Update app.py

app.py

@@ -55,10 +55,14 @@ model = BertModel.from_pretrained('bert-base-uncased').to(device)
 
 # Function to embed the question using BERT
 def embed_question(question, model, tokenizer):
-    inputs = tokenizer(question, return_tensors='pt').to(device)
-    with torch.no_grad():
-        outputs = model(**inputs)
-    return outputs.last_hidden_state.mean(dim=1).cpu().numpy().astype(np.float32)
+    try:
+        inputs = tokenizer(question, return_tensors='pt').to(device)
+        with torch.no_grad():
+            outputs = model(**inputs)
+        return outputs.last_hidden_state.mean(dim=1).cpu().numpy().astype(np.float32)
+    except Exception as e:
+        logging.error(f"Error embedding question: {e}")
+        raise
 
 # Function to retrieve the relevant document and generate a response
 @spaces.GPU(duration=120)