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A CLI tool that generates semantic Japanese commit message prompts for LLMs from Git diff information.

Project description

komitto (commit)

PyPI Downloads

English | 日本語

A CLI tool that analyzes git diff and calls LLM APIs (OpenAI, Gemini, Anthropic, Ollama, etc.) to generate semantic commit messages. It can also learn your project's commit style from history (komitto learn) and apply it automatically.

Key Features

  • Analyzes staged changes (git diff --staged) and optionally compares multiple contexts.
  • Converts change details into a structured XML/JSON format that LLMs can understand.
  • LLM API Integration: Directly calls APIs from providers like OpenAI, Gemini, Anthropic, Ollama, etc., using settings defined in komitto.toml.
  • Reasoning Process Visualization: Streams and visualizes the LLM's reasoning process (e.g., <think> tags) in real-time.
  • Contextual Understanding: Automatically includes recent commit logs in the prompt to preserve project context and style.
  • External File References: Easily reference and embed the contents of external files into your prompt context.
  • Style Learning (komitto learn): Analyzes your commit history to generate a custom system prompt that matches your project's commit style.
  • Combines with system prompts specifically designed for commit message generation; templates can be overridden per-context, per-template, or per-model.
  • Copies the final generated prompt (or raw LLM output) to the clipboard.
  • Provides functionality to attach additional context about the changes via command-line arguments.
  • Interactive Mode (-i/--interactive): Review, edit, regenerate, or commit the generated message in a rich TUI interface.
  • TUI Interface: Built with Textual for a modern terminal experience with real-time streaming, loading spinners, and animations.
  • Editor Integration: Edit the commit message using your preferred editor (VISUAL/EDITOR/GIT_EDITOR).

Installation

komitto requires Python 3.9+.

pip install komitto

For development installation, use:

pip install -e .

Language Support

komitto automatically detects your language based on OS locale. Supported languages:

  • English (en) – default
  • Japanese (ja)

Set KOMITTO_LANG=ja to force Japanese.

Usage

AI-Automated Generation (Recommended)

When you configure provider, model, and other API settings in komitto.toml, running komitto will directly interact with the LLM. It streams the reasoning process and the commit message generation in real-time, then provides an interactive prompt.

komitto
# -> ⏳ Generating...
# -> (Streams the reasoning and message)
# -> Commit message generated.
# -> [y] Accept and commit [e] Edit [r] Regenerate [n] Cancel:

Available commands during the interactive loop:

  • y – Accept and commit (git commit -m <msg>)
  • e – Edit the message in an external editor
  • r – Regenerate
  • n or Ctrl-C – Cancel

Prompt Generation Mode (Manual)

If you haven't configured the [llm] section, komitto falls back to generating a prompt based on your staged changes and copies it to your clipboard.

komitto
# -> Prompt copied!

Comparison Mode

Compare two different configurations side-by-side:

komitto --compare ctxA ctxB

Two columns are displayed; press a or b to select one, then commit or edit as usual.

Passing Additional Context

Add free-form context that will be merged into the prompt:

komitto "Urgent bug fix for payment processing"

Editor Integration

During interactive mode you can invoke the configured editor at any time. The selection order is:

  1. $GIT_EDITOR
  2. $VISUAL
  3. $EDITOR
  4. Git's built-in default (notepad on Windows, vi otherwise).

Style Learning

Analyze your existing commit history to automatically generate a system prompt tailored to your project:

komitto learn

This command:

  1. Reads recent commit messages from your repository
  2. Analyzes the language, format, and conventions used
  3. Generates a custom system prompt matching your style
  4. Optionally updates komitto.toml automatically

CLI Options

Option Description
-i, --interactive Enable interactive TUI mode
-c, --context-name NAME Use a specific context profile from config
-t, --template NAME Use a specific prompt template from config
-m, --model NAME Use a specific model from config
--compare CTX1 CTX2 Compare outputs from two context configurations

Customization via Configuration File

Create a project-specific configuration with:

komitto init

Configuration files are looked up in this order (later overrides earlier):

  1. User config directory (%APPDATA%\komitto\config.toml, etc.)
  2. Project directory ./komitto.toml

Sample komitto.toml

[prompt]
system = """
You are a helpful assistant that produces semantic commit messages following Conventional Commits.
Analyze the diff below and output only the subject line (<=50 chars) and an optional body.
"""

[context]
# Reference files to always include in the prompt
# files = ["README.md"]

[llm]
provider = "openai" # "openai", "gemini", "anthropic"
model = "gpt-5.4-mini"
# api_key = "sk-..." # Optional if environment variable is set
# base_url = "http://localhost:11434/v1" # For Ollama etc.
# history_limit = 5

[git]
# Files to exclude from the diff (glob patterns)
exclude = [
    "package-lock.json",
    "yarn.lock",
    "pnpm-lock.yaml",
    "poetry.lock",
    "Cargo.lock",
    "go.sum",
    "*.lock"
]

# --- Advanced Settings (Templates & Contexts) ---
# [templates.simple]
# system = "Summarize changes in one line."

# [models.gpt4]
# provider = "openai"
# model = "gpt-5.4-mini"

# [contexts.release]
# template = "simple"
# model = "gpt4"

Using Ollama/LM Studio

[llm]
provider = "openai"        # still used for compatibility layer
model = "qwen3"
base_url = "http://localhost:11434/v1"

How It Works (Internal Flow)

  1. git diff --staged retrieves staged changes.
  2. Differences are transformed into a structured representation (file path | operation | surrounding function/class signatures) in XML-like format.
  3. The configuration file defines a system prompt; this is merged with any user-provided context and the diff representation to produce the final LLM input.
  4. Depending on CLI flags, the tool either streams tokens live (Rich UI) or returns a complete string instantly.
  5. The resulting text is copied to the clipboard; in interactive mode the user can accept, edit, regenerate, or cancel.

License

MIT © 2025-2026

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