Update app.py

app.py

@@ -31,8 +31,14 @@ weight = st.number_input('Input your weight!', max_value=140.0, min_value=35.0,
 heart_rate = st.number_input('Input your heart rate!', max_value=130.0, min_value=60.0, step=20.0)
 body_temp = st.number_input('Input your body temperature!', max_value=45.0, min_value=35.0, step=1.0)
 
-def model_prediction(age, height, weight, duration, heart_rate, body_temp, gender, model):
+def model_prediction(age, height, weight, duration, heart_rate, body_temp, gender, model_input):
     with st.spinner('Model is being loaded..'):
+        if model_input == "Random Forest Regressor":
+            model = load_rfr()
+        elif model_input == "Linear Regressor":
+            model = load_lr()
+        else:
+            model == load_xgb()
         inputs = pd.DataFrame([{'Gender': gender, 'Age': age, 'Height': height, 'Weight': weight, 'Duration': duration, 'Heart_Rate': heart_rate, 'Body_Temp': body_temp}])
         predictions = model.predict(inputs)
         st.write("""# Prediction : """ , predictions)
@@ -50,13 +56,8 @@ with st.sidebar:
         gender = 1
 
     model_input = st.radio("model", ["Random Forest Regressor", "Linear Regressor", "XG Boost"], index=None)
-    if model_input == "Random Forest Regressor":
-        model = load_rfr()
-    elif model_input == "Linear Regressor":
-        model = load_lr()
-    else:
-        model_input == load_xgb()
+
 
 with st.container():
     if st.button("Calculate"):
-        model_prediction(age, height, weight, duration, heart_rate, body_temp, gender, model)
+        model_prediction(age, height, weight, duration, heart_rate, body_temp, gender, model_input)