Update app.py

app.py

@@ -1,50 +1,3 @@
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-Update app.py
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-2.12 kB
 ### STREAMLIT APP ####
 import streamlit as st
 from transformers import BertTokenizer, EncoderDecoderModel, EncoderDecoderConfig
@@ -65,18 +18,20 @@ except Exception as e:
 text = st.text_area('Enter an article to summarize:')
 
 if text and len(text) > 0:
+    # Ensure input is a string
     input_ids = tokenizer.encode(text, return_tensors='pt', padding='longest', truncation=True, max_length=512)
+    
     summary_ids = model.generate(input_ids,
-            min_length=40,
-            max_length=200,
-            num_beams=10,
-            repetition_penalty=2.0,
-            length_penalty=1.0,
-            no_repeat_ngram_size=3,
-            use_cache=True,
-            do_sample=False,
-            top_k=50,
-            )
+                                  min_length=40,
+                                  max_length=200,
+                                  num_beams=10,
+                                  repetition_penalty=2.0,
+                                  length_penalty=1.0,
+                                  no_repeat_ngram_size=3,
+                                  use_cache=True,
+                                  do_sample=False,
+                                  top_k=50,
+                                  )
 
     summary_text = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
     
@@ -101,5 +56,4 @@ if text and len(text) > 0:
             summary_text = summary_text.replace(wrong_term, correct_term)
         
         summary_text = capitalize_sentences(summary_text)
-        st.info(summary_text)
-
+        st.info(summary_text)  # Ensure this is passed a string