gpt-engineer README

The project's README from github.com/AntonOsika/gpt-engineer. As one markdown file: README.md.

gpt-engineer

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The OG code genereation experimentation platform!

If you are looking for the evolution that is an opinionated, managed service – check out gptengineer.app.

If you are looking for a well maintained hackable CLI for – check out aider.

gpt-engineer lets you:

Getting Started

Install gpt-engineer

For stable release:

For development:

We actively support Python 3.10 - 3.12. The last version to support Python 3.8 - 3.9 was 0.2.6.

Setup API key

Choose one of:

Check the Windows README for Windows usage.

Other ways to run:

Create new code (default usage)

Improve existing code

Benchmark custom agents

The community has started work with different benchmarking initiatives, as described in this Loom video.

Research

Some of our community members have worked on different research briefs that could be taken further. See this document if you are interested.

Terms

By running gpt-engineer, you agree to our terms.

Relation to gptengineer.app (GPT Engineer)

gptengineer.app is a commercial project for the automatic generation of web apps. It features a UI for non-technical users connected to a git-controlled codebase. The gptengineer.app team is actively supporting the open source community.

Features

Pre Prompts

You can specify the "identity" of the AI agent by overriding the preprompts folder with your own version of the preprompts. You can do so via the --use-custom-preprompts argument.

Editing the preprompts is how you make the agent remember things between projects.

Vision

By default, gpt-engineer expects text input via a prompt file. It can also accept image inputs for vision-capable models. This can be useful for adding UX or architecture diagrams as additional context for GPT Engineer. You can do this by specifying an image directory with the —-image_directory flag and setting a vision-capable model in the second CLI argument.

E.g. gpte projects/example-vision gpt-4-vision-preview --prompt_file prompt/text --image_directory prompt/images -i

Open source, local and alternative models

By default, gpt-engineer supports OpenAI Models via the OpenAI API or Azure OpenAI API, as well as Anthropic models.

With a little extra setup, you can also run with open source models like WizardCoder. See the documentation for example instructions.

Mission

The gpt-engineer community mission is to maintain tools that coding agent builders can use and facilitate collaboration in the open source community.

If you are interested in contributing to this, we are interested in having you.

If you want to see our broader ambitions, check out the roadmap, and join discord to learn how you can contribute to it.

gpt-engineer is governed by a board of long-term contributors. If you contribute routinely and have an interest in shaping the future of gpt-engineer, you will be considered for the board.

Significant contributors

Example

https://github.com/gpt-engineer-org/gpt-engineer/assets/4467025/40d0a9a8-82d0-4432-9376-136df0d57c99

gpt-engineer (AntonOsika/gpt-engineer)

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What is this?gpt-engineer is a CLI tool where you describe the software you want in a plain-text 'prompt' file, and an AI (OpenAI, Azure OpenAI, or Anthropic models) writes and executes the code for you; you can also ask it to implement improvements to existing code.
Is this a library I import, or a standalone CLI tool?It is a standalone command-line tool installed with pip (or run via Docker) and invoked as 'gpte' against a project folder, not a library you import into your own code.
How do I get it running?Install with 'python -m pip install gpt-engineer', create an empty project folder, add a file named 'prompt' containing your instructions, then run 'gpte projects/my-new-project' pointing at that folder.
Do I need an OpenAI API key to use it?Yes by default — export OPENAI_API_KEY or place it in a .env file; it also works with Azure OpenAI, Anthropic models, or local/open-source models like WizardCoder with a bit of extra setup.
Is this project still actively maintained?No — the repository is archived, and the README itself points users toward gptengineer.app for the managed successor or 'aider' for a well-maintained, hackable CLI alternative.
Does it work on Windows as well as macOS/Linux?Yes, there is a dedicated Windows README covering Windows-specific usage, in addition to the standard pip install and a Docker option.
How do I improve existing code instead of starting a new project?Point gpt-engineer at a folder that already contains code, add a 'prompt' file describing the desired changes, and run 'gpte path/to/folder -i' to apply AI-driven improvements.
Can I benchmark my own coding agents with it?Yes, installing gpt-engineer also installs a 'bench' CLI for testing custom agent implementations against public datasets like APPS and MBPP.
Does it support image inputs for vision models?Yes, you can pass an image directory with the --image_directory flag alongside a vision-capable model like gpt-4-vision-preview, useful for giving the AI UX or architecture diagrams as context.
What's the difference between this and gptengineer.app?gptengineer.app is the commercial, actively developed evolution with a UI for non-technical users and a git-controlled codebase, while this repository is the original open-source CLI experimentation tool, now archived.
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AntonOsika
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