Update app.py

app.py

@@ -13,13 +13,15 @@ def predict_corrected_calcium(total_calcium, total_protein, albumin):
     predicted_value = model.predict([[total_calcium, atr]])[0]
     
     # Return the result string
-    return f"The Actual Calcium value with Correction is {predicted_value:.2f}. The model is a RDF Regression Model with a MSE of 0.06 and R-squared of 0.931."
+    return f"{predicted_value:.2f}. The model is a RDF Regression Model with a MSE of 0.06 and R-squared of 0.931."
 
 # Define the Gradio interface
 interface = gr.Interface(fn=predict_corrected_calcium, 
                          inputs=[gr.inputs.Number(label="Total Calcium in mg/dL"),
                                  gr.inputs.Number(label="Total Protein in g/dL"),
                                  gr.inputs.Number(label="Albumin in g/dL")],
-                         outputs=gr.outputs.Textbox())
+                         outputs=gr.outputs.Textbox(label="Corrected Calcium in mg/dL")
+                         title="RandomForestRegressor assisted Calcium Correction (RaCC)")
+)
 
 interface.launch()