Update app.py

app.py

@@ -34,7 +34,7 @@ type_input = gr.Dropdown(['Natural', 'Lab Grown'], label="Type")
 hf_token = os.environ["HF_TOKEN"]
 hf_writer = gr.HuggingFaceDatasetSaver(hf_token, "diamond-price-predictor-logs")
 
-model_output = gr.Label(label="Predicted Price")
+model_output = gr.Label(label="Predicted Price (USD)")
 
 def predict_price(carat, shape, cut, color, clarity, report, type):
     sample = {
@@ -55,7 +55,7 @@ demo = gr.Interface(
     inputs=[carat_input, shape_input, cut_input, color_input, 
             clarity_input, report_input, type_input],
     outputs=model_output,
-    theme=gr.themes.Soft(),
+    theme=gr.themes.Glass(),
     title="Diamond Price Predictor",
     description="This API allows you to predict the price of a diamond given its attributes",
     allow_flagging="auto",