Update app.py

app.py

@@ -1,6 +1,7 @@
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import math
+import nltk
 import torch
 
 model_name = "craigchen/BART-139M-ecommerce-customer-service-anwser-to-query-generation"
@@ -82,7 +83,7 @@ def generate_title():
     # compute predictions
     outputs = model.generate(**inputs, do_sample=True, temperature=temperature)
     decoded_outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)
-    predicted_titles = decoded_outputs[0]
+    predicted_titles = [nltk.sent_tokenize(decoded_output.strip())[0] for decoded_output in decoded_outputs]
 
     st.session_state.titles = predicted_titles