Update app.py

app.py

@@ -49,19 +49,21 @@ if uploaded_file is not None:
     essay = monkeyReader.readEssay(saved_file_path)
     for key, values in essay.items():
         st.write(f"{key}: {', '.join(values)}")
-
-    Barttokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn')
-    summ_model_path = 'com3dian/Bart-large-paper2slides-summarizer'
-    summarizor = BartForConditionalGeneration.from_pretrained(summ_model_path)
-    exp_model_path = 'com3dian/Bart-large-paper2slides-expander'
-    expandor = BartForConditionalGeneration.from_pretrained(exp_model_path)
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-    BartSE = BARTAutoEncoder(summarizor, summarizor, device)
-    del summarizor, expandor
         
-    document = Document(essay, Barttokenizer)
-    del Barttokenizer
-    length = document.merge(10, 30, BartSE, device)
+    with st.status("Generating slides..."):
+        
+        Barttokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn')
+        summ_model_path = 'com3dian/Bart-large-paper2slides-summarizer'
+        summarizor = BartForConditionalGeneration.from_pretrained(summ_model_path)
+        exp_model_path = 'com3dian/Bart-large-paper2slides-expander'
+        expandor = BartForConditionalGeneration.from_pretrained(exp_model_path)
+        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        BartSE = BARTAutoEncoder(summarizor, summarizor, device)
+        del summarizor, expandor
+            
+        document = Document(essay, Barttokenizer)
+        del Barttokenizer
+        length = document.merge(25, 30, BartSE, device)
 
     summarizor = pipeline("summarization", model=summ_model_path, device = 0)
     summ_text = summarizor(document.segmentation['text'], max_length=100, min_length=10, do_sample=False)