Update app.py

app.py

@@ -109,17 +109,18 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
         #completion = completion.run(query)
         # from https://blog.devgenius.io/chat-with-document-s-using-openai-chatgpt-api-and-text-embedding-6a0ce3dc8bc8
 
-        completion = ChatVectorDBChain.from_llm(ChatOpenAI(temperature=temperature, max_tokens=max_tokens, model_name="gpt-3.5-turbo"), vectordb, return_source_documents=True)
+        completion = VectorDBQA.from_chain_type(llm=ChatOpenAI(temperature=temperature, max_tokens=max_tokens, model_name="gpt-3.5-turbo"), chain_type="stuff", vectorstore=vectordb, return_source_documents=True)
         query = str(system_prompt + history[-context_length*2:] +  [prompt_msg])
-        completion = completion({"question": query, "chat_history": history[-context_length*2:]})
-
-
+        completion = completion({"query": query})
+#        completion = completion({"question": query, "chat_history": history[-context_length*2:]})
 
 
+# VectorDBQA.from_chain_type(llm=OpenAI(), chain_type="stuff", vectorstore=docsearch, return_source_documents=True)
+# https://colab.research.google.com/drive/1dzdNDZyofRB0f2KIB4gHXmIza7ehMX30?usp=sharing#scrollTo=b-ejDn_JfpWW
         
         history.append(prompt_msg)
         #history.append(completion.choices[0].message.to_dict())
-        history.append(completion["result"])
+        history.append(completion['result'])
 
         state['total_tokens'] += completion['usage']['total_tokens']