Update app.py

app.py

@@ -475,7 +475,7 @@ chain = ConversationalRetrievalChain.from_llm(
         LLM_provider="Google",api_key=HF_key,temperature=0.1,
         model_name="gemini-pro"),
     memory=create_memory("gemini-pro"),
-    retriever = base_retriever_google,
+    retriever = BaseRetriever,
     llm=instantiate_LLM(
         LLM_provider="Google",api_key=HF_key,temperature=0.5,
         model_name="gemini-pro"),
@@ -486,6 +486,19 @@ chain = ConversationalRetrievalChain.from_llm(
 
 
 
+# let's invoke the chain
+response = chain.invoke({"question":"what does DTC stand for?"})
+response
+
+
+chain.memory.load_memory_variables({})
+
+follow_up_question = "plaese give more details about it, including its use cases and implementation."
+
+chain.invoke({"question":follow_up_question})['answer'])
+
+
+"""
 # 1. load memory using RunnableLambda. Retrieves the chat_history attribute using itemgetter.
 # `RunnablePassthrough.assign` adds the chat_history to the assign function
 
@@ -525,6 +538,9 @@ memory.save_context(
     {"question": "What does DTC stand for?"},
     {"answer": "Diffuse to Choose."}
 )
+
+"""
+
 print("Chat history:\n",memory.load_memory_variables({}))
 
 follow_up_question = "plaese give more details about it, including its use cases and implementation."