Update app.py

app.py

@@ -78,6 +78,7 @@ def pegasus(text):
                 length = len(sentence)
         
         sentences = [sentence.strip() for sentence in sentences]
+        size = len(sentences)
         # Append all tokenized sentences
         if sentences:
             tokenized_sentences.append(sentences)
@@ -89,6 +90,11 @@ def pegasus(text):
     global summary
     # Create an empty array for all summaries
     summary = []
+    if size <= 4: 
+       max_length= size
+    else:
+       max_length = size//4
+
     # Loop to encode tokens, to generate abstractive summary and finally decode tokens
     for token in tokenized:
         # Encoding
@@ -97,7 +103,7 @@ def pegasus(text):
         inputs = inputs.to(device)
         # Get summaries from transformer model
         all_summary = model2.to(device).generate(inputs,do_sample=True, 
-                                                max_length=50, top_k=50, top_p=0.95,
+                                                max_length=max_length, top_k=50, top_p=0.95,
                                                 num_beams = 5, early_stopping=True)
 #                                                 num_return_sequences=5)
 #                                                 length_penalty=0.2, no_repeat_ngram_size=2