GPT Engineer

Specify what you want it to build, the AI asks for clarification, and then builds it.

GPT Engineer is made to be easy to adapt, extend, and make your agent learn how you want your code to look. It generates an entire codebase based on a prompt.

• Demo

Project philosophy

• Simple to get value
• Flexible and easy to add new own "AI steps". See steps.py.
• Incrementally build towards a user experience of:
  1. high level prompting
  2. giving feedback to the AI that it will remember over time
• Fast handovers, back and forth, between AI and human
• Simplicity, all computation is "resumable" and persisted to the filesystem

Setup

Choose either stable or development.

For stable release:

• python -m pip install gpt-engineer

For development:

• git clone https://github.com/AntonOsika/gpt-engineer.git
• cd gpt-engineer
• python -m pip install -e .
  • (or: make install && source venv/bin/activate for a venv)

API Key

Choose one of:

• Export env variable (you can add this to .bashrc so that you don't have to do it each time you start the terminal)
  • export OPENAI_API_KEY=[your api key]
• .env file:
  • Create a copy of .env.template named .env
  • Add your OPENAI_API_KEY in .env
• Custom model:
  • See docs, supports local model, azure, etc.

Check the Windows README for windows usage.

Usage

There are two ways to work with GPT-engineer: new code mode (the default), and improve existing code mode (the -i option).

Creating new code

• Create an empty folder for your project anywhere on your computer
• Create a file called prompt (no extension) inside your new folder and fill it with instructions
• Run gpt-engineer <project_dir> with a relative path to your folder
  • For example: gpt-engineer projects/my-new-project from the gpt-engineer directory root with your new folder in projects/

Improving Existing Code

• Locate a folder with code which you want to improve anywhere on your computer
• Create a file called prompt (no extension) inside your new folder and fill it with instructions for how you want to improve the code
• Run gpt-engineer <project_dir> -i with a relative path to your folder
  • For example: gpt-engineer projects/my-old-project from the gpt-engineer directory root with your folder in projects/

By running gpt-engineer you agree to our terms.

Results

Check the generated files in projects/my-new-project/workspace

Workflow

gpt-engineer --help lets you see all available options.

For example:

• To improve any existing project, use the flag: -i
• To give feedback to/improve a gpt-engineer generated project, use: --steps use_feedback

Alternatives

You can check Docker instructions to use Docker, or simply do everything in your browser:

Features

You can specify the "identity" of the AI agent by editing the files in the preprompts folder.

Editing the preprompts, and evolving how you write the project prompt, is how you make the agent remember things between projects.

Each step in steps.py will have its communication history with GPT4 stored in the logs folder, and can be rerun with scripts/rerun_edited_message_logs.py.

You can also run with open source models, like WizardCoder. See the documentation for example instructions.

Vision

The gpt-engineer community is building the open platform for devs to tinker with and build their personal code-generation toolbox.

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

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

We are currently looking for more maintainers and community organizers. Email anton.osika@gmail.com if you are interested in an official role.

Example

https://github.com/AntonOsika/gpt-engineer/assets/4467025/6e362e45-4a94-4b0d-973d-393a31d92d9b ˛