update description

app.py

@@ -48,18 +48,19 @@ def predict(input_text, mcts_playouts):
 
 gradio_app = gr.Interface(
     predict,
-    inputs=[gr.Code(value=aiger_str, label="Input And-Inverter Graph (Aiger format, #(inputs) <= 8, #(outputs) <= 2)"),
+    inputs=[gr.Code(value=aiger_str, label="Input logic circuit (in Aiger format, #(inputs) <= 8, #(outputs) <= 2)"),
             gr.Slider(minimum=0, maximum=8, value=0, step=1, label="Monte-Carlo tree search steps")],
-    outputs=[gr.Code(label="Optimized And-Inverter Graph (Aiger format)"),
-             gr.BarPlot(label="Circuit Size Comparison", x="circuit", y="size", sort="-x"),
-             gr.Image(label="Original And-Inverter Graph"),
-             gr.Image(label="Optimized And-Inverter Graph"),
+    outputs=[gr.Code(label="Output logic circuit (size-optimized, in Aiger format)"),
+             gr.BarPlot(label="Circuit size comparison", x="circuit", y="size", sort="-x"),
+             gr.Image(label="Original logic circuit (And-Inverter Graph)"),
+             gr.Image(label="Optimized logic circuit (And-Inverter Graph)"),
              gr.Text(label="Truth table of the original circuit"),
              gr.Text(label="Truth table of the optimized circuit"),
              gr.Text(label="Equivalence"),],
-    title="Circuit Transformer for Size Minimization",
+    title="Circuit Transformer for Size Minimization of Logic Circuits",
     description="""This is a demo to show how a [Circuit Transformer](https://openreview.net/forum?id=kpnW12Lm9p) 
-minimize the size of a logic circuit by next token prediction, while strictly preserving logical equivalence."""
+minimize the size of a logic circuit by next token prediction, while strictly preserving logical equivalence.
+[[GitHub Repo]](https://github.com/snowkylin/circuit-transformer)"""
 )
 
 if __name__ == "__main__":