app.py

from flask import Flask, request, jsonify
import joblib
import numpy as np
import pandas as pd

# Initialize Flask app
app = Flask(__name__)

# Load the trained model (serialized earlier)
model = joblib.load("final_gradient_boosting_model.pkl")   # update filename if different

@app.route('/')
def home():
    return "SuperKart ML Model API is running 🚀"

# ----------------- Prediction Endpoint -----------------
@app.route('/predict', methods=['POST'])
def predict():
    try:
        # Get JSON data from request
        data = request.get_json(force=True)

        # Convert to DataFrame (ensures compatibility with preprocessing pipeline)
        df = pd.DataFrame([data])

        # Predict
        prediction = model.predict(df)

        # Return response
        return jsonify({
            "input": data,
            "prediction": float(prediction[0])
        })

    except Exception as e:
        return jsonify({"error": str(e)}), 400


if __name__ == "__main__":
    app.run(debug=True)