Update app.py

app.py

@@ -5,10 +5,9 @@ from pytorch_tabnet.tab_model import TabNetClassifier
 
 # Load model, scaler, and encoder
 model = TabNetClassifier()
-model.load_model('tabnet_model.zip')
-
-scaler = joblib.load('D:/Dataset/IPIP-FFM-data-8Nov2018/scaler.save')
-encoder = joblib.load('D:/Dataset/IPIP-FFM-data-8Nov2018/encoder.save')
+model.load_model('tabnet_model.zip')  # Must be .zip file
+scaler = joblib.load('scaler.save')
+encoder = joblib.load('encoder.save')
 
 # Full form trait mapping
 trait_prefixes = {
@@ -21,11 +20,9 @@ trait_prefixes = {
 
 # Create full feature names with full form labels
 feature_labels = []
-feature_keys = []
-for trait, abbrev in trait_prefixes.items():
+for trait in trait_prefixes:
     for i in range(10):
         feature_labels.append(f"{trait} Q{i+1}")
-        feature_keys.append(f"{abbrev}{i+1}")
 
 # Inference function
 def predict_personality(*inputs):
@@ -46,4 +43,5 @@ demo = gr.Interface(
     title="Personality Type Classifier (Introvert vs. Extrovert)",
     description="Provide scores (1–5) for 50 questions from the IPIP-FFM questionnaire. The model will predict whether the person is an Introvert or an Extrovert."
 )
+
 demo.launch()