app.py

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

# Initialize Flask app
app = Flask(__name__)

# Load the saved model
model = joblib.load("superkart_model.joblib")

@app.route("/")
def home():
    return "SuperKart Sales Forecast API is running successfully!"

@app.route("/v1/predict", methods=["POST"])
def predict_sales():
    try:
        data = request.get_json()
        # Convert incoming data to DataFrame
        input_data = pd.DataFrame([data])
        # Generate prediction
        prediction = model.predict(input_data)[0]
        return jsonify({"Sales": float(prediction)})
    except Exception as e:
        return jsonify({"error": str(e)})

if __name__ == '__main__':
    # In Docker/Hugging Face container, set host and port explicitly
    app.run()