Clean repo without venv

.gitattributes

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+*.bz2 filter=lfs diff=lfs merge=lfs -text
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.gitignore

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+venv/
+venv311/
+__pycache__/
+*.pyc

Dockerfile

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+FROM python:3.11-slim
+
+LABEL maintainer="NeuroHack"
+LABEL description="SQL Debugger & Optimizer — OpenEnv"
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y --no-install-recommends curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy dependency files
+COPY requirements.txt .
+COPY pyproject.toml .
+COPY uv.lock .
+
+# Install dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy project structure
+COPY server/ ./server/
+COPY sql_debugger_env.py .
+COPY openenv.yaml .
+COPY inference.py .
+COPY README.md .
+
+EXPOSE 7860
+
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
+    CMD curl -f http://localhost:7860/health || exit 1
+
+# 🔥 IMPORTANT CHANGE
+CMD ["uvicorn", "server.app:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

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+---
+title: SQL Debugger & Optimizer
+emoji: 🛠️
+colorFrom: blue
+colorTo: indigo
+sdk: docker
+app_file: app.py
+pinned: false
+---
+
+# 🛠️ SQL Debugger & Optimizer — OpenEnv Environment
+
+> 🚀 **NeuroHack — OpenEnv Submission**
+> A real-world reinforcement learning environment where an AI agent debugs broken SQL queries using **deterministic SQLite execution** — no LLM-based scoring.
+
+---
+
+## 📋 Table of Contents
+
+- [Overview](#overview)
+- [Why This Wins](#why-this-wins)
+- [Live Demo](#live-demo)
+- [Project Structure](#project-structure)
+- [Getting Started](#getting-started)
+  - [Run Locally](#run-locally)
+  - [Docker](#docker)
+  - [API Example](#api-example)
+- [Environment Details](#environment-details)
+  - [Tasks](#tasks)
+  - [Reward System](#reward-system)
+  - [Performance](#performance)
+- [License](#license)
+
+---
+
+## Overview
+
+The **SQL Debugger & Optimizer** is an OpenEnv-compatible reinforcement learning environment where an AI agent receives broken SQL queries and must output corrected versions.
+
+The agent receives:
+- 🔴 A **broken SQL query**
+- 🗂️ The **database schema**
+- 📝 A **natural language description** of the intended behavior
+
+It must output a **corrected SQL query**, which is then:
+1. Executed against a real SQLite database
+2. Compared against the reference (correct) query output
+3. Scored with a layered reward from `0.0 → 1.0`
+
+---
+
+## Why This Wins
+
+Unlike traditional LLM-evaluated systems:
+
+| Feature | Description |
+|--------|-------------|
+| ✅ **100% Deterministic Grading** | Real SQLite execution — no subjective LLM scoring |
+| ✅ **Layered Reward System** | Syntax → Logic → Data → Optimization |
+| ✅ **Real-World Bugs** | JOIN errors, N+1 queries, SQL injection vulnerabilities |
+| ✅ **Engineering Relevance** | Mirrors production database debugging scenarios |
+| ✅ **OpenEnv-Compatible API** | Drop-in `/reset` and `/step` endpoints |
+
+---
+
+## Live Demo
+
+Open the interactive UI at:
+
+```
+http://localhost:7860/ui
+```
+
+With the UI you can:
+- Fix broken SQL queries interactively
+- View the corrected SQL output
+- See reward scores in real-time
+- Track agent performance with graphs
+
+---
+
+## Project Structure
+
+```
+sql-debugger-env/
+├── app.py                 # FastAPI server — /reset, /step, /ui endpoints
+├── sql_debugger_env.py    # Core RL environment logic & SQLite execution
+├── inference.py           # Agent inference utilities
+├── openenv.yaml           # OpenEnv environment specification
+├── requirements.txt       # Python dependencies
+├── Dockerfile             # Container build configuration
+└── README.md              # This file
+```
+
+---
+
+## Getting Started
+
+### Run Locally
+
+```bash
+pip install -r requirements.txt
+python app.py
+```
+
+Then open: [http://localhost:7860/ui](http://localhost:7860/ui)
+
+---
+
+### Docker
+
+```bash
+# Build the image
+docker build -t sql-debugger-env .
+
+# Run the container
+docker run -p 7860:7860 sql-debugger-env
+```
+
+---
+
+### API Example
+
+The environment exposes an OpenEnv-compatible REST API:
+
+```python
+import requests
+
+# 1. Start a new episode
+r = requests.post("http://localhost:7860/reset", json={"task": "medium"})
+session_id = r.json()["session_id"]
+obs = r.json()["observation"]
+
+# 2. Submit a fix action
+action = {
+    "challenge_id": obs["challenge"]["id"],
+    "fixed_sql": "SELECT users.id, orders.total FROM users JOIN orders ON users.id = orders.user_id",
+    "explanation": "Fixed JOIN logic — was using wrong foreign key",
+    "detected_issues": ["wrong_join"]
+}
+
+r = requests.post("http://localhost:7860/step", json={
+    "session_id": session_id,
+    "action": action
+})
+
+print(r.json()["reward"])   # e.g. 0.92
+```
+
+**Endpoints:**
+
+| Method | Endpoint | Description |
+|--------|----------|-------------|
+| `POST` | `/reset` | Start a new episode. Accepts `{"task": "easy" \| "medium" \| "hard"}` |
+| `POST` | `/step` | Submit a fix. Returns reward, done flag, and next observation |
+| `GET`  | `/ui`   | Interactive web interface |
+
+---
+
+## Environment Details
+
+### Tasks
+
+| Difficulty | Bug Types |
+|------------|-----------|
+| 🟢 **Easy** | Syntax errors (`SELCT`, `FORM`, missing `WHERE`) |
+| 🟡 **Medium** | JOIN logic errors, aggregation mistakes |
+| 🔴 **Hard** | N+1 query patterns, optimization issues, complex aggregations |
+
+---
+
+### Reward System
+
+Each submitted query is evaluated across multiple components:
+
+| Component | Weight | Description |
+|-----------|--------|-------------|
+| Syntax Correctness | `0.20` | Query parses and executes without error |
+| Row Count Match | `0.25` | Output row count matches reference |
+| Column Match | `0.15` | Returned columns match expected schema |
+| Data Exact Match | `0.30` | Row-by-row data comparison |
+| Security Fix | `0.10` | SQL injection or unsafe patterns resolved |
+| Optimization | `0.05` | Query avoids N+1 or redundant scans |
+| Explanation Quality | `0.05` | Detected issues and explanation provided |
+| **Total** | **1.00** | |
+
+---
+
+### Performance
+
+Benchmarks from the reference agent (`inference.py`):
+
+| Task | Score |
+|------|-------|
+| Easy | ~0.90 |
+| Medium | ~0.90 |
+| Hard | ~0.76 |
+| **Average** | 🚀 **~0.85** |
+
+---
+
+## License
+
+This project is licensed under the **MIT License** — see [`LICENSE`](LICENSE) for details.
+
+---
+
+<div align="center">
+  Built for <strong>NeuroHack</strong> · OpenEnv Track · 2025
+</div>

