Update app.py

app.py

@@ -11,22 +11,25 @@ model = AutoModelForQuestionAnswering.from_pretrained(model_name, revision=revis
 model.eval()
 
 def qna(image, question):
+    try:
+        res = image_processor(image, apply_ocr = True)
+        words = res["words"][0]
+        boxes = res["boxes"][0]
     
-    res = image_processor(image, apply_ocr = True)
-    words = res["words"][0]
-    boxes = res["boxes"][0]
-
-    encoding = tokenizer(question, words, boxes = boxes, return_token_type_ids=True, return_tensors="pt", truncation=True, padding="max_length")
-
-    word_ids = encoding.word_ids(0)
-    outputs = model(**encoding)
-
-    start_scores = outputs.start_logits
-    end_scores = outputs.end_logits
-
-    start, end = word_ids[start_scores.argmax(-1).item()], word_ids[end_scores.argmax(-1).item()]
+        encoding = tokenizer(question, words, boxes = boxes, return_token_type_ids=True, return_tensors="pt", truncation=True, padding="max_length")
+    
+        word_ids = encoding.word_ids(0)
+        outputs = model(**encoding)
+    
+        start_scores = outputs.start_logits
+        end_scores = outputs.end_logits
+    
+        start, end = word_ids[start_scores.argmax(-1).item()], word_ids[end_scores.argmax(-1).item()]
+    
+        answer = " ".join(words[start : end + 1])
 
-    answer = " ".join(words[start : end + 1])
+    except:
+        answer = "No Answer"
     
     
     return answer