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| title: SQL Correction RL Environment | |
| emoji: 🛢️ | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: docker | |
| pinned: false | |
| tags: | |
| - openenv | |
| # SQL Correction RL Environment | |
| An **OpenEnv-compliant** reinforcement learning environment where an AI agent | |
| learns to fix broken SQL queries — a real task that developers face every day. | |
| --- | |
| ## Description & Motivation | |
| SQL errors are one of the most common and costly mistakes in software development. | |
| This environment trains agents to identify and correct SQL syntax and logical | |
| errors, ranging from simple typos to complex multi-join query reconstruction. | |
| The environment provides **partial progress signals** at every step; the agent | |
| receives graded feedback even for near-correct answers, enabling meaningful | |
| learning across the full trajectory rather than sparse end-of-episode rewards. | |
| --- | |
| ## Observation Space | |
| | Field | Type | Description | | |
| |--------------------|-----------------|----------------------------------------------------------| | |
| | `task_id` | string | Unique identifier for the current task instance | | |
| | `broken_query` | string | The malformed SQL query the agent must fix | | |
| | `schema_context` | string or null | Table/column definitions (provided for medium/hard tasks)| | |
| | `error_hint` | string or null | Plain-language hint about the error (easy tasks only) | | |
| | `step_number` | integer | Current step within the episode | | |
| | `previous_attempt` | string or null | The agent's SQL output from the previous step | | |
| | `feedback` | string or null | Grader feedback on the previous attempt | | |
| ## Action Space | |
| | Field | Type | Description | | |
| |--------------------|--------|------------------------------------| | |
| | `corrected_query` | string | The agent's corrected SQL query | | |
| --- | |
| ## Tasks | |
| | Name | Difficulty | Max Steps | Description | | |
| |----------|------------|-----------|-------------| | |
| | `easy` | Easy | 5 | Fix a single syntax error (e.g. `FORM` → `FROM`). Hint provided. | | |
| | `medium` | Medium | 6 | Fix multiple errors including missing keywords and wrong clauses. Schema provided, no hint. | | |
| | `hard` | Hard | 8 | Fix complex multi-join queries with subtle errors and wrong clause ordering. Schema provided, no hint. | | |
| --- | |
| ## Reward Function | |
| | Score | Condition | | |
| |-------|-----------| | |
| | `1.0` | Exact match after normalization (perfect fix) | | |
| | `0.7` | All correct tokens present, structure slightly off | | |
| | `0.5` | Mostly correct — small errors remain | | |
| | `0.3` | Partial fix — several errors remain | | |
| | `0.0` | Query still incorrect | | |
| Episodes terminate when reward = 1.0 (success) or max_steps is reached. | |
| --- | |
| ## Setup & Usage | |
| ### Local Development | |
| ```bash | |
| # Clone and install | |
| git clone https://huggingface.co/spaces/YOUR_USERNAME/sql-correction-env | |
| cd sql-correction-env | |
| pip install -r requirements.txt | |
| # Start the server | |
| uvicorn server:app --host 0.0.0.0 --port 7860 | |
| # Test endpoints | |
| curl -X POST http://localhost:7860/reset \ | |
| -H "Content-Type: application/json" -d '{"task_name": "easy"}' | |
| curl -X POST http://localhost:7860/step \ | |
| -H "Content-Type: application/json" \ | |
| -d '{"corrected_query": "SELECT * FROM users WHERE id = 1;"}' | |
| curl -X POST http://localhost:7860/state \ | |
| -H "Content-Type: application/json" -d '{}' | |
| ``` | |
| ### Docker | |
| ```bash | |
| docker build -t sql-correction-env . | |
| docker run -p 7860:7860 \ | |
| -e HF_TOKEN=your_token \ | |
| -e MODEL_NAME=Qwen/Qwen2.5-72B-Instruct \ | |
| sql-correction-env | |
| ``` | |
| ### Running Inference | |
| ```bash | |
| export HF_TOKEN=your_token | |
| export API_BASE_URL=https://router.huggingface.co/v1 | |
| export MODEL_NAME=Qwen/Qwen2.5-72B-Instruct | |
| export ENV_URL=http://localhost:7860 | |
| # Run each task | |
| SQL_ENV_TASK=easy python inference.py | |
| SQL_ENV_TASK=medium python inference.py | |
| SQL_ENV_TASK=hard python inference.py | |
| ``` | |
| --- | |
| ## Baseline Scores | |
| | Task | Model | Avg Score | Notes | | |
| |--------|------------------------|-----------|-------| | |
| | easy | Qwen/Qwen2.5-72B | ~0.85 | Single typo fix, hint provided | | |
| | medium | Qwen/Qwen2.5-72B | ~0.62 | Multi-error, schema-guided | | |
| | hard | Qwen/Qwen2.5-72B | ~0.38 | Complex multi-join, no hint | | |
| *Run `inference.py` against the live Space to reproduce these scores.* | |
| --- | |
| ## API Endpoints | |
| | Method | Path | Description | | |
| |--------|-----------|------------------------------------| | |
| | POST | `/reset` | Start new episode, returns observation | | |
| | POST | `/step` | Submit action, returns result | | |
| | POST | `/state` | Get current episode state | | |
| | GET | `/health` | Health check | | |