inference.py

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+"""
+inference.py — SQL Debugger & Optimizer Agent
+===============================================
+Runs an LLM against all 3 tasks. Emits mandatory [START]/[STEP]/[END] logs.
+
+Env vars:
+    API_BASE_URL   LLM endpoint  (default: https://router.huggingface.co/v1)
+    MODEL_NAME     Model name    (default: Qwen/Qwen2.5-72B-Instruct)
+    HF_TOKEN       API key
+"""
+from __future__ import annotations
+import json, os, textwrap
+from typing import Dict, List, Optional
+from openai import OpenAI
+from sql_debugger_env import Action, SQLDebuggerEnv
+
+API_KEY      = os.getenv("HF_TOKEN") or os.getenv("API_KEY", "")
+API_BASE_URL = os.getenv("API_BASE_URL", "https://router.huggingface.co/v1")
+MODEL_NAME   = os.getenv("MODEL_NAME",   "Qwen/Qwen2.5-72B-Instruct")
+BENCHMARK    = "sql-debugger-agent"
+TASKS        = ["easy", "medium", "hard"]
+
+client = OpenAI(api_key=API_KEY, base_url=API_BASE_URL)
+
+SYSTEM_PROMPT = textwrap.dedent("""
+    You are an expert SQL debugger and optimizer.
+    You will be given a broken SQL query, the database schema, and a description
+    of what the query SHOULD do. Your job is to fix ALL bugs.
+
+    Always respond with ONLY a JSON object — no markdown, no explanation outside JSON:
+    {
+        "challenge_id": "<id>",
+        "fixed_sql": "<your corrected SQL query>",
+        "explanation": "<brief explanation of what was wrong>",
+        "detected_issues": ["issue1", "issue2"]
+    }
+
+    Common bug types to look for:
+    - Syntax typos (SELCT, FORM, WHER)
+    - Missing GROUP BY when using aggregate functions with non-aggregate columns
+    - Wrong JOIN type (INNER vs LEFT)
+    - Wrong column in ORDER BY (ordering by raw column instead of aggregate alias)
+    - Subquery referencing wrong scope (AVG of all rows instead of filtered group)
+    - SQL injection (string concatenation of user input — fix with parameterized form)
+    - N+1 correlated subqueries (rewrite as JOIN with subquery or CTE)
+
+    Output ONLY the JSON. Nothing else.
+""").strip()
+
+
+def build_prompt(obs_dict: dict) -> str:
+    c = obs_dict["challenge"]
+    return textwrap.dedent(f"""
+        TASK: {obs_dict['task']}
+        INSTRUCTIONS: {obs_dict['instructions']}
+
+        DATABASE SCHEMA:
+        {obs_dict['schema_info']}
+
+        CHALLENGE ID: {c['id']}
+        GOAL: {c['description']}
+        DIFFICULTY: {c['difficulty']}
+
+        KNOWN BUGS (hints):
+        {chr(10).join('- ' + b for b in c['bugs'])}
+
+        HINT: {c['hint']}
+
+        BROKEN SQL TO FIX:
+        {c['broken_sql']}
+
+        Output only JSON with keys: challenge_id, fixed_sql, explanation, detected_issues
+    """).strip()
+
+
+def run_task(task_name: str) -> dict:
+    env = SQLDebuggerEnv(task=task_name)
+    obs_obj = env.reset()
+    obs = obs_obj.model_dump()
+
+    step_num = 0
+    rewards: List[float] = []
+    done = False
+    last_error = None
+
+    print(f"[START] task={task_name} env={BENCHMARK} model={MODEL_NAME}", flush=True)
+
+    while not done:
+        prompt = build_prompt(obs)
+        try:
+            resp = client.chat.completions.create(
+                model=MODEL_NAME,
+                messages=[
+                    {"role": "system", "content": SYSTEM_PROMPT},
+                    {"role": "user",   "content": prompt},
+                ],
+                max_tokens=600,
+                temperature=0.1,
+            )
+            raw = resp.choices[0].message.content or ""
+            raw = raw.strip().strip("```json").strip("```").strip()
+            action_dict = json.loads(raw)
+            action = Action(**action_dict)
+            last_error = None
+        except Exception as e:
+            last_error = str(e)[:100]
+            cid = obs["challenge"]["id"]
+            action = Action(
+                challenge_id=cid,
+                fixed_sql=obs["challenge"]["broken_sql"],
+                explanation="parse error fallback",
+                detected_issues=[],
+            )
+
+        obs_obj, reward, done, info = env.step(action)
+        obs = obs_obj.model_dump()
+        step_num += 1
+        rewards.append(reward)
+
+        action_str = f"fix(id={action.challenge_id},issues={len(action.detected_issues)})"
+        print(
+            f"[STEP] step={step_num} action={action_str} "
+            f"reward={reward:.2f} done={str(done).lower()} "
+            f"error={last_error if last_error else 'null'}",
+            flush=True,
+        )
+
+    score = env.episode_score()
+    rewards_str = ",".join(f"{r:.2f}" for r in rewards)
+    print(
+        f"[END] success={str(score >= 0.5).lower()} steps={step_num} "
+        f"score={score:.2f} rewards={rewards_str}",
+        flush=True,
+    )
+    env.close()
+    return {"task": task_name, "score": score, "steps": step_num}
+
+
+def main():
+    print(f"# SQL Debugger & Optimizer — Baseline Inference", flush=True)
+    print(f"# Model: {MODEL_NAME}  API: {API_BASE_URL}\n", flush=True)
+    results = []
+    for task in TASKS:
+        result = run_task(task)
+        results.append(result)
+        print(f"# Task '{task}' → score: {result['score']:.4f}\n", flush=True)
+
+    avg = sum(r["score"] for r in results) / len(results)
+    print("# === FINAL SUMMARY ===", flush=True)
+    for r in results:
+        print(f"#   {r['task']:8s}: {r['score']:.4f}", flush=True)
+    print(f"#   AVERAGE : {avg:.4f}", flush=True)
+
+
+if __name__ == "__main__":
+    main()

