Update app.py

app.py

@@ -4,35 +4,45 @@ import joblib
 import pandas as pd
 import os
 
-# Load the model and preprocessor
-model = joblib.load('boston_housing_model.pkl')
-preprocessor = joblib.load('preprocessor.pkl')
-
 app = Flask(__name__)
-CORS(app)  # ✅ Enable CORS for all routes
+CORS(app)  # Enable CORS for all routes
+
+model = None
+preprocessor = None
 
-# Health check route
 @app.route('/health', methods=['GET'])
-def health_check():
+def health():
     return jsonify({"status": "ok", "message": "Backend is running"}), 200
 
-# Prediction route
+def load_model():
+    global model, preprocessor
+    if model is None or preprocessor is None:
+        print("📦 Loading model and preprocessor...")
+        model = joblib.load('boston_housing_model.pkl')
+        preprocessor = joblib.load('preprocessor.pkl')
+        print("✅ Model and preprocessor loaded successfully.")
+
 @app.route('/predict', methods=['POST'])
 def predict():
     try:
+        load_model()  # Load model only when needed
+
         data = request.json
-        app.logger.info(f"📩 Received payload: {data}")
+        if not data:
+            return jsonify({'error': 'No input data provided'}), 400
 
         df = pd.DataFrame(data, index=[0])
         processed_data = preprocessor.transform(df)
         prediction = model.predict(processed_data)
 
-        app.logger.info(f"✅ Prediction result: {prediction[0]}")
-        return jsonify({'prediction': prediction[0]})
+        print(f"📨 Received payload: {data}")
+        print(f"🔮 Prediction: {prediction[0]}")
+
+        return jsonify({'prediction': float(prediction[0])})
     except Exception as e:
-        app.logger.error(f"❌ Error: {e}")
-        return jsonify({'error': str(e)})
+        return jsonify({'error': str(e)}), 500
 
 if __name__ == '__main__':
     port = int(os.environ.get("PORT", 5000))
+    print(f"🚀 Starting backend server on port {port}")
     app.run(host='0.0.0.0', port=port)