Update app.py

app.py

@@ -131,7 +131,9 @@ transapical_tavr = gr.inputs.Radio(choices=["No", "Yes"], label = 'Transapical T
 
 
 # Defining and launching the interface
-gr.Interface(predict, [age, female, race, elective, aweekend, zipinc_qrtl, hosp_region, hosp_division, hosp_locteach,
+iface = gr.Interface(
+    fn = predict, 
+    inputs = [age, female, race, elective, aweekend, zipinc_qrtl, hosp_region, hosp_division, hosp_locteach,
             hosp_bedsize, h_contrl, pay, anemia, atrial_fibrillation, 
             cancer, cardiac_arrhythmias, carotid_artery_disease, 
             chronic_kidney_disease, chronic_pulmonary_disease, coagulopathy,
@@ -141,8 +143,10 @@ gr.Interface(predict, [age, female, race, elective, aweekend, zipinc_qrtl, hosp_
             prior_cabg, prior_icd, prior_mi, prior_pci, prior_ppm, prior_tia_stroke,
             pulmonary_circulation_disorder, smoker, valvular_disease, weight_loss,
             endovascular_tavr, transapical_tavr], 
-            'text',
-            live=True,
-            title = "Predicting In-Hospital Mortality After TAVR Using Preoperative Variables and Penalized Logistic Regression",
-            description = "The app below utilizes the finalized logistic regression model with an l2 penalty based on the manuscript by Alhwiti et al. The manuscript will be submitted to JACC: Cardiovascular Interventions. The data used for model building is all TAVR procedures between 2012 and 2019 as reported in the HCUP NIS database. <br><br> The purpose of the app is to provide evidence-based clinical support for interventional cardiology. </b>.",
-            css = 'https://bootswatch.com/5/journal/bootstrap.css').launch(debug = False);
+    output = 'text',
+    live=True,
+    title = "Predicting In-Hospital Mortality After TAVR Using Preoperative Variables and Penalized Logistic Regression",
+    description = "The app below utilizes the finalized logistic regression model with an l2 penalty based on the manuscript by Alhwiti et al. The manuscript will be submitted to JACC: Cardiovascular Interventions. The data used for model building is all TAVR procedures between 2012 and 2019 as reported in the HCUP NIS database. <br><br> The purpose of the app is to provide evidence-based clinical support for interventional cardiology. </b>.",
+    css = 'https://bootswatch.com/5/journal/bootstrap.css')
+
+iface.launch()