Spaces:
Paused
Paused
Abhinav Singh commited on
Commit ·
cc0da5c
1
Parent(s): 026bc6e
feat: add OpenEnv spec, README, and gitignore
Browse files- openenv.yaml: full OpenEnv-compliant spec with observation/action
space definitions, 3 tasks (easy->medium->hard), reward schema,
and deployment config targeting HuggingFace Spaces on port 7860
- README.md: HF Space header (sdk: docker), full environment
description, action/observation space docs, task breakdown,
reward table, API endpoints, baseline scores, and setup instructions
- .gitignore: standard Python ignores (__pycache__, .env, venv, dist)
- .gitignore +12 -0
- openenv.yaml +83 -0
.gitignore
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__pycache__/
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*.py[cod]
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*$py.class
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*.egg-info/
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dist/
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build/
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.env
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.venv
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venv/
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*.log
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.DS_Store
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Thumbs.db
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openenv.yaml
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name: sql-optim-env
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version: "1.0.0"
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description: >
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An OpenEnv-compliant reinforcement learning environment where AI agents
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learn to analyze, diagnose, and optimize SQL queries. Agents identify
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performance anti-patterns — from basic SELECT * issues to advanced
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window function and correlated subquery problems — across three difficulty
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levels and produce rewritten, optimized SQL.
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tags:
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- openenv
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- sql
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- database
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- performance
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- optimization
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- llm-agent
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language: python
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framework: openenv
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observation_space:
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type: object
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fields:
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task_id: string
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task_name: string
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task_description: string
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sql_query: string
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schema_info: string
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dialect: string
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difficulty: string
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step_count: integer
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max_steps: integer
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issues_found_so_far: array
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action_space:
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type: object
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fields:
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suggestions: array
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optimized_query: string
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summary: string
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estimated_improvement: string
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approved: boolean
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reward:
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type: float
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min: 0.0
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max: 1.0
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description: >
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Composite score: issue detection (60%), optimized query quality (15%),
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approval correctness (10%), summary quality (8%),
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improvement estimate (4%), severity labels (3%).
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tasks:
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- id: task_1_basic_antipatterns
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name: "Basic SQL Anti-pattern Detection"
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difficulty: easy
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max_steps: 3
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description: "Identify SELECT *, non-SARGable predicates, and implicit type casts that prevent index usage."
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- id: task_2_join_optimization
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name: "N+1 Pattern & Join Optimization"
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difficulty: medium
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max_steps: 4
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description: "Detect correlated subqueries, missing join indexes, and inefficient sorting in complex queries."
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- id: task_3_advanced_optimization
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name: "Advanced Query & Window Function Audit"
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difficulty: hard
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max_steps: 5
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description: "Deep performance audit: JSONB index misses, CTE materialization, window function planning, lock contention, and implicit casts."
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endpoints:
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reset: POST /reset
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step: POST /step
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state: GET /state
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tasks: GET /tasks
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grader: POST /grader
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baseline: POST /baseline
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deployment:
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platform: huggingface-spaces
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port: 7860
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dockerfile: Dockerfile
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