arXiv (Cornell University)
Towards Optimizing SQL Generation via LLM Routing
November 2024 • Mohammadhossein Malekpour, Nicholas J. Shaheen, Foutse Khomh, Amine Mhedhbi
Text-to-SQL enables users to interact with databases through natural language, simplifying access to structured data. Although highly capable large language models (LLMs) achieve strong accuracy for complex queries, they incur unnecessary latency and dollar cost for simpler ones. In this paper, we introduce the first LLM routing approach for Text-to-SQL, which dynamically selects the most cost-effective LLM capable of generating accurate SQL for each query. We present two routing strategies (score- and classificat…