Update app.py

app.py

@@ -20,14 +20,14 @@ model_dir_white = model_white.download()
 model_white = joblib.load(model_dir_white + "/wine_white_model.pkl")
 print("White Model downloaded")
 
-def wine(type, alcohol, chlorides, density, volatil_acidity,fixed_acidity, citric_acid,total_sulfur_dioxide):
+def wine(category, alcohol, chlorides, density, volatil_acidity,fixed_acidity, citric_acid,total_sulfur_dioxide):
     print("Calling function")
     df = pd.DataFrame([[alcohol, chlorides, density, volatil_acidity,fixed_acidity, citric_acid,total_sulfur_dioxide]], 
                       columns=['alcohol','chlorides','density','volatil_acidity','fixed_acidity','citric_acid','total_sulfur_dioxide'])
     print("Predicting")
     print(df)
     
-    if type == 0:
+    if category == "red":
          res = model_red.predict(df) 
          print(res)
          wine_url = "https://raw.githubusercontent.com/Anniyuku/wine_quality/main/" + res[0] + ".png"
@@ -45,7 +45,7 @@ demo = gr.Interface(
     description="Experiment with type, alcohol, chlorides, density, volatil_acidity, fixed_acidity, citric_acid, total_sulfur_dioxide to predict which flower it is.",
     allow_flagging="never",
     inputs=[
-        gr.inputs.Radio(choices=[0,1], label='Type'),
+        gr.inputs.Radio(choices=["white","red"], label='category'),
         gr.inputs.Number(default=9.00, label="alcohol"),
         gr.inputs.Number(default=0.60, label="chlorides"),
         gr.inputs.Number(default=1.00, label="density"),