error check

app.py

@@ -22,10 +22,19 @@ def extract_features_in_parallel(urls):
 
 # Load the CatBoost model for inference
 def predict_with_catboost(features_df, model_path):
-    model = CatBoostClassifier()
-    model.load_model(model_path, format='cbm')  # Specify the format as 'cbm'
-    predictions = model.predict(features_df)
-    return predictions
+    try:
+        model = CatBoostClassifier()
+        # Try loading without format specification first
+        try:
+            model.load_model(model_path)
+        except:
+            # If that fails, try with explicit format
+            model.load_model(model_path, format='binary')
+        predictions = model.predict(features_df)
+        return predictions
+    except Exception as e:
+        print(f"Error loading model: {str(e)}")
+        raise
 
 # Flask App Setup
 app = Flask(__name__)
@@ -46,9 +55,22 @@ async def index():
             # Convert the features to DataFrame (in case you need to do further processing)
             features_df = pd.DataFrame([features])
             
-            # Perform prediction using the CatBoost model
-            model_path = (os.path.join(os.getcwd(),"catboost_model.bin"))
-            # model_path = "F:\\pyro guard\\model\\catboost_model.bin"  # Specify your CatBoost model path here
+            # Try multiple possible model locations
+            possible_paths = [
+                os.path.join(os.getcwd(), "catboost_model.bin"),
+                "/app/catboost_model.bin",  # Docker container path
+                "catboost_model.bin"
+            ]
+            
+            model_path = None
+            for path in possible_paths:
+                if os.path.exists(path):
+                    model_path = path
+                    break
+                    
+            if model_path is None:
+                raise FileNotFoundError("Model file not found in any expected location")
+                
             predictions = predict_with_catboost(features_df, model_path)
             
             # Determine if the URL is malicious or legitimate

test_model.py

@@ -0,0 +1,26 @@
+from catboost import CatBoostClassifier
+import os
+
+def test_model_loading():
+    possible_paths = [
+        os.path.join(os.getcwd(), "catboost_model.bin"),
+        "/app/catboost_model.bin",
+        "catboost_model.bin"
+    ]
+    
+    for path in possible_paths:
+        if os.path.exists(path):
+            print(f"Found model at: {path}")
+            model = CatBoostClassifier()
+            try:
+                model.load_model(path)
+                print(f"Successfully loaded model from {path}")
+                return True
+            except Exception as e:
+                print(f"Failed to load from {path}: {str(e)}")
+    
+    print("Model not found in any location")
+    return False
+
+if __name__ == "__main__":
+    test_model_loading()