Update app.py

app.py

@@ -1,17 +1,11 @@
 import gradio as gr
-import pickle
+import joblib
 
-# Load all models
-with open("knn_model.pkl", "rb") as f:
-    knn_model = pickle.load(f)
+# Load models using joblib
+knn_model = joblib.load("knn_model.joblib")
+rf_model = joblib.load("rf_model.joblib")
+svm_model = joblib.load("svm_model.joblib")
 
-with open("rf_model.pkl", "rb") as f:
-    rf_model = pickle.load(f)
-
-with open("svm_model.pkl", "rb") as f:
-    svm_model = pickle.load(f)
-
-# Map model name to actual model
 model_map = {
     "KNN": knn_model,
     "Random Forest": rf_model,
@@ -23,7 +17,6 @@ def predict(model_name, sex, pregnant, on_thyroxine, TT4, T3, T4U, FTI, TSH):
     try:
         model = model_map[model_name]
 
-        # Ensure inputs are correctly typed
         sex = int(sex)
         pregnant = int(pregnant)
         on_thyroxine = int(on_thyroxine)