# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md). # All rights reserved. # # SPDX-License-Identifier: BSD-3-Clause import enum import importlib import os from collections.abc import Callable import rich.console import rich.table from common import ROOT_DIR from generator import generate, get_algorithms_per_rl_library from InquirerPy import inquirer, separator class CLIHandler: """CLI handler for the Isaac Lab template.""" def __init__(self): self.console = rich.console.Console() @staticmethod def get_choices(choices: list[str], default: list[str]) -> list[str]: return default if "all" in choices or "both" in choices else choices def output_table(self, table: rich.table.Table, new_line_start: bool = True) -> None: """Print a rich table to the console. Args: table: The table to print. new_line_start: Whether to print a new line before the table. """ self.console.print(table, new_line_start=new_line_start) def input_select( self, message: str, choices: list[str], default: str | None = None, long_instruction: str = "" ) -> str: """Prompt the user to select an option from a list of choices. Args: message: The message to display to the user. choices: The list of choices to display to the user. default: The default choice. long_instruction: The long instruction to display to the user. Returns: str: The selected choice. """ return inquirer.select( message=message, choices=choices, cycle=True, default=default, style=None, wrap_lines=True, long_instruction=long_instruction, ).execute() def input_checkbox(self, message: str, choices: list[str], default: str | None = None) -> list[str]: """Prompt the user to select one or more options from a list of choices. Args: message: The message to display to the user. choices: The list of choices to display to the user. default: The default choice. Returns: The selected choices. """ def transformer(result: list[str]) -> str: if "all" in result or "both" in result: token = "all" if "all" in result else "both" return f"{token} ({', '.join(choices[: choices.index('---')])})" return ", ".join(result) return inquirer.checkbox( message=message, choices=[separator.Separator() if "---" in item else item for item in choices], cycle=True, default=default, style=None, wrap_lines=True, validate=lambda result: len(result) >= 1, invalid_message="No option selected (SPACE: select/deselect an option, ENTER: confirm selection)", transformer=transformer, ).execute() def input_path( self, message: str, default: str | None = None, validate: Callable[[str], bool] | None = None, invalid_message: str = "", ) -> str: """Prompt the user to input a path. Args: message: The message to display to the user. default: The default path. validate: A callable to validate the path. invalid_message: The message to display to the user if the path is invalid. Returns: The input path. """ return inquirer.filepath( message=message, default=default if default is not None else "", validate=validate, invalid_message=invalid_message, ).execute() def input_text( self, message: str, default: str | None = None, validate: Callable[[str], bool] | None = None, invalid_message: str = "", ) -> str: """Prompt the user to input a text. Args: message: The message to display to the user. default: The default text. validate: A callable to validate the text. invalid_message: The message to display to the user if the text is invalid. Returns: The input text. """ return inquirer.text( message=message, default=default if default is not None else "", validate=validate, invalid_message=invalid_message, ).execute() class State(str, enum.Enum): Yes = "[green]yes[/green]" No = "[red]no[/red]" def main() -> None: """Main function to run template generation from CLI.""" cli_handler = CLIHandler() lab_module = importlib.import_module("isaaclab") lab_path = os.path.realpath(getattr(lab_module, "__file__", "") or (getattr(lab_module, "__path__", [""])[0])) is_lab_pip_installed = ("site-packages" in lab_path) or ("dist-packages" in lab_path) if not is_lab_pip_installed: # project type is_external_project = ( cli_handler.input_select( "Task type:", choices=["External", "Internal"], long_instruction=( "External (recommended): task/project is in its own folder/repo outside the Isaac Lab project.