Update app.py

app.py

@@ -24,16 +24,20 @@ def sentiment_analysis_DB(input):
         pad_to_max_length=True,
         return_token_type_ids=True
     )
-    ids = inputs['input_ids']
-    mask = inputs['attention_mask']
-    token_type_ids = inputs["token_type_ids"]
+    ids = torch.tensor([inputs['input_ids']])  # Convert to PyTorch tensor
+    mask = torch.tensor([inputs['attention_mask']])  # Convert to PyTorch tensor
+    token_type_ids = torch.tensor([inputs["token_type_ids"]])  # Convert to PyTorch tensor
+
+    # Assuming model_DB is a PyTorch model
     output = model_DB(ids, mask, token_type_ids)
-    final_outputs = np.array(output)
-    final_outputs = final_outputs[0]
+    
+    final_outputs = output[0].item()  # Extract the scalar value
+
     if final_outputs == True:
         result = 1
     else:
         result = 0
+
     return result
 
 # Streamlit app