Update app.py

app.py

@@ -21,16 +21,16 @@ insurance_charge_predictor = joblib.load('model.joblib')
 
 # # Prepare the logging functionality
 
-# log_file = Path("logs/") / f"data_{uuid.uuid4()}.json"
-# log_folder = log_file.parent
-
-# scheduler = CommitScheduler(
-#     repo_id="insurance-charge-logs",
-#     repo_type="dataset",
-#     folder_path=log_folder,
-#     path_in_repo="data",
-#     every=2
-# )
+log_file = Path("logs/") / f"data_{uuid.uuid4()}.json"
+log_folder = log_file.parent
+
+scheduler = CommitScheduler(
+    repo_id="insurance-charge-logs",
+    repo_type="dataset",
+    folder_path=log_folder,
+    path_in_repo="data",
+    every=2
+)
 
 # Define the predict function that runs when 'Submit' is clicked or when a API request is made
 def predict_insurance_charge(age, bmi, children,sex, smoker, region):
@@ -50,20 +50,20 @@ def predict_insurance_charge(age, bmi, children,sex, smoker, region):
     # While writing to the log file, ensure that the commit scheduler is locked to avoid parallel
     # access
     
-    # with scheduler.lock:
-    #     with log_file.open("a") as f:
-    #         f.write(json.dumps(
-    #             {
-    #                 'age': age,
-    #                 'bmi': bmi,
-    #                 'children': children,
-    #                 'sex': sex,
-    #                 'smoker': smoker,
-    #                 'region': region,
-    #                 'prediction': prediction[0]
-    #             }
-    #         ))
-    #         f.write("\n")
+    with scheduler.lock:
+        with log_file.open("a") as f:
+            f.write(json.dumps(
+                {
+                    'age': age,
+                    'bmi': bmi,
+                    'children': children,
+                    'sex': sex,
+                    'smoker': smoker,
+                    'region': region,
+                    'prediction': prediction[0]
+                }
+            ))
+            f.write("\n")
             
     return round(prediction[0],2)