Converted numeric label to string

app.py

@@ -23,7 +23,7 @@ log_file = Path("logs/") / f"data_{uuid.uuid4()}.json"
 log_folder = log_file.parent
 
 scheduler = CommitScheduler(
-    repo_id="machine-failure-logs",
+    repo_id="machine-failure-mlops-logs",
     repo_type="dataset",
     folder_path=log_folder,
     path_in_repo="data",
@@ -42,7 +42,7 @@ type_input = gr.Dropdown(
     label='Type'
 )
 
-model_output = gr.Label(label="Machine failure")
+model_output = gr.Label(label="Machine Failure Expected?")
 
 # Define the predict function that runs when 'Submit' is clicked or when a API request is made
 def predict_machine_failure(air_temperature, process_temperature, rotational_speed, torque, tool_wear, type):
@@ -55,7 +55,12 @@ def predict_machine_failure(air_temperature, process_temperature, rotational_spe
         'Type': type
     }
     data_point = pd.DataFrame([sample])
-    prediction = machine_failure_predictor.predict(data_point).tolist()
+    prediction = machine_failure_predictor.predict(data_point).tolist()[0]
+    
+    if prediction == 1:
+        prediction_label = 'yes'
+    else:
+        prediction_label = 'no' 
 
     with scheduler.lock:
         with log_file.open("a") as f:
@@ -67,7 +72,7 @@ def predict_machine_failure(air_temperature, process_temperature, rotational_spe
                     'Torque [Nm]': torque,
                     'Tool wear [min]': tool_wear,
                     'Type': type,
-                    'prediction': prediction[0]
+                    'prediction': prediction_label
                 }
             ))
             f.write("\n")