RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interface

Authors

  • Zeyuan Zhang University of California, San Diego
  • Tanmay Laud University of California, San Diego
  • Zihang He University of California, San Diego
  • Xiaojie Chen University of California, San Diego
  • Xinshuang Liu University of California, San Diego
  • Zhouhang Xie University of California, San Diego
  • Julian McAuley University of California, San Diego
  • Zhankui He University of California, San Diego

DOI:

https://doi.org/10.1609/aaai.v38i21.30588

Keywords:

Artificial Intelligence, Human-AI interaction (including Human-robot interaction), Natural language processing and speech recognition, Software and testing tools for developing AI technologies

Abstract

We present a new Python toolkit called RecWizard for Conversational Recommender Systems (CRS). RecWizard offers support for development of models and interactive user interface, drawing from the best practices of the Huggingface ecosystems. CRS with RecWizard are modular, portable, interactive and Large Language Models (LLMs)-friendly, to streamline the learning process and reduce the additional effort for CRS research. For more comprehensive information about RecWizard, please check our GitHub https://github.com/McAuley-Lab/RecWizard.
AAAI-24 / IAAI-24 / EAAI-24 Proceedings Cover

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Published

2024-03-24

How to Cite

Zhang, Z., Laud, T., He, Z., Chen, X., Liu, X., Xie, Z., McAuley, J., & He, Z. (2024). RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interface. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23856-23858. https://doi.org/10.1609/aaai.v38i21.30588

Issue

Vol. 38 No. 21: IAAI-24, EAAI-24, AAAI-24 Student Abstracts, Undergraduate Consortium and Demonstrations

Section

AAAI Demonstration Track