Building Preset AI Assist: Bringing Text-to-SQL to Superset

Preset's AI Assist is a groundbreaking Text-to-SQL solution that utilizes Language Learning Models (LLMs) to transform natural language into SQL queries, addressing the challenges of bridging human language fluidity with SQL precision. Built on advanced LLM research, AI Assist integrates vector representations and cosine similarity to match user queries with relevant database metadata, ensuring accurate and efficient data retrieval. The development process highlighted the importance of prompt engineering and the need for a robust accuracy evaluation framework, leading to a 75% accuracy target across various SQL dialects. AI Assist's implementation includes a Retrieval-augmented Generation (RAG) architecture to track and cache database metadata, using pgvector for high-speed similarity search within Postgres. This innovative approach not only enhances data interaction but also sets the stage for the future of Business Intelligence, enabling seamless SQL query generation and promoting a more data-driven culture by democratizing data access for users of varying SQL proficiency.

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