Update app.py

app.py

@@ -1,7 +1,8 @@
-
 from flask import Flask, request, jsonify
 import joblib
 import pandas as pd
+import os
+from datetime import datetime
 
 # Load the model and preprocessor
 model = joblib.load('boston_housing_model.pkl')
@@ -9,25 +10,31 @@ preprocessor = joblib.load('preprocessor.pkl')
 
 app = Flask(__name__)
 
+@app.before_first_request
+def startup_message():
+    print(f"[{datetime.now()}] 🚀 Backend server is up and running on port {os.environ.get('PORT', 5000)}!")
+
 @app.route('/predict', methods=['POST'])
 def predict():
     try:
         data = request.json
+        print(f"[{datetime.now()}] 📩 Received prediction request: {data}")
+
         df = pd.DataFrame(data, index=[0])
 
-        # Preprocess the data using the loaded preprocessor
-        # Note: The preprocessor expects a DataFrame, so we transform it here.
+        # Preprocess the data
         processed_data = preprocessor.transform(df)
 
         # Make prediction
         prediction = model.predict(processed_data)
+        print(f"[{datetime.now()}] ✅ Prediction result: {prediction[0]}")
 
         return jsonify({'prediction': prediction[0]})
     except Exception as e:
+        print(f"[{datetime.now()}] ❌ Error: {str(e)}")
         return jsonify({'error': str(e)})
 
 if __name__ == '__main__':
-    import os
     port = int(os.environ.get("PORT", 5000))
+    print(f"[{datetime.now()}] Starting Flask server...")
     app.run(host='0.0.0.0', port=port)
-