Text2SQL semantic parsing method for domain large language model

The invention discloses a Text2SQL semantic parsing method oriented to a domain large language model. The method comprises the following steps: S1, connecting a domain database and storing database mode information; s2, constructing a knowledge base based on the domain database and the domain background knowledge, and mounting the knowledge base into the large language model; s3, generating a Text-SQL (Structured Query Language) data set on the basis of an SQL-to-Text model; s4, performing fine adjustment, evaluation and optimization on the large language model by using the Text-SQL data set, and constructing a high-performance Text 2Sql model; s5, inputting a natural language question and optimizing the natural language question based on Prompt and a domain knowledge base; and S6, analyzing semantics through a Text2Sql model, and designing a Prompt reasoning result based on requirements. According to the method, natural language problem input is optimized based on Prompt, pre-training and fine tuning are car