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.