appleboy/CodeGPT: a Go CLI that writes commit messages and review briefs

The problem CodeGPT targets: commit messages that describe nothing

Most commit messages are written after the work is done, under time pressure, from memory. The result is a one-line summary that says what changed but not why, and reviewers end up reading the diff anyway. CodeGPT takes the staged diff, sends it to a language model, and returns a message that follows the conventional commits specification. The README lists that specification as a feature, which tells you the intended output shape: a type, an optional scope, and a description.

The tool is aimed at individual developers and small teams who already care about commit hygiene but do not want to write the message themselves. It is a command line program, not an editor plugin. There is no editor integration in the repository as described; the README mentions a VSCode devcontainer feature, which installs the binary inside a container, not a VSCode extension. If you searched for a CodeGPT extension for VSCode or IntelliJ, the repository does not describe one.

The second use case is a code review brief. The README shows a screenshot of that output and lists it as a feature, but the surrounding text does not explain what the brief contains or how it is scoped. Treat that as a secondary capability with thin documentation.

How CodeGPT builds a prompt from a git diff

The flow is straightforward and visible from the repository layout. The git/ directory handles diff extraction, the prompt/ directory holds templates, the provider/ directory holds the API clients, and core/ ties them together. The go.mod file confirms the provider clients: github.com/sashabaranov/go-openai for OpenAI, github.com/liushuangls/go-anthropic/v2 for Anthropic, and google.golang.org/genai for Gemini. Groq, Ollama and OpenRouter are listed as supported in the README features, and the go.mod also carries github.com/go-authgate/sdk-go, which is consistent with the API key helper described in the configuration section.

The diff is not sent raw. The README states that you can specify the number of context lines in the generated diff, with a default of 3, and that file exclusion patterns are supported. Both settings matter: context lines control how much surrounding code the model sees, and exclusion patterns are the only mechanism described for keeping files out of the request. There is no mention of a size cap or truncation strategy, so a large staged change is an open question.

Prompts are templates with variables, and the default prompt folder can be pointed elsewhere. That is the main extension point. If the default output does not match your team's style, you edit the template rather than the binary. Output can also be streamed, which the README lists as a feature for real-time token display.

Installing CodeGPT and generating your first commit message

On macOS the README gives Homebrew. On Windows it gives Chocolatey. Both install a prebuilt binary, so no Go toolchain is required.

brew tap appleboy/tap
brew install codegpt

The script route works on most systems and downloads the latest release automatically.

bash < <(curl -sSL https://raw.githubusercontent.com/appleboy/CodeGPT/main/install.sh)

If you prefer to build it yourself, the module path is given in the README and the binary lands in your Go bin directory.

go install github.com/appleboy/CodeGPT/cmd/codegpt@latest

After installing, confirm the binary is on your PATH. The README uses this command for that check.

codegpt version

Configuration comes next. The README opens the configuration section by telling you to create an OpenAI API key on the OpenAI Platform, and the codebase loads environment files through github.com/joho/godotenv, so a .env file in the working directory is the expected place for credentials. The README also documents an API key helper for dynamic credentials, with a configurable refresh interval, and a priority order for where the key is read from. That section is the one to read carefully before putting CodeGPT into a shared environment, because a helper that shells out on a timer is a different trust decision from a static key in a dotfile.

The first real use is the hook. The README documents both install and uninstall, and the hook is a git prepare-commit-msg hook, so it runs when git opens the commit message editor. Once installed, staging files and running git commit should produce a prefilled message you can edit or accept.

Where CodeGPT gets in the way

The hook model is the biggest constraint. A prepare-commit-msg hook fires on every commit in that repository, including merges, amends and quick fixups where a generated message is noise. The README documents install and uninstall but does not document a bypass flag or a way to skip generation for a single commit, and it does not document rollback beyond uninstalling the hook. If the API is unreachable, the README does not say what the hook does. A blocking hook that waits on a network call is a real cost on an offline train or behind a proxy that is not configured.

Privacy is the second constraint, and it is not addressed in the README at all. The staged diff leaves your machine and goes to whichever provider you configured. Exclusion patterns reduce the surface but do not remove it, and there is no described mode that redacts content before sending. For a repository containing credentials, customer data or regulated code, that is a decision to make before installation, not after.

The third constraint is that the tool is a message drafter, not a reviewer with repository context. It sees a diff and a template. It does not see your issue tracker, your architecture, or the discussion that produced the change. A generated message can be confidently wrong about intent, and nothing in the documented flow checks it against anything.

CodeGPT against writing the message yourself, or against a local model

The honest alternative is not another tool. It is writing the message yourself, which costs thirty seconds and produces something accurate. CodeGPT wins when the diff is large and mechanical, or when a team has agreed on conventional commits and wants consistency more than nuance.

The more interesting alternative is Ollama. The README lists it as a supported provider alongside Azure OpenAI, OpenAI, Gemini, Anthropic, Groq and OpenRouter. The difference in approach is where inference happens: with Ollama the model runs on your own hardware, so the diff never leaves the machine, at the cost of a local runtime and whatever quality gap exists between your local model and a hosted one. Because CodeGPT treats providers as interchangeable behind one configuration surface, switching between a hosted API and Ollama is a configuration change rather than a different tool. That is the strongest argument for this project over a provider-specific wrapper.

The provider list also means you are not locked into one vendor's pricing or availability, which matters more than raw output quality for a tool that runs on every commit.

Maintenance, releases and what the MIT licence means here

The last push to the default branch was on 2026-08-30, and the most recent release is v1.7.2 from 2026-06-28, following v1.7.1 in March 2026 and v1.7.0 earlier that same month. The repository is not archived. That pattern shows a project still receiving changes, with releases spaced a few months apart.

Upgrade cost is low for the binary itself: Homebrew, Chocolatey, the install script and go install all fetch a new build, and the Makefile embeds version, build time, commit, Go version, OS and architecture through linker flags, so codegpt version tells you exactly what you are running. The cost that is not low is prompt drift. Custom prompt templates are the documented extension point, and a template tuned for one model may not produce the same output after a provider changes its default model or after you switch providers. The README does not describe a migration path for prompt templates between versions.

The licence is MIT, which permits commercial use, modification and redistribution provided the copyright notice and permission notice are retained. That is a permissive arrangement with few obligations for internal tooling. What MIT does not do is address the terms of the model providers you point the tool at, and those terms are separate from the repository licence. This is not legal advice; read the provider terms yourself.

Editorial conclusion

Adopt CodeGPT if your team already writes conventional commits and you want the message drafted from the staged diff rather than typed by hand; the hook install and uninstall commands are documented, and the MIT licence imposes no distribution constraints. Skip it if your repository cannot send diffs to a third-party API, or if nobody will review the generated text before it lands in history. Verify first that your provider and model settings are accepted, that your diff exclusion patterns actually keep secrets out, and that the hook behaves as expected on a scratch branch before you install it in a shared repository.

Frequently asked questions

Official sources

1. appleboy/CodeGPT on GitHub
2. Issues
3. License: MIT
4. README
5. Releases