Update app.py

app.py

@@ -6,7 +6,7 @@ import time
 from langchain.document_loaders import OnlinePDFLoader #for laoding the pdf
 from langchain.embeddings import OpenAIEmbeddings # for creating embeddings
 from langchain.vectorstores import Chroma # for the vectorization part
-from langchain.chains import ConversationalRetrievalChain # for conversing with chatGPT
+from langchain.chains import RetrievalQA # for conversing with chatGPT
 from langchain.chat_models import ChatOpenAI # the LLM model we'll use (ChatGPT)
 
 def loading_pdf():
@@ -29,7 +29,7 @@ def pdf_changes(pdf_doc, open_ai_key):
         #A ConversationalRetrievalChain is similar to a RetrievalQAChain, except that the ConversationalRetrievalChain allows for 
         #passing in of a chat history which can be used to allow for follow up questions.
         global pdf_qa
-        pdf_qa = ConversationalRetrievalChain.from_llm(ChatOpenAI(temperature=0, model_name="gpt-4"), vectordb.as_retriever(), return_source_documents=False)
+        pdf_qa = RetrievalQA.from_chain_type(ChatOpenAI(temperature=0, model_name="gpt-4"), vectordb.as_retriever(), return_source_documents=False)
         
         return "Ready"
     else: