English

Retail-GPT: leveraging Retrieval Augmented Generation (RAG) for building E-commerce Chat Assistants

Information Retrieval 2024-08-20 v1 Artificial Intelligence Computation and Language Human-Computer Interaction

Abstract

This work presents Retail-GPT, an open-source RAG-based chatbot designed to enhance user engagement in retail e-commerce by guiding users through product recommendations and assisting with cart operations. The system is cross-platform and adaptable to various e-commerce domains, avoiding reliance on specific chat applications or commercial activities. Retail-GPT engages in human-like conversations, interprets user demands, checks product availability, and manages cart operations, aiming to serve as a virtual sales agent and test the viability of such assistants across different retail businesses.

Cite

@article{arxiv.2408.08925,
  title  = {Retail-GPT: leveraging Retrieval Augmented Generation (RAG) for building E-commerce Chat Assistants},
  author = {Bruno Amaral Teixeira de Freitas and Roberto de Alencar Lotufo},
  journal= {arXiv preprint arXiv:2408.08925},
  year   = {2024}
}

Comments

5 pages, 4 figures

R2 v1 2026-06-28T18:15:02.513Z