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app.py

@@ -51,11 +51,9 @@ def predict_sales():
     # Make prediction (get sales)
     predicted_sales = model.predict(input_data)[0]
 
-    # # Convert predicted_price to Python float
-    # predicted_sales = round(float(predicted_sales), 2)
-    # # The conversion above is needed as we convert the model prediction (log price) to actual price using np.exp, which returns predictions as NumPy float32 values.
-    # # When we send this value directly within a JSON response, Flask's jsonify function encounters a datatype error
-
+    # Convert to Python float and round
+    predicted_sales = round(float(predicted_sales), 2)
+    
     # Return the actual price
     return jsonify({'Predicted Sales Forecast (in dollars)': predicted_sales})