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-mini Task | Opper AI

Input Tokens

0

Output Tokens

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Duration

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Cost

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Context

Input

I am in the class with teacher Amanda Svensson, I can't find the link to the video for the last lesson. Can you provide me with it?

Expected output

SELECT l.video_url FROM lessons l JOIN courses c ON l.course_id = c.course_id JOIN users u ON c.instructor_id = u.user_id WHERE u.name = 'Amanda Svensson' AND l.order_index = (SELECT MAX(order_index) FROM lessons l2 WHERE l2.course_id = c.course_id);

Model output

SELECT l.video_url FROM lessons l JOIN courses c ON l.course_id = c.course_id JOIN users instr ON c.instructor_id = instr.user_id JOIN enrollments e ON e.course_id = c.course_id WHERE instr.name = 'Amanda Svensson' AND e.user_id = $1 AND NOT l.is_draft AND l.video_url IS NOT NULL AND l.order_index = (SELECT MAX(COALESCE(order_index, 0)) FROM lessons WHERE course_id = c.course_id AND NOT is_draft) LIMIT 1;