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.
** It now comes with a real-time websocket interface between an optimized fast-loading ReactJS web app running on localhost and the Python3 agent. **
- 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
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)
- (or:
For GUI release:
sudo apt install python3-aiohttp
sudo apt install python3-socketio
pip install python-socketio
python3 applications/w3s/server.py &
cd /app
npm run build
npm install
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
- Create a copy of
- Custom model:
- See docs, supports local model, azure, etc.
Check the Windows README for windows usage.
Other ways to run:
- Use Docker (instructions)
- Do everything in your browser:
There are two ways to work with GPT-engineer: new code mode (the default), and improve existing code mode (the -i
option).
- 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 inprojects/
- For example:
- 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 inprojects/
- For example:
By running gpt-engineer you agree to our terms.
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.
You can also automatically copy all preprompts
files into your project folder using the cli parameter --use-custom-prepompts
. This way you can have custom preprompts for all of your projects without the need to edit the main files.
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.
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 [email protected] if you are interested in an official role.