Update app.py

app.py

@@ -3,37 +3,13 @@ import numpy as np
 import joblib
 from tensorflow.keras.models import load_model
 import os
-import requests
 
-# URLs of the files in your Hugging Face repository
-scaler_url = 'https://huggingface.co/spaces/saba000farahani/Env_ContaminationLevel/raw/main/scaler_X.pkl'
-rf_model_url = 'https://huggingface.co/spaces/saba000farahani/Env_ContaminationLevel/raw/main/rf_model.pkl'
-mlp_model_url = 'https://huggingface.co/spaces/saba000farahani/Env_ContaminationLevel/raw/main/mlp_model.h5'
-meta_model_url = 'https://huggingface.co/spaces/saba000farahani/Env_ContaminationLevel/raw/main/meta_model.pkl'
-
-# Local paths to save the downloaded files
-scaler_path = 'scaler_X.pkl'
-rf_model_path = 'rf_model.pkl'
-mlp_model_path = 'mlp_model.h5'
-meta_model_path = 'meta_model.pkl'
-
-# Function to download a file from a URL
-def download_file(url, local_path):
-    with requests.get(url, stream=True) as r:
-        r.raise_for_status()
-        with open(local_path, 'wb') as f:
-            for chunk in r.iter_content(chunk_size=8192):
-                f.write(chunk)
-    print(f"Downloaded {local_path}")
-
-# Download the files
-try:
-    download_file(scaler_url, scaler_path)
-    download_file(rf_model_url, rf_model_path)
-    download_file(mlp_model_url, mlp_model_path)
-    download_file(meta_model_url, meta_model_path)
-except Exception as e:
-    print(f"Error downloading files: {e}")
+# Directory paths for the saved models
+script_dir = os.path.dirname(os.path.abspath(__file__))
+scaler_path = os.path.join(script_dir, 'toolkit', 'scaler_X.pkl')
+rf_model_path = os.path.join(script_dir, 'toolkit', 'rf_model.pkl')
+mlp_model_path = os.path.join(script_dir, 'toolkit', 'mlp_model.h5')
+meta_model_path = os.path.join(script_dir, 'toolkit', 'meta_model.pkl')
 
 # Load the scaler and models
 try: