🚀 Fix: Ensure backend starts and runs Flask app

app.py

@@ -1,8 +1,9 @@
+# Superkart Sales Forecasting Flask API 
+
 from flask import Flask, request, jsonify
 import pandas as pd
 import numpy as np
 import joblib
-import os
 import traceback
 
 app = Flask(__name__)
@@ -13,7 +14,7 @@ try:
     model = joblib.load(MODEL_PATH)
     print("✅ Model loaded successfully.")
 except Exception as e:
-    print("❌ Failed to load model from:", MODEL_PATH)
+    print("❌ Model load error:", e)
     traceback.print_exc()
 
 @app.route("/", methods=["GET"])
@@ -28,18 +29,13 @@ def predict_single():
 
         df["Store_Age"] = 2025 - df["Store_Establishment_Year"]
         df["Price_per_kg"] = df["Product_MRP"] / df["Product_Weight"]
-        df["MRP_Band"] = pd.cut(df["Product_MRP"], bins=[0, 100, 200, float("inf")], labels=["Low", "Mid", "High"])
+        df["MRP_Band"] = pd.cut(
+            df["Product_MRP"], bins=[0, 100, 200, float("inf")], labels=["Low", "Mid", "High"]
+        )
 
         pred_log = model.predict(df)[0]
         pred = np.expm1(pred_log)
-        return jsonify({"Predicted_Sales": round(float(pred), 2)}), 200
+        return jsonify({"Predicted_Sales": round(float(pred), 2)})
 
     except Exception as e:
         return jsonify({"error": str(e)}), 500
-        # === Entrypoint for Docker / HF Space ===
-if __name__ == "__main__":
-    port = int(os.environ.get("PORT", 7860))
-    app.run(host="0.0.0.0", port=port)
-    
-    print("🚀 Flask app has started on port", port)
-