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

TL;DR

Retail-GPT is an open-source, retrieval-augmented generation chatbot that enhances e-commerce user engagement by providing product recommendations, managing carts, and supporting cross-platform retail interactions.

Contribution

It introduces a versatile, open-source RAG-based chatbot tailored for retail e-commerce, capable of human-like conversations and adaptable to various domains without relying on proprietary chat platforms.

Findings

Effective in guiding product recommendations

Handles cart operations seamlessly

Demonstrates cross-platform adaptability

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.