Update app.py

app.py

@@ -102,15 +102,15 @@ y_pred = model.predict(x_test)
 
 
 # predictor for generic number of features
-def general_predictor(*args):
+def general_predictor(input_list):
   features = []
 
   # transform categorical input
-  for colname, arg in zip(data.columns, args):
+  for colname, input in zip(data.columns, input_list):
     if (colname in cat_value_dicts):
-      features.append(cat_value_dicts[colname][arg])
+      features.append(cat_value_dicts[colname][input])
     else:
-      features.append(arg)
+      features.append(input)
 
   # predict single datapoint
   new_input = [features]
@@ -135,7 +135,6 @@ for colname in data.columns:
   
 # generate gradio interface
 if st.button("Submit"):
-  x = pd.DataFrame([inputls])
-  prediction = model.predict(x)[0]
+  prediction = general_predictor(inputls)
   
   st.text(f"This instance is a {prediction}")