app.py

from flask import Flask, request, jsonify
from flask_cors import CORS
import joblib
import pandas as pd
import os

app = Flask(__name__)
CORS(app)  # Enable CORS for all routes

model = None
preprocessor = None

@app.route('/health', methods=['GET'])
def health():
    return jsonify({"status": "ok", "message": "Backend is running"}), 200

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
        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)

        print(f"📨 Received payload: {data}")
        print(f"🔮 Prediction: {prediction[0]}")

        return jsonify({'prediction': float(prediction[0])})
    except Exception as 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)