try this

app.py

@@ -47,8 +47,7 @@ def respond(custom_string):
 
         out = model.out(model.decoder(outputs[:i].unsqueeze(0), e_outputs, src_mask, trg_mask))
         out = torch.nn.functional.softmax(out, dim=-1).detach()
-        print(out)
-        ix = np.random.choice(np.arange(out), 1, p=out)
+        ix = np.random.choice(np.arange(out[:, -1]), 1, p=out[:, -1])
         # val, ix = out[:, -1].data.topk(1)
 
         outputs[i] = ix[0][0]