DBCopilot: Scaling Natural Language Querying to Massive Databases

arXiv:2312.03463v2 Announce Type: replace
Abstract: Text-to-SQL simplifies database interactions by enabling non-experts to convert their natural language (NL) questions into Structured Query Language (SQL) queries. While recent advances in large language models (LLMs) have improved the zero-shot text-to-SQL paradigm, existing methods face scalability challenges when dealing with massive, dynamically changing databases. This paper introduces DBCopilot, a framework that addresses these challenges by employing a compact and flexible copilot model for routing across massive databases. Specifically, DBCopilot decouples the text-to-SQL process …

abstract advances arxiv challenges cs.cl cs.db cs.ir database databases enabling experts face interactions language language models large language large language models llms massive natural natural language natural language querying paradigm queries query query language questions scalability scaling sql structured query language text text-to-sql type zero-shot