Update app.py

app.py

@@ -1,47 +1,38 @@
 from flask import Flask, request, jsonify
+from flask_cors import CORS
 import joblib
 import pandas as pd
 import os
-from datetime import datetime
 
 # 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
 
+# Health check route
 @app.route('/health', methods=['GET'])
 def health_check():
     return jsonify({"status": "ok", "message": "Backend is running"}), 200
 
+# Prediction route
 @app.route('/predict', methods=['POST'])
 def predict():
     try:
-        steps = []
-        steps.append("✅ Request received")
-
         data = request.json
-        print(f"[{datetime.now()}] 📩 Received prediction request: {data}")
-        steps.append("📦 Data loaded into DataFrame")
+        app.logger.info(f"📩 Received payload: {data}")
 
         df = pd.DataFrame(data, index=[0])
         processed_data = preprocessor.transform(df)
-        steps.append("🔄 Data preprocessed")
-
         prediction = model.predict(processed_data)
-        steps.append("📊 Prediction complete")
-
-        print(f"[{datetime.now()}] ✅ Prediction result: {prediction[0]}")
 
-        return jsonify({
-            'prediction': prediction[0],
-            'steps': steps
-        })
+        app.logger.info(f"✅ 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)}), 500
+        app.logger.error(f"❌ Error: {e}")
+        return jsonify({'error': str(e)})
 
 if __name__ == '__main__':
     port = int(os.environ.get("PORT", 5000))
-    print(f"[{datetime.now()}] 🚀 Backend server starting on port {port}...")
     app.run(host='0.0.0.0', port=port)