MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

Understand

Recent LLM-based Text-to-SQL methods usually suffer from significant performance degradation on "huge" databases and complex user questions that require multi-step reasoning.

• Moreover, most existing methods neglect the crucial significance of LLMs utilizing external tools and model collaboration.
• To address these challenges, we introduce MAC-SQL, a novel LLM-based multi-agent collaborative framework.
• Our framework comprises a core decomposer agent for Text-to-SQL generation with few-shot chain-of-thought reasoning, accompanied by two auxiliary agents that utilize external tools or models to acquire smaller sub-databases and refine erroneous SQL queries.