Update utils.py

utils.py

@@ -50,6 +50,7 @@ def ask_and_get_answer(vector_store, q, k=3):
     from langchain.chat_models import ChatOpenAI
     # choose the 3.5 turbo model which is default and set the temperature to 1 which is maximum
     llm = ChatOpenAI(model='gpt-3.5-turbo', temperature=1)
+    #VectorStoreRetrieverMemory stores memories in a VectorDB and queries the top-K most "salient" docs every time it is called.
     retriever = vector_store.as_retriever(search_type='similarity', search_kwargs={'k': k})
     chain = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever)
     answer = chain.run(q)