Update endpoint

api.py

@@ -71,7 +71,7 @@ def creating_qdrant_index(embeddings):
     # )
 
     vector_store = QdrantVectorStore.from_existing_collection(
-        url="https://a2790d6c-f701-4a62-a57c-81d8fb4558f8.us-east-1-0.aws.cloud.qdrant.io:6333",
+        url="https://a2790d6c-f701-4a62-a57c-81d8fb4558f8.us-east-1-0.aws.cloud.qdrant.io",
         collection_name="rag-documents",
         embedding=embeddings,
         api_key=QDRANT_CLOUD_KEY,
@@ -303,7 +303,7 @@ if __name__ == "__main__":
     # Initializing embedding model for creating document vectors
     embeddings = GoogleGenerativeAIEmbeddings(model="models/text-embedding-004")
 
-    url = "https://a2790d6c-f701-4a62-a57c-81d8fb4558f8.us-east-1-0.aws.cloud.qdrant.io:6333"
+    url = "https://a2790d6c-f701-4a62-a57c-81d8fb4558f8.us-east-1-0.aws.cloud.qdrant.io"
 
     # Qdrant index name for storing document embeddings
     index_name = "rag-chatbot"