Auto prompt sql: a resource-efficient architecture for text-to-sql translation in constrained environments

• URL: http://arxiv.org/abs/2506.03598v1
• Date: Wed, 04 Jun 2025 06:04:46 GMT
• Title: Auto prompt sql: a resource-efficient architecture for text-to-sql translation in constrained environments
• Authors: Zetong Tang, Qian Ma, Di Wu,
• Abstract summary: This paper introduces Auto Promptsql(AP-), a novel architecture designed to bridge the gap between resource-efficient small open-source models and the powerful capabilities of large closed-source models for Text-to- translation.
• Score: 6.2022166353084485
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Using the best Text-to-SQL methods in resource-constrained environments is challenging due to their reliance on resource-intensive open-source models. This paper introduces Auto Prompt SQL(AP-SQL), a novel architecture designed to bridge the gap between resource-efficient small open-source models and the powerful capabilities of large closed-source models for Text-to-SQL translation. Our method decomposes the task into schema filtering, retrieval-augmented text-to-SQL generation based on in-context examples, and prompt-driven schema linking and SQL generation. To improve schema selection accuracy, we fine-tune large language models. Crucially, we also explore the impact of prompt engineering throughout the process, leveraging Chain-of-Thought(CoT) and Graph-of-Thought(GoT) templates to significantly enhance the model's reasoning for accurate SQL generation. Comprehensive evaluations on the Spider benchmarks demonstrate the effectiveness of AP-SQL.

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