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app.py

@@ -1,15 +1,4 @@
 
-from flask import Flask
-
-def create_app():
-    app = Flask(__name__)
-    # ... any other app configuration
-    @app.route("/v1/sales_batch", methods=["POST"])
-    def sales_batch():
-        return "Sales batch endpoint"
-    return app
-
-
 import numpy as np
 import joblib
 import pandas as pd
@@ -20,6 +9,7 @@ superkart_api = Flask("superkart_sales_api")
 
 # Load the trained model (must be in same folder as app.py)
 try:
+    # This assumes 'superkart_prediction.joblib' is in the same directory as app.py
     model = joblib.load("superkart_prediction.joblib")
     print("✅ Model loaded successfully.")
 except Exception as e:
@@ -82,7 +72,8 @@ def predict_sales():
         return jsonify({'error': f"Prediction failed: {str(e)}"}), 500
 
 # BATCH SALES PREDICTION
-@app.route("/v1/sales_batch", methods=["POST"])
+# Corrected decorator to use the `superkart_api` instance
+@superkart_api.route("/v1/sales_batch", methods=["POST"])
 def predict_sales_batch():
     try:
         file = request.files.get("file")
@@ -103,4 +94,5 @@ def predict_sales_batch():
 
 # Local testing
 if __name__ == '__main__':
+    # This will still use superkart_api for local runs
     superkart_api.run(debug=True, host='0.0.0.0', port=7860)