ADEPT-SQL: A High-performance Text-to-SQL Application for Real-World Enterprise-Level Databases

This paper presents ADEPT-SQL, a domainadapted Text2SQL system that addresses critical deployment challenges in professional fields. While modern LLM-based solutions excel on academic benchmarks, we identify three persistent limitations in industrial application: domain-specific knowledge barriers, the schemas complexity in real-world, and the prohibitive computational costs of large LLMs. Our framework introduces two key innovations: a three-stage grounding mechanism combining dynamic terminology expansion, focused schema alignment, and historical query retrieval; coupled with a hybrid prompting architecture that decomposes SQL generation into schema-aware hinting, term disambiguation, and few-shot example incorporation phases. This approach enables efficient execution using smaller open-source LLMs while maintaining semantic precision. Deployed in petroleum engineering domains, our system achieves 97% execution accuracy on real-world databases, demonstrating 49% absolute improvement over SOTA baselines. We release implementation code to advance research in professional Text2SQL systems.