Update app.py

app.py

@@ -2,12 +2,10 @@ import gradio as gr
 import pandas as pd
 import joblib
 
-# Load model and feature names once (for performance)
 model = joblib.load("ar_overdue_model.joblib")
 feature_names = joblib.load("ar_model_features.joblib")
 
 def predict(company_code, document_type, amount, due_in_days):
-    # Prepare input as DataFrame
     input_dict = {
         "company_code": company_code,
         "document_type": document_type,
@@ -16,12 +14,10 @@ def predict(company_code, document_type, amount, due_in_days):
     }
     input_df = pd.DataFrame([input_dict])
     input_df = pd.get_dummies(input_df)
-    # Ensure all model columns are present
     for col in feature_names:
         if col not in input_df.columns:
             input_df[col] = 0
     input_df = input_df[feature_names]
-    # Predict
     proba = model.predict_proba(input_df)[0,1]
     pred = model.predict(input_df)[0]
     return f"Overdue: {bool(pred)} (Probability: {proba:.2f})"
@@ -34,9 +30,8 @@ iface = gr.Interface(
         gr.Number(label="Amount"),
         gr.Number(label="Due In Days")
     ],
-    outputs="text",
-    title="SAP AR Overdue Predictor"
+    outputs="text"
 )
 
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch(ssr_mode=False)