Update app.py

app.py

@@ -109,7 +109,7 @@ def predict_salary(job_title, experience_level, company_size, employment_type, c
 
         # Check if components loaded
         if model is None or scaler is None or feature_names is None or deployment_data is None:
-            return "Error: Model components could not be loaded.", ""
+            return "Error: Model components could not be loaded."
 
         # Engineer features
         input_features = engineer_features_simple(job_title, experience_level, company_size, employment_type, company_location, remote_ratio)
@@ -131,16 +131,14 @@ def predict_salary(job_title, experience_level, company_size, employment_type, c
         salary_min = int(predicted_salary - margin_of_error)
         salary_max = int(predicted_salary + margin_of_error)
 
-        confidence_score = 0.85 # Example confidence score
-
         result_range = f"Estimated Salary Range: ${salary_min:,} - ${salary_max:,}"
-        result_confidence = f"Confidence Score: {confidence_score:.0%}"
 
-        return result_range, result_confidence
+        return result_range
+
 
     except Exception as e:
         print(f"Prediction Error: {e}")
-        return "An error occurred during prediction. Please check inputs.", ""
+        return "An error occurred during prediction. Please check inputs."
 
 # Pre-defined choices for dropdowns - Limiting to 5 core ML/AI roles + 'Other_Roles'
 # These should align with the job_title_category feature engineering
@@ -227,11 +225,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css=CUSTOM_CSS) as demo:
                     scale=2
                 )
 
-            explanation_output = gr.Textbox(
-                label="Prediction Confidence Score",
-                value="Confidence score will appear here after prediction",
-            )
-
             gr.Markdown("## 🎯 What-If Analysis")
             gr.Markdown("Try changing the parameters above to see how they affect salary predictions!")
 
@@ -239,7 +232,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=CUSTOM_CSS) as demo:
     predict_btn.click(
         fn=predict_salary,
         inputs=[job_title, experience_level, company_size, employment_type, company_location, remote_ratio],
-        outputs=[salary_output, explanation_output]
+        outputs=[salary_output]
     )
 
     gr.Markdown("---")
@@ -251,4 +244,4 @@ with gr.Blocks(theme=gr.themes.Soft(), css=CUSTOM_CSS) as demo:
 
 # Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()