openenv.yaml

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+name: sql-debugger-agent
+version: "1.0.0"
+description: >
+  A real-world environment where an AI agent debugs broken SQL queries —
+  fixing syntax errors, logic bugs (wrong JOINs, aggregation mistakes,
+  subquery scope), performance anti-patterns (N+1 correlated subqueries),
+  and SQL injection vulnerabilities. Uses a live in-memory SQLite database
+  for 100% deterministic, execution-based grading.
+
+author: NeuroHack
+tags:
+  - openenv
+  - sql
+  - debugging
+  - optimization
+  - security
+  - real-world
+  - data-engineering
+
+tasks:
+  - name: easy
+    description: Fix SQL syntax errors — typos in keywords, missing clauses.
+    difficulty: easy
+    max_steps: 3
+    reward_range: [0.0, 1.0]
+
+  - name: medium
+    description: Fix logic bugs — wrong JOIN types, incorrect aggregation scope, bad ORDER BY.
+    difficulty: medium
+    max_steps: 3
+    reward_range: [0.0, 1.0]
+
+  - name: hard
+    description: >
+      Fix + optimize + secure: N+1 correlated subqueries, SQL injection vulnerabilities,
+      and missing column aliases. All bugs must be identified and fixed.
+    difficulty: hard
+    max_steps: 3
+    reward_range: [0.0, 1.0]
+
+interface:
+  observation: Observation
+  action: Action
+  reward: Reward
+  methods:
+    - reset
+    - step
+    - state
+
+environment:
+  python: ">=3.10"
+  framework: openenv-core
+  database: sqlite3 (in-memory, no external deps)
+  api: openai-compatible
+
+hf_space:
+  sdk: docker
+  tags:
+    - openenv

pyproject.toml

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+[project]
+name = "sql-debugger-env"
+version = "0.1.0"
+description = "SQL Debugger & Optimizer OpenEnv environment"
+authors = [{ name = "Abrar" }]
+
+dependencies = [
+  "fastapi",
+  "uvicorn",
+  "pydantic",
+  "openenv"
+]
+requires-python = ">=3.10,<3.12"
+[project.scripts]
+server = "server.app:main"
+
+[build-system]
+requires = ["setuptools", "wheel"]
+build-backend = "setuptools.build_meta"

requirements.txt

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+fastapi>=0.110.0
+uvicorn[standard]>=0.29.0
+pydantic>=2.6.0
+openai>=1.14.0
+pyyaml>=6.0
+httpx>=0.27.0

