Update app.py

app.py

@@ -134,7 +134,7 @@ def create_embeddings(text_chunks):
 chunk_embeddings = create_embeddings(brand_chunks)
 
 # Define a function to find the most relevant text chunks for a given query, chunk_embeddings, and text_chunks
-def get_top_chunks(query, chunk_embeddings, text_chunks):
+def get_top_chunks(query, chunk_embeddings, text_chunks, top_k=7, similarity_threshold=0.4):
   if not text_chunks or chunk_embeddings is None or chunk_embeddings.size(0) == 0:
     return []
   # Convert the query text into a vector embedding