shifted predict code

app.py

@@ -23,16 +23,16 @@ def predict(model, input_df):
 
 #input_dict = {"AGE": age, "GENDER_F": gender, "RACE_Asian":	,"RACE_Black": ,	"RACE_Coloured":,	"RACE_Other":,	"RACE_White":,	"DIABETES_CLASS_Type 1 diabetes":}
 
-input_dict = {"AGE": 70.0, "GENDER_F": 0.0, "RACE_Asian": 1.0, "RACE_Black": 0.0,	"RACE_Coloured": 0.0,	"RACE_Other": 0.0,	"RACE_White": 0.0,	"DIABETES_CLASS_Type 1 diabetes":0.0}
 
 
-input_df = pd.DataFrame([input_dict])
-
 
 
 
 # the parameters in this function, actually gets the inputs for the prediction 
 def predict_amputation(age, gender, race, diabetes_type):
+	input_dict = {"AGE": 70.0, "GENDER_F": 0.0, "RACE_Asian": 1.0, "RACE_Black": 0.0,	"RACE_Coloured": 0.0,	"RACE_Other": 0.0,	"RACE_White": 0.0,	"DIABETES_CLASS_Type 1 diabetes":0.0}
+    
+	input_df = pd.DataFrame([input_dict])
     return "ALLAH"+predict(model=model, input_df=input_df) # calls the predict function when the 'submit' button is clicked
 
 
@@ -40,11 +40,16 @@ title = "DIabetes-related Amputation Risk Calculator (DIARC)"
 
 description = "A diabetes-related amputation machine learning model trained on the diabetes dataset from the Inkosi Albert Luthuli Central Hospital (IALCH) in Durban, KwaZulu-Natal, South Africa."
 
+article = "<p style='text-align: center'>Copyright (C) 2021. All Rights Reserved.</p>"
+
+
+
 
 iface = gr.Interface(
 		fn=predict_amputation, 
 		title=title, 
 		description=description, 
+		article=article,
 		inputs=[gr.inputs.Slider(minimum=0,maximum=100, step=1, label="Age"), gr.inputs.Dropdown(["Female", "Male"], default="Male", label="Gender"), gr.inputs.Dropdown(["Asian", "Black", "Coloured", "White", "Other"], default="Asian", label="Race"), gr.inputs.Dropdown(["1", "2"], default="1", label="Diabetes Type")], 
 		outputs="text",
 		theme="darkhuggingface",