Update app.py

app.py

@@ -15,29 +15,29 @@ warnings.filterwarnings('ignore', category=UserWarning, module='sklearn')
 # Logging setup
 logging.basicConfig(level=logging.INFO)
 
-# Model URLs from env
-DIABETES_MODEL_URL = os.getenv("DIABETES_MODEL_URL")
-SCALER_URL = os.getenv("SCALER_URL")
-MULTI_MODEL_URL = os.getenv("MULTI_MODEL_URL")
+# Load URLs from environment
+MODEL_URLS = {
+    "DIABETES_MODEL": os.getenv("DIABETES_MODEL_URL"),
+    "SCALER": os.getenv("SCALER_URL"),
+    "MULTI_MODEL": os.getenv("MULTI_MODEL_URL"),
+}
 
-# Model ZIP names
+# Model ZIP filenames
 MODEL_PATHS = {
     "DIABETES_MODEL": "finaliseddiabetes_model.zip",
     "SCALER": "finalisedscaler.zip",
     "MULTI_MODEL": "nodiabetes.zip",
 }
 
-# Extracted joblib names
+# Extracted model file names
 EXTRACTED_MODELS = {
     "DIABETES_MODEL": "finaliseddiabetes_model.joblib",
     "SCALER": "finalisedscaler.joblib",
     "MULTI_MODEL": "nodiabetes.joblib",
 }
 
-# Use writeable temp dir
 TMP_DIR = "/tmp"
 
-# Flask app init
 app = Flask(__name__)
 CORS(app, supports_credentials=True)
 
@@ -103,11 +103,18 @@ def initialize_models():
     models = {}
     for model_key, zip_filename in MODEL_PATHS.items():
         extracted_filename = EXTRACTED_MODELS[model_key]
+        url = MODEL_URLS.get(model_key)
+
         zip_path = os.path.join(TMP_DIR, zip_filename)
         if not os.path.exists(zip_path):
-            download_model(globals()[f"{model_key}_URL"], zip_filename)
-        extract_if_needed(zip_filename, extracted_filename)
+            if not download_model(url, zip_filename):
+                continue
+
+        if not extract_if_needed(zip_filename, extracted_filename):
+            continue
+
         models[model_key] = load_model(extracted_filename)
+
     return models
 
 models = initialize_models()
@@ -183,7 +190,7 @@ def predict_health():
 
         gender = validate_gender(data.get('gender'))
         if gender is None:
-            return jsonify({'status': 'error', 'error': 'Invalid gender value. Must be "male" or "female"'}), 400
+            return jsonify({'status': 'error', 'error': 'Invalid gender value. Must be \"male\" or \"female\"'}), 400
 
         systolic, diastolic = validate_blood_pressure(data.get('systolic'), data.get('diastolic'))
         if systolic is None or diastolic is None: