Squrve: A Unified and Modular Framework for Complex Real-World Text-to-SQL Tasks
Yihan Wang, Peiyu Liu, Runyu Chen, Jiaxing Pu, Wei Xu

TL;DR
Squrve is a comprehensive, modular framework that unifies and enhances Text-to-SQL systems, facilitating real-world deployment through standardized interfaces and collaborative components, outperforming existing methods on benchmarks.
Contribution
Introduces Squrve, a unified, modular framework with a universal execution paradigm and multi-actor collaboration for improved real-world Text-to-SQL performance.
Findings
Outperforms individual methods on benchmarks
Standardizes invocation interfaces for deployment
Demonstrates effectiveness of multi-actor collaboration
Abstract
Text-to-SQL technology has evolved rapidly, with diverse academic methods achieving impressive results. However, deploying these techniques in real-world systems remains challenging due to limited integration tools. Despite these advances, we introduce Squrve, a unified, modular, and extensive Text-to-SQL framework designed to bring together research advances and real-world applications. Squrve first establishes a universal execution paradigm that standardizes invocation interfaces, then proposes a multi-actor collaboration mechanism based on seven abstracted effective atomic actor components. Experiments on widely adopted benchmarks demonstrate that the collaborative workflows consistently outperform the original individual methods, thereby opening up a new effective avenue for tackling complex real-world queries. The codes are available at https://github.com/Satissss/Squrve.
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