Authors:
João Pinheiro
1
;
Wendy Victorio
1
;
2
;
Eduardo Nascimento
1
;
2
;
Antony Seabra
1
;
Yenier Izquierdo
2
;
Grettel García
2
;
Gustavo Coelho
2
;
Melissa Lemos
1
;
2
;
Luiz Leme
3
;
Antonio Furtado
1
and
Marco Casanova
1
;
2
Affiliations:
1
Departamento de Informática, PUC-Rio, Rio de Janeiro, 22451-900, RJ, Brazil
;
2
Instituto Tecgraf, PUC-Rio, Rio de Janeiro, 22451-900, RJ, Brazil
;
3
Instituto de Computação, UFF, Niterói, 24210-310, RJ, Brazil
Keyword(s):
Large Language Models, Database Interfaces, Conversational Interfaces.
Abstract:
This paper argues that Large Language Models (LLMs) can be profitably used to construct natural language (NL) database interfaces, including conversational interfaces. Such interfaces will be simply called LLM-based database (conversational) interfaces. It discusses three problems: how to use an LLM to create an NL database interface; how to fine-tune an LLM to follow instructions over a particular database; and how to simplify the construction of LLM-based database (conversational) interfaces. The paper covers the first two problems with the help of examples based on two well-known LLM families, GPT and LLaMA, developed by OpenAI and Meta, respectively. Likewise, it discusses the third problem, with the help of examples based on two frameworks, LangChain and LlamaIndex.