server/app.py

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+"""
+SQL Debugger & Optimizer — FastAPI Server for HF Spaces
+"""
+from __future__ import annotations
+import os
+import uuid
+from typing import Any, Dict, Optional
+
+from fastapi import FastAPI, HTTPException, Body
+from fastapi.responses import HTMLResponse
+from pydantic import BaseModel
+
+from sql_debugger_env import Action, SQLDebuggerEnv
+
+app = FastAPI(
+    title="SQL Debugger & Optimizer — OpenEnv",
+    description="Real-world SQL debugging environment for RL agent evaluation.",
+    version="1.0.0",
+)
+
+_sessions: Dict[str, SQLDebuggerEnv] = {}
+
+
+class ResetRequest(BaseModel):
+    task: str = "easy"
+    session_id: Optional[str] = None
+
+
+class StepRequest(BaseModel):
+    session_id: str
+    action: Dict[str, Any]
+
+
+# ✅ HEALTH CHECK
+@app.get("/health")
+def health():
+    return {"status": "ok"}
+
+
+# ✅ RESET
+@app.post("/reset")
+def reset(req: Optional[ResetRequest] = Body(default=None)):
+    task = req.task if req else "easy"
+    session_id = req.session_id if req else str(uuid.uuid4())
+
+    env = SQLDebuggerEnv(task=task)
+    _sessions[session_id] = env
+    obs = env.reset()
+
+    return {
+        "session_id": session_id,
+        "observation": obs.model_dump()
+    }
+
+
+# ✅ STEP
+@app.post("/step")
+def step(req: StepRequest):
+    env = _sessions.get(req.session_id)
+    if not env:
+        raise HTTPException(status_code=404, detail="Session not found.")
+
+    action = Action(**req.action)
+    obs, reward, done, info = env.step(action)
+
+    return {
+        "observation": obs.model_dump(),
+        "reward": reward,
+        "done": done,
+        "info": info
+    }
+
+
+# ✅ ROOT UI
+@app.get("/", response_class=HTMLResponse)
+def ui():
+    return r"""<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8"/>
+<meta name="viewport" content="width=device-width, initial-scale=1.0"/>
+<title>SQL Debugger & Optimizer</title>
+<link href="https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;600;700&family=Syne:wght@700;800&display=swap" rel="stylesheet"/>
+<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
+<style>
+  :root {
+    --bg:       #080c14;
+    --surface:  #0d1525;
+    --card:     #111b2e;
+    --border:   #1e2f4a;
+    --accent:   #00d4ff;
+    --accent2:  #7c3aed;
+    --green:    #22d3a0;
+    --yellow:   #fbbf24;
+    --red:      #f87171;
+    --text:     #e2eaf8;
+    --muted:    #5a7092;
+    --glow:     0 0 24px rgba(0,212,255,.25);
+  }
+  *{box-sizing:border-box;margin:0;padding:0;}
+  html,body{height:100%;background:var(--bg);color:var(--text);font-family:'JetBrains Mono',monospace;}
+
+  /* ── Background grid ── */
+  body::before{
+    content:'';position:fixed;inset:0;z-index:0;
+    background-image:
+      linear-gradient(rgba(0,212,255,.04) 1px,transparent 1px),
+      linear-gradient(90deg,rgba(0,212,255,.04) 1px,transparent 1px);
+    background-size:40px 40px;
+    pointer-events:none;
+  }
+
+  .wrapper{position:relative;z-index:1;max-width:1200px;margin:0 auto;padding:32px 24px 60px;}
+
+  /* ── Header ── */
+  header{display:flex;align-items:center;gap:16px;margin-bottom:36px;}
+  .logo-box{
+    width:52px;height:52px;border-radius:14px;
+    background:linear-gradient(135deg,var(--accent2),var(--accent));
+    display:flex;align-items:center;justify-content:center;font-size:22px;
+    box-shadow:var(--glow);
+  }
+  header h1{font-family:'Syne',sans-serif;font-size:26px;font-weight:800;letter-spacing:-.5px;}
+  header h1 span{color:var(--accent);}
+  .badge{
+    margin-left:auto;padding:5px 14px;border-radius:20px;font-size:11px;font-weight:700;
+    background:rgba(0,212,255,.1);border:1px solid rgba(0,212,255,.3);color:var(--accent);
+    letter-spacing:1.5px;text-transform:uppercase;
+  }
+
+  /* ── Difficulty row ── */
+  .diff-row{display:flex;gap:12px;margin-bottom:28px;flex-wrap:wrap;}
+  .diff-btn{
+    flex:1;min-width:120px;padding:13px 0;border-radius:12px;border:1.5px solid var(--border);
+    background:var(--card);cursor:pointer;font-family:'Syne',sans-serif;font-size:13px;font-weight:700;
+    color:var(--muted);letter-spacing:.8px;transition:all .2s;position:relative;overflow:hidden;
+  }
+  .diff-btn::after{
+    content:'';position:absolute;inset:0;opacity:0;
+    background:linear-gradient(135deg,rgba(0,212,255,.12),rgba(124,58,237,.12));
+    transition:opacity .2s;
+  }
+  .diff-btn:hover::after,.diff-btn.active::after{opacity:1;}
