automake-cli 0.3.4

AI-powered Makefile command execution

🤖 auto-make

Makefiles without writing Makefiles.

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auto-make is a Python-based command-line tool that leverages a local Large Language autModel (LLM) to interpret your natural language commands and execute the correct Makefile target.

Tired of grep "deploy" Makefile? Just run automake "deploy the app to staging" and let the AI do the work.

✨ Key Features

• Natural Language Commands: Run make targets using plain English. No more memorizing target names.
• Local First: Integrates with local LLMs via Ollama for privacy and offline access.
• User-Friendly CLI: A clean, simple interface built with Typer.
• Configurable: Set your preferred LLM model and other options in a simple config.toml file.
• Modern Python Stack: Built with uv, smolagents, and pre-commit for a robust development experience.

⚙️ How It Works

auto-make follows a simple, powerful workflow to translate your instructions into actions:

1. Parse Command: The CLI captures your natural language instruction.
2. Read Makefile: It finds and reads the Makefile in your current directory.
3. Consult AI: It sends the Makefile contents and your instruction to a local LLM (via Ollama).
4. Identify Target: The LLM analyzes the context and identifies the single most likely make command to run.
5. Execute: The identified command is executed, and its output is streamed directly to your terminal.

🚀 Getting Started

Prerequisites

• Python 3.11+
• uv (recommended for installation)
• An active Ollama server with a running model (e.g., ollama run qwen3:0.6b).

Installation

Install auto-make using uvx (the uv equivalent of npx):

uvx automake-cli

This command temporarily installs and runs the automake CLI tool in an isolated environment.

First-Time Setup

After installation, run the initialization command once to set up Ollama and download the required model:

automake init

This command will:

• Verify that Ollama is installed and running
• Download the configured LLM model if not already available
• Ensure everything is ready for natural language command interpretation

✍️ Usage

To use auto-make, simply pass your command as a string argument:

automake "run the tests and generate a coverage report"

The tool will find the corresponding target in your Makefile and execute it.

For detailed usage information and available options, run:

automake help

🛠️ Configuration

On first run, auto-make will create a config.toml file in your user configuration directory. You can edit this file to change the default Ollama model or other settings.

Example config.toml:

# Default configuration for auto-make
[ollama]
model = "qwen3:0.6b" # Specify the Ollama model you want to use

🎬 Demos

Want to see some UI/UX demos? Just run uv run make demo-all or use automake: automake "show all demos"

Note: Running demos with automake may cause animation display issues. For the best demo experience, use the direct uv run make demo-all command.

🗺️ Project Roadmap

For a detailed breakdown of the project roadmap, implementation phases, and technical specifications, see SPECS.md.

🚀 Development & Publishing

For Contributors

This project uses modern Python tooling and automated publishing:

• Package Management: UV for fast dependency management
• Code Quality: Pre-commit hooks with Ruff for linting and formatting
• Testing: Pytest with comprehensive test coverage
• CI/CD: GitHub Actions for automated testing and publishing

Publishing Process

The project uses GitHub Actions with Trusted Publishing for secure, automated releases:

• Production: Automatically publishes to PyPI when a GitHub release is created
• Testing: Manual workflow to test publishing on TestPyPI before production releases

For detailed publishing instructions, see docs/PUBLISHING.md.

Installation Methods

# Direct execution (recommended for users)
uvx automake-cli

# Alternative with explicit package name
uvx --from automake-cli automake

# Traditional pip installation
pip install automake-cli