This is the code release for the paper ProgPrompt: Generating Situated Robot Task Plans using Large Language Models. It contains code for replicating the results on the VirtualHome dataset.

Create a conda environment (or your virtualenv):

conda create -n progprompt python==3.9

Install dependencies:

pip install -r requirements.txt

Clone VirtualHome and install it by running:

pip install -e .

Note: If you an encounter an error to do with wrong number of arguments to function execute, then in file virtualhome/src/virtualhome/simulation/evolving_graph/execution.py line 67, add *args as follows:

    def execute(self, script: Script, state: EnvironmentState, info: ExecutionInfo, char_index, *args):

This was tested on VirtualHome commit f84ee28a75b23318ee1bf652862b1c993269cd06.

Finally, download the virtualhome unity simulator and make sure it runs. The simulator can run on the desktop, or on a virtual x-server.

Here is a minimal example how to run the evaluation script. Replace {arguments in curly braces} with appropriate values on your system:

python3 scripts/run_eval.py --progprompt-path $(pwd) --expt-name {expt_name} --openai-api-key {key} --unity-filename {v2.3_virtualhome_sim} --display {0}

For more options and arguments, look inside scripts/run_eval.py.