DEPRECATED: Try Mentat instead! https://github.com/AbanteAI/mentat

Wolverine

About

Give your python scripts regenerative healing abilities!

Run your scripts with Wolverine and when they crash, GPT-4 edits them and explains what went wrong. Even if you have many bugs it will repeatedly rerun until it's fixed.

For a quick demonstration see my demo video on twitter.

Setup

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
cp .env.sample .env

Add your openAI api key to .env

warning! By default wolverine uses GPT-4 and may make many repeated calls to the api.

Example Usage

To run with gpt-4 (the default, tested option):

python -m wolverine examples/buggy_script.py "subtract" 20 3

You can also run with other models, but be warned they may not adhere to the edit format as well:

python -m wolverine --model=gpt-3.5-turbo examples/buggy_script.py "subtract" 20 3

If you want to use GPT-3.5 by default instead of GPT-4 uncomment the default model line in .env:

DEFAULT_MODEL=gpt-3.5-turbo

You can also use flag --confirm=True which will ask you yes or no before making changes to the file. If flag is not used then it will apply the changes to the file

python -m wolverine examples/buggy_script.py "subtract" 20 3 --confirm=True

Environment variables

env name	description	default value
OPENAI_API_KEY	OpenAI API key	None
DEFAULT_MODEL	GPT model to use	"gpt-4"
VALIDATE_JSON_RETRY	Number of retries when requesting OpenAI API (-1 means unlimites)	-1

Future Plans

This is just a quick prototype I threw together in a few hours. There are many possible extensions and contributions are welcome:

• add flags to customize usage, such as asking for user confirmation before running changed code
• further iterations on the edit format that GPT responds in. Currently it struggles a bit with indentation, but I'm sure that can be improved
• a suite of example buggy files that we can test prompts on to ensure reliability and measure improvement
• multiple files / codebases: send GPT everything that appears in the stacktrace
• graceful handling of large files - should we just send GPT relevant classes / functions?
• extension to languages other than python

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