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HIMANSHU KUMAR
HIMANSHU KUMAR

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I Built a CLI Tool That Writes Git Commit Messages Using Local AI (Ollama)

#ai #programming #productivity #python

One of the most common problems developers face is writing good Git commit messages.

After a long coding session, many of us end up writing commit messages like:

fix stuff
update code
changes
final fix
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These messages work, but they don't really explain what changed or why the change was made. Over time, this makes project history harder to understand.

So I decided to build a small developer tool to solve this problem.

Introducing AI Commit — a CLI tool that automatically generates meaningful Git commit messages using local AI models.

The Idea

The idea behind AI Commit is simple:

  1. Detect staged Git changes
  2. Send the diff to a local AI model
  3. Generate a structured commit message
  4. Let the developer review and commit

The interesting part is that everything runs locally using Ollama, which means:

  • No API keys required
  • No cloud dependency
  • Works completely offline
  • Privacy-first workflow

How It Works

The tool analyzes your staged Git changes and sends them to a local language model.

Git diff
   ↓
AI Commit CLI
   ↓
Local Ollama Model
   ↓
Generated Commit Message
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The generated commit message can follow different formats such as:

  • Conventional commits
  • Semantic commit messages
  • Detailed commit descriptions

Installation

The tool is available on PyPI and can be installed with pip.

pip install ollama-git-commit
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Requirements

Before using the tool, make sure you have:

  • Python 3.8+
  • Git installed
  • Ollama installed and running

Start Ollama:

ollama serve
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Pull a model (example):

ollama pull llama3
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Usage

Navigate to any Git repository and stage your changes.

git add .
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Then run:

ai-commit
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The tool will:

  1. Analyze your staged changes
  2. Generate a commit message
  3. Allow you to review or modify it

This makes writing good commit messages fast and consistent.

Why Local AI?

Many AI developer tools rely on cloud APIs.

While this works well, it has a few drawbacks:

  • API costs
  • Internet dependency
  • Privacy concerns

By using local LLMs with Ollama, AI Commit keeps everything on your machine.

This makes it ideal for developers who prefer offline and private AI workflows.

Tech Stack

The project is built with:

  • Python
  • Ollama
  • Git CLI
  • Local LLM models
  • Open source tooling

Open Source Project

AI Commit is fully open source and available on GitHub.

GitHub Repository:
https://github.com/himanshu231204/ai-commit

PyPI Package:
https://pypi.org/project/ollama-git-commit/

If you find the project useful, consider giving it a ⭐ on GitHub.

What I Learned Building This

While building this project, I learned several things:

  • How to build CLI tools with Python
  • Integrating local LLMs using Ollama
  • Packaging and publishing Python libraries to PyPI
  • Designing developer productivity tools

Open source projects like this are a great way to learn by building real tools.

Future Improvements

Some features I'm planning to add:

  • Git hook support
  • Better commit style detection
  • Configuration file support
  • VS Code integration

Final Thoughts

Good commit messages are an important part of maintaining clean and understandable project history.

AI Commit is a small step toward making that process easier with the help of local AI.

If you're interested in experimenting with AI-powered developer tools, feel free to try it out.

Feedback and contributions are always welcome.

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