COMPASS

Official Implementation of Unveiling User Preferences: A Knowledge Graph and LLM-Driven Approach for Conversational Recommendation

Installation

Follow these steps to set up the environment:

1. Create a Conda Environment

   Use the provided environment.yml file to create and activate the Conda environment:

   conda env create -f environment.yml
   conda activate compass

2. Set up Hugging Face Token

   Add your Hugging Face token to a .env file. Ensure you have accepted the license agreements for the required model. Visit the Hugging Face website to review and accept the agreements.

   HUGGINGFACE_API_KEY=<your_huggingface_token>

Quick-Start

To train the COMPASS model, run the following command:

python main.py

You can specify dataset, models in the config/default.yaml file.

• Dataset-specific configurations can be found in the config/dataset/ folder.
• Model-specific configurations can be found in the config/model/ folder.

Enhancement

Once training is complete, copy the generated user preference summary folder to: data/<dataset_name>/preprocessed/llm_outputs/compass/ folder.

Then update the config/default.yaml file with the baseline model name and run the following command:

python main.py

Citation

@article{qiu2024unveiling,
  title={Unveiling User Preferences: A Knowledge Graph and LLM-Driven Approach for Conversational Recommendation},
  author={Qiu, Zhangchi and Luo, Linhao and Pan, Shirui and Liew, Alan Wee-Chung},
  journal={arXiv preprint arXiv:2411.14459},
  year={2024},
}