Update app.py

app.py

@@ -10,6 +10,10 @@ import sklearn
 import gradio as gr
 import numpy as np
 
+from io import BytesIO
+import pickle
+import requests
+
 ex_data = pd.read_csv('https://raw.githubusercontent.com/fmegahed/tavr_paper/main/data/example_data2.csv')
 ex_data = ex_data.to_numpy()
 ex_data = ex_data.tolist()
@@ -26,7 +30,9 @@ def predict(age, female, race, elective, aweekend, zipinc_qrtl, hosp_region, hos
             pulmonary_circulation_disorder, smoker, valvular_disease, weight_loss,
             endovascular_tavr, transapical_tavr):
   
-  model = load_model('https://github.com/fmegahed/tavr_paper/blob/main/data/final_model.pkl?raw=true')
+  mLink = 'https://github.com/fmegahed/tavr_paper/blob/main/data/final_model.pkl?raw=true'
+  mfile = BytesIO(requests.get(mLink).content)
+  model = load_model(mfile)
 
   df = pd.DataFrame.from_dict({
       'age': [age], 'female': [female], 'race': [race], 'elective': elective,