from flask import Flask, request, jsonify
import numpy as np
import xgboost as xgb

app = Flask(__name__)

# Load model from JSON (instead of pickle)
model = xgb.Booster()
model.load_model("xgb_superkart_model.json")

@app.route("/", methods=["GET"])
def root():
    return "SuperKart Sales Forecasting API is running."


@app.route("/predict", methods=["POST"])
def predict():
    data = request.get_json(force=True)
    features = np.array(data["features"]).reshape(1, -1)
    dmatrix = xgb.DMatrix(features)
    prediction = model.predict(dmatrix)
    return jsonify({"prediction": float(prediction[0])})

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860)