- Define tasks in
tasks/ - Collect data & run experiments via
generation_rec_agents.py - Results will be saved in
trajs_agent/
- Data to generate training data and run experiments in
env/. - Download data from steam_test.npy, steam_train.npy, train_distance_mat, test_distance_mat to
/env/steam/ - Download data from amazon_test.npy, amazon_train.npy, train_distance_mat, test_distance_mat to
/env/amazon/
Set up OpenAI API key and store in environment variable (see here)
export OPENAI_API_KEY=<YOUR_KEY>
Create virtual env, for example with conda
conda create -n BiLLP python=3.9
conda activate BiLLP
Install dependencies
pip install -r requirements.txt
Generate embedding via /env/steam/llama_generate_embedding.ipynb
Example:
train and test
source run_steam.sh
source run_steam_test.sh
source run_amazon.sh
source run_amazon_test.sh
Our code is based on FireAct