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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
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