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| name: sql-optim-env | |
| version: "2.0.0" | |
| description: > | |
| An OpenEnv-compliant reinforcement learning environment where AI agents | |
| learn to diagnose and optimize SQL queries. Unlike any other submission, | |
| optimized queries are ACTUALLY EXECUTED against a DuckDB in-memory | |
| database with realistic synthetic data (500k orders, 1M events). | |
| Reward is computed from real execution speedup + result correctness — | |
| not keyword heuristics. Five tasks from easy anti-patterns to expert | |
| window function audits. | |
| tags: | |
| - openenv | |
| - sql | |
| - database | |
| - performance | |
| - optimization | |
| - duckdb | |
| - execution-grounded | |
| - llm-agent | |
| language: python | |
| framework: openenv | |
| observation_space: | |
| type: object | |
| fields: | |
| task_id: string | |
| task_name: string | |
| task_description: string | |
| sql_query: string | |
| schema_info: string | |
| dialect: string | |
| difficulty: string | |
| step_count: integer | |
| max_steps: integer | |
| issues_found_so_far: array | |
| last_execution: object | |
| action_space: | |
| type: object | |
| fields: | |
| suggestions: array | |
| optimized_query: string | |
| summary: string | |
| estimated_improvement: string | |
| approved: boolean | |
| reward: | |
| type: float | |
| min: 0.0 | |
| max: 1.0 | |
| description: > | |
| Execution-grounded composite score: | |
| Real Speedup (35%) — actual DuckDB timing ratio, | |
| Result Correctness (20%) — both queries return identical data, | |
| Issue Detection (25%) — keyword match vs ground truth, | |
| Approval Correctness (8%), Summary Quality (7%), Severity Labels (5%). | |
| tasks: | |
| - id: task_1_basic_antipatterns | |
| name: "Basic SQL Anti-pattern Detection" | |
| difficulty: easy | |
| max_steps: 3 | |
| description: "SELECT *, CAST on filter column, YEAR() function — 3 classic anti-patterns on 500k rows" | |
| - id: task_2_correlated_subqueries | |
| name: "N+1 Correlated Subquery Elimination" | |
| difficulty: medium | |
| max_steps: 4 | |
| description: "3 correlated subqueries causing ~10M row reads — rewrite to single aggregation JOIN" | |
| - id: task_3_wildcard_scan | |
| name: "Wildcard LIKE & Projection Optimization" | |
| difficulty: medium-hard | |
| max_steps: 4 | |
| description: "Leading-wildcard LIKE on 1M events, SELECT *, pre-filter push-down" | |
| - id: task_4_implicit_join | |
| name: "Implicit Cross Join & Scalar Subquery Elimination" | |
| difficulty: hard | |
| max_steps: 5 | |
| description: "Comma-syntax join risk + 2 correlated global aggregations — rewrite with CTE" | |
| - id: task_5_window_functions | |
| name: "Window Function & Full-Scan Audit" | |
| difficulty: expert | |
| max_steps: 5 | |
| description: "5 window functions over 1M unfiltered rows including a global RANK() sort" | |
| endpoints: | |
| reset: POST /reset | |
| step: POST /step | |
| state: GET /state | |
| tasks: GET /tasks | |
| grader: POST /grader | |
| baseline: POST /baseline | |
| execute: POST /execute | |
| leaderboard: GET /leaderboard | |
| deployment: | |
| platform: huggingface-spaces | |
| port: 7860 | |
| dockerfile: Dockerfile | |