+  .diff-btn:hover,.diff-btn.active{border-color:var(--accent);color:var(--text);transform:translateY(-2px);box-shadow:var(--glow);}
+  .diff-btn.active{color:var(--accent);}
+  .diff-btn .pill{
+    display:inline-block;margin-left:8px;padding:2px 8px;border-radius:8px;font-size:10px;
+    vertical-align:middle;
+  }
+  .pill-easy{background:rgba(34,211,160,.15);color:var(--green);}
+  .pill-medium{background:rgba(251,191,36,.15);color:var(--yellow);}
+  .pill-hard{background:rgba(248,113,113,.15);color:var(--red);}
+  .pill-custom{background:rgba(124,58,237,.2);color:#a78bfa;}
+
+  /* ── Main grid ── */
+  .grid{display:grid;grid-template-columns:1fr 1fr;gap:20px;margin-bottom:20px;}
+  @media(max-width:768px){.grid{grid-template-columns:1fr;}}
+
+  /* ── Card ── */
+  .card{
+    background:var(--card);border:1.5px solid var(--border);border-radius:16px;
+    padding:20px;
+  }
+  .card-title{
+    font-family:'Syne',sans-serif;font-size:11px;font-weight:800;letter-spacing:2px;
+    text-transform:uppercase;color:var(--muted);margin-bottom:14px;display:flex;align-items:center;gap:8px;
+  }
+  .card-title .dot{width:8px;height:8px;border-radius:50%;background:var(--accent);box-shadow:0 0 8px var(--accent);}
+
+  /* ── Textarea / pre ── */
+  textarea{
+    width:100%;height:150px;background:#060d1a;border:1.5px solid var(--border);
+    border-radius:10px;color:var(--text);font-family:'JetBrains Mono',monospace;
+    font-size:13px;padding:14px;resize:vertical;outline:none;transition:border-color .2s;
+    line-height:1.6;
+  }
+  textarea:focus{border-color:var(--accent);}
+  pre{
+    background:#060d1a;border:1.5px solid var(--border);border-radius:10px;
+    padding:14px;min-height:80px;font-size:13px;line-height:1.6;white-space:pre-wrap;
+    word-break:break-all;color:var(--green);overflow:auto;
+  }
+
+  /* ── Custom SQL ── */
+  .custom-area{display:none;margin-bottom:20px;}
+  .custom-area.show{display:block;}
+  .custom-area textarea{height:80px;}
+  .custom-label{font-size:11px;color:var(--muted);margin-bottom:6px;letter-spacing:1px;}
+
+  /* ── Run button ── */
+  .run-row{display:flex;gap:12px;margin-bottom:20px;align-items:center;}
+  .run-btn{
+    flex:1;padding:14px;border-radius:12px;border:none;cursor:pointer;
+    background:linear-gradient(135deg,var(--accent2),var(--accent));
+    font-family:'Syne',sans-serif;font-size:14px;font-weight:800;color:#fff;
+    letter-spacing:.5px;transition:all .2s;box-shadow:0 4px 24px rgba(0,212,255,.2);
+  }
+  .run-btn:hover{transform:translateY(-2px);box-shadow:0 8px 32px rgba(0,212,255,.35);}
+  .run-btn:active{transform:translateY(0);}
+
+  /* ── Score strip ── */
+  .score-strip{
+    display:flex;gap:14px;margin-bottom:20px;flex-wrap:wrap;
+  }
+  .score-card{
+    flex:1;min-width:110px;background:var(--card);border:1.5px solid var(--border);
+    border-radius:14px;padding:16px 14px;text-align:center;transition:all .3s;
+  }
+  .score-card.lit{border-color:var(--accent);box-shadow:var(--glow);}
+  .score-card .sc-val{font-family:'Syne',sans-serif;font-size:28px;font-weight:800;color:var(--accent);}
+  .score-card .sc-lbl{font-size:10px;color:var(--muted);margin-top:4px;letter-spacing:1.5px;text-transform:uppercase;}
+
+  /* ── Progress bar ── */
+  .prog-wrap{background:var(--surface);border-radius:99px;height:10px;overflow:hidden;margin-top:8px;}
+  .prog-bar{
+    height:100%;border-radius:99px;width:0%;
+    background:linear-gradient(90deg,var(--accent2),var(--accent));
+    transition:width .8s cubic-bezier(.4,0,.2,1);
+    box-shadow:0 0 12px var(--accent);
+  }
+
+  /* ── Status badge ── */
+  .status-pill{
+    display:inline-flex;align-items:center;gap:6px;padding:6px 14px;
+    border-radius:20px;font-size:12px;font-weight:700;letter-spacing:.5px;
+    margin-bottom:8px;
+  }
+  .status-pill.win{background:rgba(34,211,160,.15);border:1px solid var(--green);color:var(--green);}
+  .status-pill.lose{background:rgba(248,113,113,.12);border:1px solid var(--red);color:var(--red);}
+  .status-pill.neutral{background:rgba(91,112,146,.12);border:1px solid var(--muted);color:var(--muted);}
+
+  /* ── Chart ── */
+  .chart-wrap{position:relative;height:220px;}
+
+  /* ── Issues list ── */
+  .issues{list-style:none;}
+  .issues li{
+    padding:8px 12px;border-radius:8px;margin-bottom:6px;font-size:12px;
+    background:rgba(248,113,113,.08);border-left:3px solid var(--red);color:#fca5a5;
+  }
+
+  /* ── Log ── */
+  .log-wrap{
+    background:#060d1a;border:1.5px solid var(--border);border-radius:12px;
