dataset_adapters/952b489de97f366fb44523b27fb3f0069050635fc6ada37e63997201324b3c41.py

def transform_data(data):
    conversations = []

    # Check for system message and prepend if present
    if data.get('system'):
        conversations.append({'from': 'system', 'value': data['system']})

    # Determine the correct order of human and gpt messages
    human_msg = ''
    if 'instruction' in data:
        human_msg += data['instruction']
    if 'input' in data and data['input']:  # Check if input exists and is not empty
        human_msg += (' ' if human_msg else '') + data['input']

    if human_msg:  # Add the human message if it's not empty
        conversations.append({'from': 'human', 'value': human_msg})

    if 'response' in data:
        conversations.append({'from': 'gpt', 'value': data['response']})

    # Return the transformed data without the schema
    return {'conversations': conversations}