Update app.py

app.py

@@ -1,16 +1,19 @@
 import streamlit as st
-import joblib
 import numpy as np
+import pandas as pd
+from sklearn.preprocessing import StandardScaler
+from sklearn.decomposition import PCA
+import pickle
 
 # Load the trained model, scaler, and PCA
-regressor = joblib.load('slump_regressor.pkl')
-scaler = joblib.load('scaler.pkl')
+with open('slump_regressor.pkl', 'rb') as f:
+    regressor = pickle.load(f)
+with open('scaler.pkl', 'rb') as f:
+    scaler = pickle.load(f)
+with open('pca.pkl', 'rb') as f:
+    pca = pickle.load(f)
 
 def preprocess_data(X):
-    # Load the trained scaler and PCA
-    scaler = joblib.load('scaler.pkl')
-    pca = joblib.load('pca.pkl')
-
     # Check if the input has 8 features
     if X.shape[1] != 8:
         raise ValueError("Input data should have 8 features.")