Update app.py

app.py

@@ -89,12 +89,14 @@ QA_CHAIN_PROMPT = PromptTemplate(input_variables=["context", "question"],templat
 
 llm_model = "deepset/roberta-base-squad2"
 from transformers import AutoTokenizer
-#tokenizer = AutoTokenizer.from_pretrained(llm_model)
+tokenizer = AutoTokenizer.from_pretrained(llm_model)
 #question = "How can I reverse diabetes?"
 
+pipe = pipeline(model = llm_model, tokenizer = tokenizer, task = "text-generation", temperature=0.2)
+
 print("check2")
 qa = ConversationalRetrievalChain.from_llm(
-    llm_model,
+    pipe,
     retriever=retriever,
     memory=memory,
     chain_type_kwargs={"prompt": QA_CHAIN_PROMPT}
@@ -105,7 +107,6 @@ result = qa({"question": question})
 print("result")
 #result['answer']
 
-#pipe = pipeline(model = llm_model, tokenizer = tokenizer, task = "text-generation", temperature=0.2)
 #"question-answering", "conversational"
 
 print("check3")