\n" "Internal: the task is implemented within the Isaac Lab project (in source/isaaclab_tasks)." ), ).lower() == "external" ) else: is_external_project = True # project path (if 'external') project_path = None if is_external_project: project_path = cli_handler.input_path( "Project path:", default=os.path.dirname(ROOT_DIR) + os.sep, validate=lambda path: not os.path.abspath(path).startswith(os.path.abspath(ROOT_DIR)), invalid_message="External project path cannot be within the Isaac Lab project", ) # project/task name project_name = cli_handler.input_text( "Project name:" if is_external_project else "Task's folder name:", validate=lambda name: name.isidentifier(), invalid_message=( "Project/task name must be a valid identifier (Letters, numbers and underscores only. No spaces, etc.)" ), ) # Isaac Lab workflow # - show supported workflows and features workflow_table = rich.table.Table(title="RL environment features support according to Isaac Lab workflows") workflow_table.add_column("Environment feature", no_wrap=True) workflow_table.add_column("Direct", justify="center") workflow_table.add_column("Manager-based", justify="center") workflow_table.add_row("Single-agent", State.Yes, State.Yes) workflow_table.add_row("Multi-agent", State.Yes, State.No) workflow_table.add_row("Fundamental/composite spaces (apart from 'Box')", State.Yes, State.No) cli_handler.output_table(workflow_table) # - prompt for workflows supported_workflows = ["Direct | single-agent", "Direct | multi-agent", "Manager-based | single-agent"] workflow = cli_handler.get_choices( cli_handler.input_checkbox("Isaac Lab workflow:", choices=[*supported_workflows, "---", "all"]), default=supported_workflows, ) workflow = [{"name": item.split(" | ")[0].lower(), "type": item.split(" | ")[1].lower()} for item in workflow] single_agent_workflow = [item for item in workflow if item["type"] == "single-agent"] multi_agent_workflow = [item for item in workflow if item["type"] == "multi-agent"] # RL library rl_library_algorithms = [] algorithms_per_rl_library = get_algorithms_per_rl_library() # - show supported RL libraries and features rl_library_table = rich.table.Table(title="Supported RL libraries") rl_library_table.add_column("RL/training feature", no_wrap=True) rl_library_table.add_column("rl_games") rl_library_table.add_column("rsl_rl") rl_library_table.add_column("skrl") rl_library_table.add_column("sb3") rl_library_table.add_row("ML frameworks", "PyTorch", "PyTorch", "PyTorch, JAX", "PyTorch") rl_library_table.add_row("Relative performance", "~1X", "~1X", "~1X", "~0.03X") rl_library_table.add_row( "Algorithms", ", ".join(algorithms_per_rl_library.get("rl_games", [])), ", ".join(algorithms_per_rl_library.get("rsl_rl", [])), ", ".join(algorithms_per_rl_library.get("skrl", [])), ", ".join(algorithms_per_rl_library.get("sb3", [])), ) rl_library_table.add_row("Multi-agent support", State.No, State.No, State.Yes, State.No) rl_library_table.add_row("Distributed training", State.Yes, State.No, State.Yes, State.No) rl_library_table.add_row("Vectorized training", State.Yes, State.Yes, State.Yes, State.No) rl_library_table.add_row("Fundamental/composite spaces", State.No, State.No, State.Yes, State.No) cli_handler.output_table(rl_library_table) # - prompt for RL libraries supported_rl_libraries = ["rl_games", "rsl_rl", "skrl", "sb3"] if len(single_agent_workflow) else ["skrl"] selected_rl_libraries = cli_handler.get_choices( cli_handler.input_checkbox("RL library:", choices=[*supported_rl_libraries, "---", "all"]), default=supported_rl_libraries, ) # - prompt for algorithms per RL library algorithms_per_rl_library = get_algorithms_per_rl_library(len(single_agent_workflow), len(multi_agent_workflow)) for rl_library in selected_rl_libraries: algorithms = algorithms_per_rl_library.get(rl_library, []) if len(algorithms) > 1: algorithms = cli_handler.get_choices( cli_handler.input_checkbox(f"RL algorithms for {rl_library}:", choices=[*algorithms, "---", "all"]), default=algorithms, ) rl_library_algorithms.append({"name": rl_library, "algorithms": [item.lower() for item in algorithms]}) specification = { "external": is_external_project, "path": project_path, "name": project_name, "workflows": workflow, "rl_libraries": rl_library_algorithms, } generate(specification) if __name__ == "__main__": main()