Update app.py

app.py

@@ -55,8 +55,7 @@ def create_prediction_interface(model, scaler, features_mapping, data):
         input_values = pd.DataFrame([args], columns=nasa_features)
         input_values_scaled = scaler.transform(input_values)
         prediction = model.predict(input_values_scaled)
-        # Format the prediction as USD with two decimal places
-        return f"${round(prediction[0], 2):.2f}"
+        return f"${round(prediction[0], 2)}"  # Format the prediction with a dollar sign
 
     with gr.Blocks(theme=gr.themes.Default()) as demo:
         gr.Markdown("### Stock Price Prediction")
@@ -82,9 +81,8 @@ def create_prediction_interface(model, scaler, features_mapping, data):
                 predict_btn = gr.Button("Predict", variant="primary")
             
             with gr.Column(scale=1):
-                gr.Markdown("#### Predicted Result")
-                # Use TextOutput to display the formatted USD value
-                output = gr.TextOutput(label="Predicted Close_^FTSE", value="0.00", interactive=False)
+                gr.Markdown("#### Predicted Result", elem_id="result-header")
+                output = gr.Markdown(label="Predicted Close_^FTSE", interactive=False, value="$0.00")  # Change to Markdown and add $
                 predict_btn.click(fn=predict_func, inputs=inputs, outputs=output)
     
     return demo