Update app.py

app.py

@@ -14,13 +14,11 @@ from sklearn import metrics
 ###        interface setup        ###
 ### ----------------------------- ###
 
-col1, col2 = st.columns(2)
-
 with open('styles.css') as f:
   st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
   
-with open('info.md') as f:
-  col1.markdown(f.read())
+st.markdown('###Mental Health App')
+st.markdown('##A machine learning app by Isabel')
 
 
 ### ------------------------------ ###
@@ -92,23 +90,6 @@ model.fit(x_train, y_train.values.ravel())
 y_pred = model.predict(x_test)
 
 
-### -------------------------------- ###
-###        article generation        ###
-### -------------------------------- ###
-# borrow file reading function from reader.py
-
-# def get_feat():
-#   feats = [abs(x) for x in model.coef_[0]]
-#   max_val = max(feats)
-#   idx = feats.index(max_val)
-#   return data.columns[idx]
-  
-# acc = str(round(metrics.accuracy_score(y_test, y_pred) * 100, 1)) + '%**'
-# most_imp_feat = get_feat() + "**"
-# info = get_article(acc, most_imp_feat)
-
-
-
 ### ------------------------------- ###
 ###        interface creation       ###
 ### ------------------------------- ###
@@ -141,13 +122,16 @@ for colname in data.columns:
   # otherwise, just use a number input
   if colname in cat_value_dicts:
     radio_options = list(cat_value_dicts[colname].keys())
-    inputls.append(col2.selectbox(colname, radio_options))
+    inputls.append(st.selectbox(colname, radio_options))
   else:
     # add numerical input
-    inputls.append(col2.number_imput(colname))
+    inputls.append(st.number_imput(colname))
   
 # generate gradio interface
 if col2.button("Submit"):
   prediction = general_predictor(inputls)
   
-  col2.text(f"Your recommendation: {prediction}")
+  st.text(f"Your recommendation: {prediction}")
+  
+with open('info.md') as f:
+  st.markdown(f.read())