gpt-engineer

GPT Engineer port in Typescript

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:
  • high level prompting
  • 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

Usage

Choose either stable or development.

For stable release:

• npx gpt-engineer

For development:

• coming soon

Setup

With an OpenAI API key (preferably with GPT-4 access) run:

• export OPENAI_API_KEY=[your api key]

To set API key on windows check the Windows README.

Run:

• Create an empty folder. If inside the repo, you can run:
  • cp -r projects/example/ projects/my-new-project
• Fill in the prompt file in your new folder
• gpt-engineer projects/my-new-project
  • (Note, gpt-engineer --help lets you see all available options. For example --steps use_feedback lets you improve/fix code in a project)

By running gpt-engineer you agree to our terms.

Results

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

To run in the browser you can simply:

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.

Credits

Based on the implementaion of GPT-Engineer . More details will be added soon.

Example

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