# Buggy code
def load_data(resource_name: Text, language: Optional[Text] = "en") -> "TrainingData":
    """Load training data from disk.

    Merges them if loaded from disk and multiple files are found."""
    from rasa.nlu.training_data import TrainingData

    files = utils.list_files(resource_name)
    data_sets = [_load(f, language) for f in files]
    data_sets = [ds for ds in data_sets if ds]
    if len(data_sets) == 0:
        training_data = TrainingData()
    elif len(data_sets) == 1:
        training_data = data_sets[0]
    else:
        training_data = data_sets[0].merge(*data_sets[1:])

    return training_data


# Traceback (FileNotFoundError)
? Export stories to (if file exists, this will append the stories)
? Export NLU data to (if file exists, this will merge learned data with previous training examples)
? Export domain file to (if file exists, this will be overwritten) domain.yml
2019-06-18 08:16:35 ERROR    rasa.core.training.interactive  - An exception occurred while recording messages.
Traceback (most recent call last):
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 1367, in record_messages
endpoint, sender_id, sender_ids, plot_file
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 885, in _predict_till_next_listen
action_name, policy, confidence, predictions, endpoint, sender_id
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 1024, in _validate_action
is_correct = await _ask_questions(question, sender_id, endpoint)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 312, in _ask_questions
should_retry = await _ask_if_quit(sender_id, endpoint)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 591, in _ask_if_quit
await _write_data_to_file(sender_id, endpoint)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 566, in _write_data_to_file
await _write_stories_to_file(story_path, events)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 764, in _write_stories_to_file
with open(export_story_path, append_write, encoding="utf-8") as f:
FileNotFoundError: [Errno 2] No such file or directory: ''
2019-06-18 08:16:35 ERROR    asyncio  - Task exception was never retrieved
future: <Task finished coro=<_serve_application.<locals>.run_interactive_io() done, defined at /Users/erohmensing/rasa/rasa/core/training/interactive.py:1409> exception=FileNotFoundError(2, 'No such file or directory')>
Traceback (most recent call last):
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 1416, in run_interactive_io
sender_id=uuid.uuid4().hex,
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 1367, in record_messages
endpoint, sender_id, sender_ids, plot_file
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 885, in _predict_till_next_listen
action_name, policy, confidence, predictions, endpoint, sender_id
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 1024, in _validate_action
is_correct = await _ask_questions(question, sender_id, endpoint)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 312, in _ask_questions
should_retry = await _ask_if_quit(sender_id, endpoint)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 591, in _ask_if_quit
await _write_data_to_file(sender_id, endpoint)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 566, in _write_data_to_file
await _write_stories_to_file(story_path, events)
File "/Users/erohmensing/rasa/rasa/core/training/interactive.py", line 764, in _write_stories_to_file
with open(export_story_path, append_write, encoding="utf-8") as f:
FileNotFoundError: [Errno 2] No such file or directory: ''

# Fixed code
def load_data(resource_name: Text, language: Optional[Text] = "en") -> "TrainingData":
    """Load training data from disk.

    Merges them if loaded from disk and multiple files are found."""
    from rasa.nlu.training_data import TrainingData

    if not os.path.exists(resource_name):
        raise ValueError("File '{}' does not exist.".format(resource_name))

    files = utils.list_files(resource_name)
    data_sets = [_load(f, language) for f in files]
    data_sets = [ds for ds in data_sets if ds]
    if len(data_sets) == 0:
        training_data = TrainingData()
    elif len(data_sets) == 1:
        training_data = data_sets[0]
    else:
        training_data = data_sets[0].merge(*data_sets[1:])

    return training_data