Updated code

utils.py

@@ -257,9 +257,8 @@ def load_ensemble_retriver(text_chunks, embeddings, chroma_vectorstore):
     bm25_retriever.k = 1
     chroma_retriever = chroma_vectorstore.as_retriever(search_kwargs={"k": 1})  
     ensemble_retriever = EnsembleRetriever(retrievers=[bm25_retriever, chroma_retriever], weights=[0.3, 0.7])
-    retriever_from_llm = MultiQueryRetriever.from_llm(retriever=ensemble_retriever, llm=ChatOpenAI()
-)
-    return retriever_from_llm
+    # retriever_from_llm = MultiQueryRetriever.from_llm(retriever=ensemble_retriever, llm=ChatOpenAI())
+    return ensemble_retriever
 
 
 def load_conversational_retrievel_chain(retriever, llm):
@@ -311,7 +310,7 @@ def load_conversational_retrievel_chain(retriever, llm):
     Helpful Answer:"""
 
     prompt = PromptTemplate(input_variables=["history", "context", "question"], template=template)
-    memory = ConversationBufferWindowMemory(input_key="question", memory_key="history", k=2)
+    memory = ConversationBufferWindowMemory(input_key="question", memory_key="history", k=1)
 
     qa = RetrievalQA.from_chain_type(
         llm=llm,