Update app.py

app.py

@@ -84,7 +84,7 @@ def greet(htmlString,userQuestion):
     question = userQuestion
     single_html_string = htmlString
     #single_html_string = "<h1>Grid Fin</h1><table><tr><td><p>Cost Risk</p></td><td><p>None</p></td></tr><tr><td><p>Schedule Risk</p></td><td><p>None</p></td></tr></table><h1>Propulsion</h1><table><tr><td><p>Cost Risk</p></td><td><p>Yes, material overrun</p></td></tr><tr><td><p>Schedule Risk</p></td><td><p>None</p></td></tr></table><h1>Nose Cone</h1><table><tr><td><p>Cost Risk</p></td><td><p>Labor rate increases</p></td></tr><tr><td><p>Schedule Risk</p></td><td><p>None</p></td></tr></table>"
-    inputs = tokenizer.encode_plus(question, single_html_string, return_tensors="pt", padding="max_length", max_length=10, truncation=True) 
+    inputs = tokenizer.encode_plus(question, single_html_string, return_tensors="pt", padding="max_length", max_length=512, truncation=True) 
     
     answer_start_scores, answer_end_scores = model(**inputs, return_dict=False)
     answer_start = torch.argmax(answer_start_scores)  # get the most likely beginning of answer with the argmax of the score