CodeAct-based Agent Framework

This folder implements the CodeAct idea that relies on LLM to autonomously perform actions in a Bash shell. It requires more from the LLM itself: LLM needs to be capable enough to do all the stuff autonomously, instead of stuck in an infinite loop.

NOTE: This agent is still highly experimental and under active development to reach the capability described in the original paper & repo.

codeact-demo.mp4

Demo of the expected capability - work-in-progress.

mkdir workspace
PYTHONPATH=`pwd`:$PYTHONPATH python3 opendevin/main.py -d ./workspace -c CodeActAgent -t "Please write a flask app that returns 'Hello, World\!' at the root URL, then start the app on port 5000. python3 has already been installed for you."

Example: prompts gpt-4-0125-preview to write a flask server, install flask library, and start the server.

Most of the things are working as expected, except at the end, the model did not follow the instruction to stop the interaction by outputting <execute> exit </execute> as instructed.

TODO: This should be fixable by either (1) including a complete in-context example like this, OR (2) collect some interaction data like this and fine-tune a model (like this, a more complex route).