Using the scheduler

app.py

@@ -24,7 +24,7 @@ log_folder = log_file.parent
 hf_token = os.environ.get('HF_TOKEN')
 print(hf_token)
 
-Scheduler will log every 2 API calls:
+# Scheduler will log every 2 API calls:
 scheduler = CommitScheduler(
     repo_id="machine-failure-logs",
     repo_type="dataset",
@@ -59,7 +59,7 @@ def predict_machine_failure(air_temperature, process_temperature, rotational_spe
     data_point = pd.DataFrame([sample])
     prediction = machine_failure_predictor.predict(data_point).tolist()
 
-    Each time we get a prediction we will determine if we should log it to a hugging_face dataset according to the schedule definition outside this function
+    # Each time we get a prediction we will determine if we should log it to a hugging_face dataset according to the schedule definition outside this function
     with scheduler.lock:
         with log_file.open("a") as f:
             f.write(json.dumps(