ml-cli-tools

What problem does it solve?

This skill helps you avoid brittle, hard-to-maintain ML command-line interfaces by giving you a clean, type-safe way to parse complex parameters and present readable runtime feedback.

Core Features & Use Cases

• Type-safe argument parsing with Typer: Define commands and options using Python type hints for validation, autocomplete, and self-documenting help text.
• Rich terminal UX for ML workflows: Add progress bars, tables, and hierarchical views (e.g., model structure trees) without messy console output.
• Logging that doesn’t break progress bars: Use RichHandler so logs and progress render cleanly together, including multi-process-friendly logging patterns.
• Hydra configuration integration: Load and compose Hydra configs inside Typer commands to manage ML experiment parameters from the CLI.

Quick Start

Ask it to generate a Typer + Rich ML CLI command that accepts Hydra config overrides and prints a clean training progress bar with RichHandler logging.