Upload app.py

app.py

@@ -50,7 +50,7 @@ model_output = gr.Label(label="charges")
 # Define the predict function which will take features, convert to dataframe and make predictions using the saved model
 # the functions runs when 'Submit' is clicked or when a API request is made
 
-def predict_term_deposit(age, bmi, children, sex, smoker, region):
+def predict_insurance_charges(age, bmi, children, sex, smoker, region):
     
     sample = {
         'Age': age,
@@ -82,7 +82,7 @@ def predict_term_deposit(age, bmi, children, sex, smoker, region):
     return prediction[0]
 
 gr_interface = gr.Interface(
-    fn=predict_term_deposit,
+    fn=predict_insurance_charges,
     inputs=[age_input,
             bmi_input,
             children_input,