from autocoder import autocoder
data = {
    "project_name": "random_midi_generator", # name of the project
    "goal": "Generate a 2 minute midi track with multiple instruments. The track must contain at least 500 notes, but can contain any number of notes. The track should be polyphonic and have multiple simultaneous instruments", # goal of the project
    "project_dir": "random_midi_generator", # name of the project directory
    "log_level": "normal", # normal, debug, or quiet
    "step": False, # whether to step through the loop manually, False by default
    "model": "gpt-3.5-turbo", # default
    "api_key": <your openai api key> # can also be passed in via env var OPENAI_API_KEY
}

autocoder(project_data)

# Initial context object
context = {
    epoch,
    name,
    goal,
    project_dir,
    project_path
}

# Added by reasoning step
context = {
    reasoning,
    file_count,
    filetree,
    filetree_formatted,
    python_files,
    main_success,
    main_error,
    backup,
    project_code: [{
        rel_path,
        file_path,
        content,
        validation_success,
        validation_error,
        test_success,
        test_error,
    }],
    project_code_formatted
}

# Action step context
context = {
    name, # project name
    goal, # project goal
    project_dir,
    project_path,
    file_count,
    filetree,
    filetree_formatted, # formatted for prompt template
    python_files,
    main_success, # included in project_code_formatted
    main_error, # included in project_code_formatted
    backup,
    available_actions, # list of available actions
    available_action_names, # list of just the action names
    project_code_formatted, # formatted for prompt template
    action_name,
    reasoning, # formatted for prompt template
    project_code: [{
        rel_path,
        file_path,
        content,
        validation_success,
        validation_error,
        test_success,
        test_error,
    }]
}