+    max-height:180px;overflow-y:auto;padding:12px;
+  }
+  .log-line{font-size:11px;line-height:1.8;color:var(--muted);}
+  .log-line span{color:var(--accent);}
+  .log-line.ok span{color:var(--green);}
+  .log-line.err span{color:var(--red);}
+
+  /* ── Explanation ── */
+  .explain-input{
+    width:100%;padding:10px 14px;border-radius:10px;border:1.5px solid var(--border);
+    background:#060d1a;color:var(--text);font-family:'JetBrains Mono',monospace;font-size:12px;
+    outline:none;transition:border-color .2s;
+  }
+  .explain-input:focus{border-color:var(--accent);}
+
+  /* ── Hackathon meter ── */
+  .hack-bar{
+    background:var(--card);border:1.5px solid var(--border);border-radius:16px;
+    padding:20px;margin-bottom:20px;
+  }
+  .hack-bar .hb-title{font-family:'Syne',sans-serif;font-size:12px;font-weight:800;letter-spacing:2px;color:var(--muted);text-transform:uppercase;margin-bottom:12px;}
+  .hack-bar .hb-row{display:flex;justify-content:space-between;margin-bottom:8px;font-size:12px;}
+  .hack-bar .hb-val{color:var(--accent);font-weight:700;}
+  .hack-meter{position:relative;height:22px;background:var(--surface);border-radius:99px;overflow:hidden;}
+  .hack-fill{
+    height:100%;border-radius:99px;width:0%;
+    background:linear-gradient(90deg,#f43f5e,#fbbf24,#22d3a0,#00d4ff);
+    transition:width 1s cubic-bezier(.4,0,.2,1);
+    box-shadow:0 0 16px rgba(0,212,255,.4);
+  }
+  .hack-labels{display:flex;justify-content:space-between;margin-top:6px;font-size:10px;color:var(--muted);}
+
+  /* ── Animations ── */
+  @keyframes fadeUp{from{opacity:0;transform:translateY(12px);}to{opacity:1;transform:translateY(0);}}
+  .card,.score-card,.hack-bar{animation:fadeUp .4s ease both;}
+
+  /* ── Spinner ── */
+  @keyframes spin{to{transform:rotate(360deg);}}
+  .spinner{width:18px;height:18px;border:2px solid rgba(255,255,255,.2);border-top-color:#fff;border-radius:50%;animation:spin .6s linear infinite;display:none;}
+  .loading .spinner{display:block;}
+  .loading .btn-label{display:none;}
+</style>
+</head>
+<body>
+<div class="wrapper">
+
+  <!-- Header -->
+  <header>
+    <div class="logo-box">⚡</div>
+    <div>
+      <h1>SQL <span>Debugger</span> & Optimizer</h1>
+      <div style="font-size:11px;color:var(--muted);margin-top:2px;">RL Environment · OpenEnv Protocol</div>
+    </div>
+    <div class="badge">v1.0.0</div>
+  </header>
+
+  <!-- Difficulty Buttons -->
+  <div class="diff-row">
+    <button class="diff-btn active" data-task="easy" onclick="selectTask('easy',this)">
+      🟢 EASY <span class="pill pill-easy">+100</span>
+    </button>
+    <button class="diff-btn" data-task="medium" onclick="selectTask('medium',this)">
+      🟡 MEDIUM <span class="pill pill-medium">+200</span>
+    </button>
+    <button class="diff-btn" data-task="hard" onclick="selectTask('hard',this)">
+      🔴 HARD <span class="pill pill-hard">+400</span>
+    </button>
+    <button class="diff-btn" data-task="custom" onclick="selectTask('custom',this)">
+      🟣 CUSTOM <span class="pill pill-custom">+∞</span>
+    </button>
+  </div>
+
+  <!-- Custom SQL entry -->
+  <div class="custom-area" id="customArea">
+    <div class="custom-label">PASTE YOUR BROKEN SQL BELOW</div>
+    <textarea id="customSql" placeholder="-- Paste broken SQL here for custom challenge..."></textarea>
+  </div>
+
+  <!-- Explanation -->
+  <div style="margin-bottom:16px;">
+    <div class="custom-label" style="margin-bottom:6px;">FIX EXPLANATION (boosts score)</div>
+    <input class="explain-input" id="explanation" placeholder="e.g. Fixed typo in FROM clause, added missing JOIN condition..."/>
+  </div>
+
+  <!-- Run -->
+  <div class="run-row">
+    <button class="run-btn" id="runBtn" onclick="runFix()">
+      <div class="spinner" id="spinner"></div>
+      <span class="btn-label">⚡ RUN FIX &amp; SCORE</span>
+    </button>
+  </div>
+
+  <!-- Hackathon Meter -->
+  <div class="hack-bar">
+    <div class="hb-title">🏆 Hackathon Score Meter</div>
+    <div class="hb-row">
+      <span>Cumulative Score</span><span class="hb-val" id="hackScore">0</span>
+    </div>
+    <div class="hack-meter"><div class="hack-fill" id="hackFill"></div></div>
+    <div class="hack-labels">
+      <span>0</span><span>Participant</span><span>Good</span><span>Finalist</span><span>🥇 Winner</span>
+    </div>
+  </div>
+
+  <!-- Score Strip -->
+  <div class="score-strip">
+    <div class="score-card" id="scReward">
+      <div class="sc-val" id="valReward">—</div>
+      <div class="sc-lbl">Last Reward</div>
+    </div>
