Text-to-SQL systems are becoming a key interface for non-technical users to query databases using natural language. This post from the Chinese developer community walks through a complete implementation using Spring Boot for the backend and a modern frontend framework, with a large language model handling the natural language to SQL conversion. The architecture emphasizes a clean separation between the frontend, backend, and LLM service, which is critical for maintainability and scalability. Key production considerations include handling ambiguous queries, validating generated SQL, and managing API costs. For teams building similar systems, the post offers a solid starting point for architectural decisions, though it focuses more on implementation than on advanced optimization techniques like query caching or fine-tuning.
A practical look at building production-grade Text-to-SQL systems with Spring Boot and LLMs, covering architecture, integration, and deployment considerations.