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app.py

@@ -47,7 +47,7 @@ def predict_sales():
     input_data = pd.DataFrame([sample])
 
     # Make prediction (get log_sales)
-    predictions = model.predict(input_data)[0]
+    predictions = np.log(model.predict(input_data)[0])
 
     # Round predictions
     predicted_sales = round(float(predictions), 2)
@@ -85,7 +85,7 @@ def sales_price_batch():
         # input_data_transformed = preprocessor.transform(input_data_batch)
         # predictions = model.predict(input_data_transformed)
 
-        predictions = model.predict(input_data_batch)  # Assuming already preprocessed or numeric
+        predictions = np.log(model.predict(input_data_batch))  # Assuming already preprocessed or numeric
 
         # Round predictions
         predicted_sales = [round(float(x), 2) for x in predictions]

sales_prediction_model_v1_0.joblib

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f73bfed3c2961bf373f589e120f7ed1696151a0db1f5b165774586ebeaa28416
-size 3121176
+oid sha256:c80f31f23cac2e4218afe9f62e34faf4fb53aa769225321333aa414ffe8fb055
+size 48300698