+    <div class="score-card" id="scTotal">
+      <div class="sc-val" id="valTotal">0</div>
+      <div class="sc-lbl">Total Score</div>
+    </div>
+    <div class="score-card" id="scRuns">
+      <div class="sc-val" id="valRuns">0</div>
+      <div class="sc-lbl">Runs</div>
+    </div>
+    <div class="score-card" id="scBest">
+      <div class="sc-val" id="valBest">—</div>
+      <div class="sc-lbl">Best Reward</div>
+    </div>
+    <div class="score-card" id="scAcc">
+      <div class="sc-val" id="valAcc">0%</div>
+      <div class="sc-lbl">Win Rate</div>
+    </div>
+  </div>
+
+  <!-- Main Grid -->
+  <div class="grid">
+    <!-- Left: SQL panels -->
+    <div>
+      <div class="card" style="margin-bottom:16px;">
+        <div class="card-title"><span class="dot"></span>BROKEN SQL (from challenge)</div>
+        <textarea id="sql" placeholder="Click a difficulty button above to load a challenge..."></textarea>
+      </div>
+      <div class="card">
+        <div class="card-title"><span class="dot" style="background:var(--green);box-shadow:0 0 8px var(--green);"></span>FIXED SQL OUTPUT</div>
+        <div id="statusPill"></div>
+        <pre id="out">-- Fixed SQL will appear here after running ⚡</pre>
+        <div style="margin-top:12px;">
+          <div class="custom-label" style="margin-bottom:4px;">SCORE PROGRESS</div>
+          <div class="prog-wrap"><div class="prog-bar" id="progBar"></div></div>
+        </div>
+      </div>
+    </div>
+
+    <!-- Right: Charts & logs -->
+    <div>
+      <div class="card" style="margin-bottom:16px;">
+        <div class="card-title"><span class="dot" style="background:var(--accent2);box-shadow:0 0 8px var(--accent2);"></span>REWARD HISTORY</div>
+        <div class="chart-wrap"><canvas id="rewardChart"></canvas></div>
+      </div>
+      <div class="card" style="margin-bottom:16px;">
+        <div class="card-title"><span class="dot" style="background:var(--yellow);box-shadow:0 0 8px var(--yellow);"></span>DIFFICULTY BREAKDOWN</div>
+        <div class="chart-wrap"><canvas id="diffChart"></canvas></div>
+      </div>
+      <div class="card">
+        <div class="card-title"><span class="dot"></span>SESSION LOG</div>
+        <div class="log-wrap" id="log">
+          <div class="log-line">Waiting for first run…</div>
+        </div>
+      </div>
+    </div>
+  </div>
+
+  <!-- Issues -->
+  <div class="card">
+    <div class="card-title"><span class="dot" style="background:var(--red);box-shadow:0 0 8px var(--red);"></span>DETECTED ISSUES</div>
+    <ul class="issues" id="issueList">
+      <li>No issues detected yet — run a fix to analyse SQL.</li>
+    </ul>
+  </div>
+
+</div>
+
+<script>
+/* ─── State ─── */
+let sid = null, challenge = null;
+let currentTask = 'easy';
+let totalScore = 0, runs = 0, wins = 0, bestReward = null;
+const rewardHistory = [];
+const diffScores = { easy:0, medium:0, hard:0, custom:0 };
+
+const THRESHOLDS = { easy:0.6, medium:0.6, hard:0.6, custom:0.5 };
+
+/* ─── Charts ─── */
+const chartDefaults = {
+  color: '#e2eaf8',
+  plugins:{ legend:{ labels:{ color:'#5a7092', font:{ family:'JetBrains Mono', size:10 } } } },
+  scales:{
+    x:{ ticks:{ color:'#5a7092', font:{ family:'JetBrains Mono', size:10 } }, grid:{ color:'rgba(30,47,74,.6)' } },
+    y:{ ticks:{ color:'#5a7092', font:{ family:'JetBrains Mono', size:10 } }, grid:{ color:'rgba(30,47,74,.6)' } }
+  }
+};
+
+const rewardCtx = document.getElementById('rewardChart').getContext('2d');
+const rewardChart = new Chart(rewardCtx, {
+  type: 'line',
+  data:{
+    labels:[],
+    datasets:[{
+      label:'Reward',
+      data:[],
+      borderColor:'#00d4ff',
+      backgroundColor:'rgba(0,212,255,.08)',
+      borderWidth:2,
+      pointBackgroundColor:'#00d4ff',
+      pointRadius:4,
+      tension:.4,
+      fill:true
+    }]
+  },
+  options:{ ...chartDefaults, animation:{ duration:600 }, plugins:{ legend:{ display:false } } }
+});
+
+const diffCtx = document.getElementById('diffChart').getContext('2d');
+const diffChart = new Chart(diffCtx, {
+  type:'bar',
+  data:{
+    labels:['Easy','Medium','Hard','Custom'],
+    datasets:[{
+      label:'Score',
+      data:[0,0,0,0],
+      backgroundColor:['rgba(34,211,160,.7)','rgba(251,191,36,.7)','rgba(248,113,113,.7)','rgba(167,139,250,.7)'],
+      borderColor:['#22d3a0','#fbbf24','#f87171','#a78bfa'],
+      borderWidth:1.5,
+      borderRadius:6
+    }]
+  },
+  options:{ ...chartDefaults, animation:{ duration:600 }, plugins:{ legend:{ display:false } } }
+});
+
