Opper

SQL

Natural language to SQL query generation evaluates text-to-query fidelity and schema reasoning. This task is particularly relevant for analytics chat assistants and simplified database interfaces where users need to query data using natural language. Models must understand both the intent behind the question and the structure of the underlying database schema.

SQL – openai/gpt-5-nano Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Cost

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Context

Input

Add a foreign key from completions to enrollments, linking through user_id and course_id to ensure data consistency.

Expected output

ALTER TABLE completions ADD COLUMN course_id INT, ADD CONSTRAINT fk_completions_user_course FOREIGN KEY (user_id, course_id) REFERENCES enrollments(user_id, course_id);

Model output

ALTER TABLE completions ADD COLUMN course_id INT;

UPDATE completions AS c
SET course_id = l.course_id
FROM lessons AS l
WHERE l.lesson_id = c.lesson_id;

ALTER TABLE completions ALTER COLUMN course_id SET NOT NULL;

ALTER TABLE completions
ADD CONSTRAINT fk_completions_enrollments
FOREIGN KEY (user_id, course_id)
REFERENCES enrollments(user_id, course_id)
ON UPDATE CASCADE
ON DELETE CASCADE;