a

app.py

@@ -31,27 +31,31 @@ dict_category_answer = {
 
 
 def QA(text):
-    MODEL_NAME = 'cl-tohoku/bert-base-japanese-whole-word-masking'
-    bert_sc = BertForSequenceClassification.from_pretrained("/saved_model")
-
-    tokenizer = BertJapaneseTokenizer.from_pretrained(
-        MODEL_NAME,
-        model_max_length = 200,
-        padding_side="right"
-    )
-
-    question_classifier = pipeline(
-        "text-classification",
-        model=bert_sc.to("cpu"), 
-        tokenizer=tokenizer
-    )
-
-    predicted_output = question_classifier(text)
-    predicted_label = predicted_output[0]['label']
-
-    answer_text = dict_category_answer[predicted_label]
     
-    return answer_text
+    try:
+        MODEL_NAME = 'cl-tohoku/bert-base-japanese-whole-word-masking'
+        bert_sc = BertForSequenceClassification.from_pretrained("/saved_model")
+
+        tokenizer = BertJapaneseTokenizer.from_pretrained(
+            MODEL_NAME,
+            model_max_length = 200,
+            padding_side="right"
+        )
+
+        question_classifier = pipeline(
+            "text-classification",
+            model=bert_sc.to("cpu"), 
+            tokenizer=tokenizer
+        )
+
+        predicted_output = question_classifier(text)
+        predicted_label = predicted_output[0]['label']
+
+        answer_text = dict_category_answer[predicted_label]
+    except e:
+        return str(e)
+    
+    return "error occured"
 
 demo = gr.Interface(fn=QA, inputs="text", outputs="text")