Update app.py

app.py

@@ -280,6 +280,48 @@ with gr.Blocks() as demo:
         btn.click(chat, [inp, user_state], [output, user_state])
         btn.click(clear, inp, inp)
     gr.Markdown("""### need help? got feedback? have thoughts? etc. ➜ Join the [Discord](https://discord.gg/KvG3azf39U)""")
-    
+    gr.Examples(examples=['''---------------------------------------------------------------------------
+RuntimeError                              Traceback (most recent call last)
+/var/folders/49/9g9lxm9d3f3br8zlg2l2fmz80000gn/T/ipykernel_1349/2634282627.py in <module>
+----> 1 torch.onnx.export(model, x, "output.onnx")
+
+/opt/anaconda3/lib/python3.9/site-packages/torch/onnx/utils.py in export(model, args, f, export_params, verbose, training, input_names, output_names, operator_export_type, opset_version, do_constant_folding, dynamic_axes, keep_initializers_as_inputs, custom_opsets, export_modules_as_functions)
+    502     """
+    503 
+--> 504     _export(
+    505         model,
+    506         args,
+
+/opt/anaconda3/lib/python3.9/site-packages/torch/onnx/utils.py in _export(model, args, f, export_params, verbose, training, input_names, output_names, operator_export_type, export_type, opset_version, do_constant_folding, dynamic_axes, keep_initializers_as_inputs, fixed_batch_size, custom_opsets, add_node_names, onnx_shape_inference, export_modules_as_functions)
+   1527             _validate_dynamic_axes(dynamic_axes, model, input_names, output_names)
+   1528 
+-> 1529             graph, params_dict, torch_out = _model_to_graph(
+   1530                 model,
+   1531                 args,
+
+/opt/anaconda3/lib/python3.9/site-packages/torch/onnx/utils.py in _model_to_graph(model, args, verbose, input_names, output_names, operator_export_type, do_constant_folding, _disable_torch_constant_prop, fixed_batch_size, training, dynamic_axes)
+   1113 
+   1114     try:
+-> 1115         graph = _optimize_graph(
+   1116             graph,
+   1117             operator_export_type,
+
+/opt/anaconda3/lib/python3.9/site-packages/torch/onnx/utils.py in _optimize_graph(graph, operator_export_type, _disable_torch_constant_prop, fixed_batch_size, params_dict, dynamic_axes, input_names, module)
+    580     _C._jit_pass_lint(graph)
+    581     _C._jit_pass_onnx_autograd_function_process(graph)
+--> 582     C._jit_pass_lower_all_tuples(graph)
+    583 
+    584     # we now record some ops like ones/zeros
+
+RuntimeError: outerNode->outputs().size() == node->inputs().size() INTERNAL ASSERT FAILED at "/Users/runner/work/pytorch/pytorch/pytorch/torch/csrc/jit/passes/dead_code_elimination.cpp":140, please report a bug to PyTorch.''', '''error[E0382]: use of moved value: `primes`
+ --> src/main.rs:9:31
+  |
+9 |         if vectorIsPrime(num, primes) {
+  |                               ^^^^^^ value moved here, in previous iteration of loop
+  |
+  = note: move occurs because `primes` has type `std::vec::Vec<u64>`, which does not implement the `Copy` trait
+''', "Uncaught Error: Invariant Violation: Element type is invalid: expected a string (for built-in components) or a class/function (for composite components) but got: object."],
+        inputs=inp,
+        cache_examples=False,)
 if __name__ == "__main__":
     demo.launch(debug=True)