
+        VectorParams,
     )
 except ImportError:
     print("Please install the qdrant-client package")
@@ -91,7 +92,7 @@ class Qdrant:
             )
             print(f"Collection '{self.collection_name}' created.")
 
-    def add_vectors(self, docs: List[dict]):
+    def add(self, docs: List[dict], *args, **kwargs):
         """
         Adds vector representations of documents to the Qdrant collection.
 
@@ -128,13 +129,15 @@ class Qdrant:
                 collection_name=self.collection_name,
                 wait=True,
                 points=points,
+                *args,
+                **kwargs,
             )
             return operation_info
         except Exception as e:
             print(f"Error adding vectors: {e}")
             return None
 
-    def search_vectors(self, query: str, limit: int = 3):
+    def query(self, query: str, limit: int = 3, *args, **kwargs):
         """
         Searches the collection for vectors similar to the query vector.
 
@@ -147,12 +150,14 @@ class Qdrant:
         """
         try:
             query_vector = self.model.encode(
-                query, normalize_embeddings=True
+                query, normalize_embeddings=True, *args, **kwargs
             )
             search_result = self.client.search(
                 collection_name=self.collection_name,
                 query_vector=query_vector,
                 limit=limit,
+                *args,
+                **kwargs,
             )
             return search_result
         except Exception as e: