SQL reference

AI-SQL extends standard SQL with functions that call a language model during query execution. You can filter rows, join tables, score documents, assign labels, and extract answers using natural language instructions.

Write a query

For example, suppose you registered a reviews table with columns id and body. This query returns IDs of reviews that discuss the movie's ending:

SELECT r.id
FROM reviews r
WHERE AI.IF(PROMPT('Does this review discuss the ending of the movie?\n\n{0}', r.body))

The model reads each review and returns TRUE or FALSE. Quail keeps the rows where the answer is TRUE.

Quail supports Snowflake and BigQuery syntax:

session.sql(text, dialect="snowflake")  # AI_FILTER syntax
session.sql(text, dialect="bq")         # AI.IF syntax

The query above uses the BigQuery dialect (dialect="bq").