Update app.py

app.py

@@ -1,10 +1,10 @@
 # Initialize a retriever using Qdrant and SentenceTransformer embeddings
-from langchain_community.vectorstores import Qdrant
-from langchain_community.embeddings import SentenceTransformerEmbeddings
-from kaggle_secrets import UserSecretsClient
+from langchain.vectorstores import Qdrant
+from langchain.retrievers import EnsembleRetriever
+from langchain.embeddings import SentenceTransformerEmbeddings
 from qdrant_client import QdrantClient
 import pandas as pd
-import gradio as gd
+import gradio as gr
 
 
 embeddings = SentenceTransformerEmbeddings(model_name='sentence-transformers/clip-ViT-B-32')
@@ -13,7 +13,6 @@ def get_results(search_results):
     filtered_img_ids = [doc.metadata.get("image_id") for doc in search_results]
     return filtered_img_ids
 
-user_secrets = UserSecretsClient()
 vector_db_key = user_secrets.get_secret("vector_db_key")
 
 client = QdrantClient(
@@ -39,4 +38,4 @@ def get_link(query):
     return links
 
 # print(get_link("black shirt for men"))
-gr.Interface(fn = get_link, inputs = 'textbox', outputs = 'textbox').launch()
+gr.Interface(fn = get_link, inputs = 'textbox', outputs = 'textbox').launch()