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app.py

@@ -14,32 +14,53 @@ app = Flask(__name__)
 socketio = SocketIO(app, cors_allowed_origins="*")
 
 # Load models
-try:
-    # Try loading from the current directory first
-    HEART_MODEL_PATH = os.path.join('heart', 'models', 'heart_model.joblib')
-    logger.info(f"Attempting to load heart model from {HEART_MODEL_PATH}")
-    heart_model = joblib.load(HEART_MODEL_PATH)
-    logger.info("Heart model loaded successfully")
-except:
-    try:
-        # If that fails, try loading from the absolute path
-        HEART_MODEL_PATH = os.path.join(os.path.dirname(__file__), 'heart', 'models', 'heart_model.joblib')
-        logger.info(f"Attempting to load heart model from {HEART_MODEL_PATH}")
-        heart_model = joblib.load(HEART_MODEL_PATH)
-        logger.info("Heart model loaded successfully")
-    except Exception as e:
-        logger.error(f"Could not load heart model: {str(e)}")
-        heart_model = None
+def load_models():
+    global heart_model, autoencoder
+    heart_model = None
+    autoencoder = None
+    
+    # Define possible model paths
+    model_paths = [
+        os.path.join('heart', 'models', 'heart_model.joblib'),
+        os.path.join(os.path.dirname(__file__), 'heart', 'models', 'heart_model.joblib'),
+        os.path.join('/app', 'heart', 'models', 'heart_model.joblib')
+    ]
+    
+    # Try loading heart model
+    for path in model_paths:
+        try:
+            logger.info(f"Attempting to load heart model from {path}")
+            heart_model = joblib.load(path)
+            logger.info("Heart model loaded successfully")
+            break
+        except Exception as e:
+            logger.warning(f"Failed to load heart model from {path}: {str(e)}")
+            continue
+    
+    # Try loading autoencoder
+    autoencoder_paths = [
+        os.path.join('models', 'best_model.pth'),
+        os.path.join(os.path.dirname(__file__), 'models', 'best_model.pth'),
+        os.path.join('/app', 'models', 'best_model.pth')
+    ]
+    
+    for path in autoencoder_paths:
+        try:
+            logger.info(f"Attempting to load autoencoder from {path}")
+            autoencoder = torch.load(path)
+            autoencoder.eval()
+            logger.info("Autoencoder model loaded successfully")
+            break
+        except Exception as e:
+            logger.warning(f"Failed to load autoencoder from {path}: {str(e)}")
+            continue
 
+# Load models on startup
+logger.info("Loading trained models...")
 try:
-    MODEL_DIR = os.path.join(os.path.dirname(__file__), 'models')
-    logger.info(f"Attempting to load autoencoder from {MODEL_DIR}")
-    autoencoder = torch.load(os.path.join(MODEL_DIR, 'best_model.pth'))
-    autoencoder.eval()
-    logger.info("Autoencoder model loaded successfully")
+    load_models()
 except Exception as e:
-    logger.error(f"Could not load autoencoder model: {str(e)}")
-    autoencoder = None
+    logger.error(f"Error loading models: {str(e)}")
 
 @app.route('/')
 def home():