tableswift 0.1.2

Data wrangling framework with LLM using code generation

Following work by Narayan et al., we use the same set of benchmark datasets. You can clone the repo and download the data by using:

git clone [e-mail]:effyli/efficient_llm_data_wrangling.git
mkdir data/
wget https://fm-data-tasks.s3.us-west-1.amazonaws.com/datasets.tar.gz -P data
tar xvf data/datasets.tar.gz -C data/

To run the script, first setup the data_dir environmental variable by using:

export DATASET_PATH="$PWD/data/datasets"

To start running jobs (e.g. for bing-query-logs-unit without data router and generate python code), try:

python src/run_wrangler.py --data_dir %your_data_directory/data_transformation/benchmark-bing-query-logs-unit%  --num_trials 3  --seed 42 --k 3 --d 0 --num_iter 5 --llm llama3.2 --lang python