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 👶🤖
- 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
Setup
git clone [email protected]:AntonOsika/gpt-engineer.git
cd gpt-engineer
make install
source venv/bin/activate
With an api key that has GPT4 access run:
export OPENAI_API_KEY=[your api key]
Run:
- Create an empty folder. If inside the repo, you can run:
cp -r projects/example/ projects/my-new-project
- Fill in the
main_prompt
file in your new folder - Run:
gpt-engineer projects/my-new-project
Results
- Check the generated files in
projects/my-new-project/workspace
You can specify the "identity" of the AI agent by editing the files in the identity
folder.
Editing the identity, and evolving the main_prompt
, is currently 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
.
We are building the open platform for devs to tinker with and build their personal code-generation toolbox.
If you want to contribute, please check out the roadmap, projects or issues tab in the GitHub repo. You are welcome to read the contributing document and join our Discord 💬.
We are currently looking for more maintainers and community organisers. Email [email protected] if you are interested in an official role.