Update app.py

app.py

@@ -709,7 +709,7 @@ chain = ConversationalRetrievalChain.from_llm(
 )
 
 
-
+"""
 # let's invoke the chain
 response = chain.invoke({"question":"what does Google stand for?"})
 print(response['answer'])
@@ -720,7 +720,7 @@ 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']
-
+"""
 
 from langchain.chains import ConversationalRetrievalChain
 
@@ -781,8 +781,19 @@ Standalone question:""")
 
 
 
+"""
+# let's invoke the chain
+response = chain.invoke({"question":"what does Google stand for?"})
+print(response['answer'])
 
 
+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']
+"""
+
 def submit_message(prompt, prompt_template, temperature, max_tokens, context_length, state):
     
     
@@ -796,7 +807,7 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
     completion = chain.invoke({"question":prompt})
     #chain = load_qa_chain(ChatOpenAI(temperature=temperature, max_tokens=max_tokens, model_name="gpt-3.5-turbo"), chain_type="stuff")
     #completion = chain.run(input_documents=docs, question=query)
-    print(completion)
+  
 
     
     get_empty_state()
@@ -805,12 +816,13 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
     
     completion = { "content": completion }
     print("completion2")
-    print(completion)
+    print(completion['content']['answer'])
+    print(completion['content']['answer'])
 
 
 
     #chat_messages = [(prompt_msg['content'], completion['content'])]    
-    chat_messages = [(prompt, completion)] 
+    chat_messages = [(prompt, completion['content']['answer'])] 
     return '', chat_messages,  state    # total_tokens_used_msg,