Update app.py

app.py

@@ -50,9 +50,7 @@ if query:
         temp.text("Searching for memories..!")
         query_embedding = model.encode(query).astype('float32').reshape(1, -1)  # Encode the query
         k = 6  # Number of nearest neighbors to retrieve
-        #distances, indices = index.search(query_embedding, k)
-        arr=index.search(query_embedding, k)
-        st.write(arr)
+        distances, indices = index.search(query_embedding, k)
         retrieved_chunks = [chunks[i] for i in indices[0]]
         # # Use a prompt to generate a response with your language model
         # input_prompt = f"""Given the question and