Update app.py

app.py

@@ -50,25 +50,27 @@ if uploaded_file is not None:
     for key, values in essay.items():
         st.write(f"{key}: {', '.join(values)}")
         
-    with st.status("Understanding paper..."):
+    # with st.status("Understanding paper..."):
         
-        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
+    #     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)
+    #     document = Document(essay, Barttokenizer)
+    #     del Barttokenizer
+    #     length = document.merge(25, 30, BartSE, device)
 
-    with st.status("Generating slides..."):
-        summarizor = pipeline("summarization", model=summ_model_path, device = device)
-        summ_text = summarizor(document.segmentation['text'], max_length=100, min_length=10, do_sample=False)
-        summ_text = [text['summary_text'] for text in summ_text]
+    # with st.status("Generating slides..."):
+    #     summarizor = pipeline("summarization", model=summ_model_path, device = device)
+    #     summ_text = summarizor(document.segmentation['text'], max_length=100, min_length=10, do_sample=False)
+    #     summ_text = [text['summary_text'] for text in summ_text]
         
-        for summ in summ_text:
-            st.write(summ)
+    #     for summ in summ_text:
+    #         st.write(summ)
+
+