Update app.py

app.py

@@ -50,7 +50,7 @@ def get_splade_representation(text):
         # output.logits is typically [batch_size, sequence_length, vocab_size]
         # We need to take the max over the sequence_length dimension to get a [batch_size, vocab_size] vector.
         # inputs.attention_mask.unsqueeze(-1) expands the mask to match vocab_size for element-wise multiplication.
-        splade_vector = torch.max(torch.log(1 + torch.relu(output.logits)) * inputs.attention_mask.unsqueeze(-1), dim=1)[0].squeeze()
+        splade_vector = torch.max(torch.log(1 + torch.relu(output.logits)) * inputs['attention_mask'].unsqueeze(-1), dim=1)[0].squeeze()
     else:
         # Fallback/error message if the output structure is unexpected
         return "Model output structure not as expected for SPLADE. 'logits' not found."