Update app.py

app.py

@@ -1,100 +1,156 @@
 
+import pandas as pd 
 import gradio as gr 
-
 import pickle 
 
- 
 
 # Load the XGBoost model from disk 
 
 loaded_model = pickle.load(open("xgb_h.pkl", 'rb')) 
 
  
-
 # Function to predict intent to stay 
-
 def predict_intent_to_stay(Engagement, WorkEnvironment, UpperLevelManagement, RewardsBenefits, EmployeeWellBeing, Workload, LearningDevelopment): 
 
+ 
 # Create input DataFrame 
-
 input_data = pd.DataFrame({ 
 
 'Engagement': [Engagement], 
 
+ 
+
 'WorkEnvironment': [WorkEnvironment], 
 
+ 
+
 'UpperLevelManagement': [UpperLevelManagement], 
 
+ 
+
 'RewardsBenefits': [RewardsBenefits], 
 
+ 
+
 'EmployeeWellBeing': [EmployeeWellBeing], 
 
+ 
+
 'Workload': [Workload], 
 
+ 
+
 'LearningDevelopment': [LearningDevelopment] 
 
+ 
+
 }) 
 
  
 
+ 
+
+ 
+
 # Perform prediction using the loaded model 
 
 prediction = loaded_model.predict(input_data)[0] 
 
- 
-
 return {"Leave": prediction, "Stay": 1 - prediction} 
 
- 
 
 # Create sliders for user input 
 
+
 engagement_slider = gr.Slider(minimum=1, maximum=5, value=3, label="Engagement") 
 
+ 
+
 work_environment_slider = gr.Slider(minimum=1, maximum=5, value=3, label="Work Environment") 
 
+ 
+
 upper_level_management_slider = gr.Slider(minimum=1, maximum=5, value=3, label="Upper Level Management") 
 
+ 
+
 rewards_benefits_slider = gr.Slider(minimum=1, maximum=5, value=3, label="Rewards Benefits") 
 
+ 
+
 employee_wellbeing_slider = gr.Slider(minimum=1, maximum=5, value=3, label="Employee Well-Being") 
 
+ 
+
 workload_slider = gr.Slider(minimum=1, maximum=5, value=3, label="Workload") 
 
+ 
+
 learning_development_slider = gr.Slider(minimum=1, maximum=5, value=3, label="Learning & Development") 
 
  
 
-# Create the interface 
+ 
 
+ 
+
+# Create the interface 
 interface = gr.Interface( 
 
+ 
+
 fn=predict_intent_to_stay, 
 
+ 
+
 inputs=[ 
 
+ 
+
 engagement_slider, 
 
+ 
+
 work_environment_slider, 
 
+ 
+
 upper_level_management_slider, 
 
+ 
+
 rewards_benefits_slider, 
 
+ 
+
 employee_wellbeing_slider, 
 
+ 
+
 workload_slider, 
 
+ 
+
 learning_development_slider 
 
+ 
+
 ], 
 
+ 
+
 outputs="text" 
 
+ 
+
 ) 
 
  
 
+ 
+
+ 
+
 # Launch the interface 
 
 interface.launch()