app.py

# -----------------------------------------------------------
# SuperKart Backend API - Flask Application
# -----------------------------------------------------------

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

# -----------------------------------------------------------
# App setup
# -----------------------------------------------------------
app = Flask(__name__)
CORS(app)

MODEL_PATH = "model.joblib"
model = None


# -----------------------------------------------------------
# Load model
# -----------------------------------------------------------
def load_model():
    global model
    try:
        model = joblib.load(MODEL_PATH)
        print(f"✅ Model loaded successfully from: {MODEL_PATH}")
    except Exception as e:
        print(f"❌ Failed to load model: {e}")
        model = None


# -----------------------------------------------------------
# Home / Health endpoint
# -----------------------------------------------------------
@app.route("/", methods=["GET"])
def home():
    return jsonify({
        "status": "ok",
        "model_loaded": model is not None,
        "version": "v4.0.3",
        "message": "SuperKart backend ready — use POST /predict"
    })


# -----------------------------------------------------------
# Routes endpoint (debugging)
# -----------------------------------------------------------
@app.route("/routes", methods=["GET"])
def show_routes():
    """List all registered endpoints for debugging."""
    routes = [str(rule) for rule in app.url_map.iter_rules()]
    return jsonify({"available_routes": routes})


# -----------------------------------------------------------
# Prediction endpoint
# -----------------------------------------------------------
@app.route("/predict", methods=["POST"])
def predict():
    """Accepts JSON input and returns model predictions."""
    try:
        data = request.get_json(force=True)
        print("Received data:", data)

        # Convert JSON list of dicts -> DataFrame
        df = pd.DataFrame(data)

        # Run model inference
        preds = model.predict(df)

        return jsonify({
            "status": "ok",
            "predictions": preds.tolist(),
            "version": "v4.0.3"
        })
    except Exception as e:
        print("Prediction error:", e)
        return jsonify({"status": "error", "message": str(e)}), 500


# -----------------------------------------------------------
# Entry point
# -----------------------------------------------------------
if __name__ == "__main__":
    load_model()
    port = int(os.environ.get("PORT", 7860))
    print(f"🚀 Starting SuperKart backend on 0.0.0.0:{port}")
    app.run(host="0.0.0.0", port=port, debug=False)
if __name__ == "__main__":
    load_model()
    port = int(os.environ.get("PORT", 7860))
    print(f"🚀 Starting SuperKart backend on 0.0.0.0:{port}")
    app.run(host="0.0.0.0", port=port, debug=False)