t

app.py

@@ -21,7 +21,7 @@ from sklearn.preprocessing import OneHotEncoder
 # Adapted from https://www.geeksforgeeks.org/predict-tinder-matches-with-machine-learning/
 # TODO: Implement MBTI features
 
-def predict(name, body_profile_type):
+def predict_match(name, body_profile_type):
     user_df = {}
 
     # Get user input for numerical columns
@@ -304,5 +304,5 @@ def recommendOne(user_df, num_recommendations=1):
 
 # Setup complete!
 
-iface = gr.Interface(fn=predict, inputs=["text", "text"], outputs="text")
+iface = gr.Interface(fn=predict_match, inputs=["text", "text"], outputs="text")
 iface.launch()