+/* ─── Select task ─── */
+function selectTask(task, btn) {
+  currentTask = task;
+  document.querySelectorAll('.diff-btn').forEach(b=>b.classList.remove('active'));
+  btn.classList.add('active');
+
+  const ca = document.getElementById('customArea');
+  if(task==='custom') { ca.classList.add('show'); }
+  else { ca.classList.remove('show'); }
+
+  if(task !== 'custom') loadChallenge(task);
+}
+
+/* ─── Load challenge ─── */
+async function loadChallenge(task) {
+  try {
+    const r = await fetch('/reset',{
+      method:'POST',
+      headers:{'Content-Type':'application/json'},
+      body: JSON.stringify({ task })
+    });
+    const d = await r.json();
+    sid = d.session_id;
+    challenge = d.observation.challenge;
+    document.getElementById('sql').value = challenge.broken_sql || '-- No SQL provided';
+    addLog('ok', `Challenge loaded · task=${task} · id=${challenge.id}`);
+  } catch(e) {
+    addLog('err', `Failed to load challenge: ${e.message}`);
+  }
+}
+
+/* ─── Run Fix ─── */
+async function runFix() {
+  const btn = document.getElementById('runBtn');
+  btn.classList.add('loading');
+
+  try {
+    let brokenSql = document.getElementById('sql').value.trim();
+    let customSql = document.getElementById('customSql').value.trim();
+    const explanation = document.getElementById('explanation').value.trim() || 'auto fix';
+
+    // For custom, auto-load a session first
+    if(currentTask === 'custom') {
+      if(!customSql) { addLog('err','Paste your broken SQL in the custom box.'); btn.classList.remove('loading'); return; }
+      // Load a session for custom (use easy as base env)
+      const rr = await fetch('/reset',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({task:'easy'})});
+      const rd = await rr.json();
+      sid = rd.session_id;
+      challenge = rd.observation.challenge;
+      brokenSql = customSql;
+      challenge.broken_sql = customSql;
+    }
+
+    if(!sid || !challenge) { addLog('err','Click a difficulty button first.'); btn.classList.remove('loading'); return; }
+
+    /* ── Smart fixer ── */
+    const fixed = smartFix(brokenSql);
+    const issues = detectIssues(brokenSql);
+
+    const resp = await fetch('/step',{
+      method:'POST',
+      headers:{'Content-Type':'application/json'},
+      body: JSON.stringify({
+        session_id: sid,
+        action:{
+          challenge_id: challenge.id,
+          fixed_sql: fixed,
+          explanation: explanation,
+          detected_issues: issues
+        }
+      })
+    });
+    const data = await resp.json();
+    const reward = data.reward ?? 0;
+
+    /* ── Update UI ── */
+    updateScores(reward, issues, fixed, data);
+
+    /* ── Reload next challenge ── */
+    if(currentTask !== 'custom') loadChallenge(currentTask);
+
+  } catch(e) {
+    addLog('err', `Error: ${e.message}`);
+  } finally {
+    btn.classList.remove('loading');
+  }
+}
+
+/* ─── Smart SQL fixer (high-reward logic) ─── */
+function smartFix(sql) {
+  let s = sql;
+
+  // Keyword typos
+  const fixes = [
+    [/\bSELCT\b/gi,'SELECT'],[/\bSELECT\b/gi,'SELECT'],
+    [/\bFORM\b/g,'FROM'],[/\bFROM\b/gi,'FROM'],
+    [/\bWHER\b/g,'WHERE'],[/\bWHERE\b/gi,'WHERE'],
+    [/\bORDER\s+BU\b/gi,'ORDER BY'],[/\bGROUP\s+BU\b/gi,'GROUP BY'],
+    [/\bHAVNG\b/gi,'HAVING'],[/\bHAVING\b/gi,'HAVING'],
+    [/\bINNER\s+JION\b/gi,'INNER JOIN'],[/\bLEFT\s+JION\b/gi,'LEFT JOIN'],
+    [/\bJOIN\s+ON\b/gi,'JOIN'],[/\bINSERT\s+IN\b/g,'INSERT INTO'],
+    [/\bDELETE\s+FORM\b/gi,'DELETE FROM'],
+    [/\bUPDATE\b/gi,'UPDATE'],[/\bSET\b/gi,'SET'],
+    [/\bDISTINT\b/gi,'DISTINCT'],[/\bCOUNT\s*\(\s*\)/gi,'COUNT(*)'],
+    [/\bNULL\b/gi,'NULL'],[/\bIS\s+NOT\s+NUL\b/gi,'IS NOT NULL'],
+    [/\bIS\s+NUL\b/gi,'IS NULL'],
+    [/\bLIMT\b/gi,'LIMIT'],[/\bOFFST\b/gi,'OFFSET'],
+    [/\bUNION\s+AL\b/gi,'UNION ALL'],
+    [/\bCREATE\s+TABL\b/gi,'CREATE TABLE'],
+    [/\bALTER\s+TABL\b/gi,'ALTER TABLE'],
+    [/\bDROP\s+TABL\b/gi,'DROP TABLE'],
+    [/\bVARCAHR\b/gi,'VARCHAR'],[/\bINTEGR\b/gi,'INTEGER'],
+    [/==\s*/g,'= '],[/\bAND\s+AND\b/gi,'AND'],
+    [/\bOR\s+OR\b/gi,'OR'],[/\bNOT\s+NOT\b/gi,'NOT'],
+    [/\bTRUNCATE\b/gi,'TRUNCATE'],[/\bTRANSACTION\b/gi,'TRANSACTION'],
+  ];
+
+  fixes.forEach(([pat,rep])=>{ s = s.replace(pat,rep); });
+
+  // Unclosed quotes fix
+  const sq = (s.match(/'/g)||[]).length;
+  if(sq%2!==0) s += "'";
+
+  // Unclosed parens fix
+  const op=(s.match(/\(/g)||[]).length, cl=(s.match(/\)/g)||[]).length;
+  if(op>cl) s += ')'.repeat(op-cl);
+  if(cl>op) s = '('.repeat(cl-op) + s;
+
+  // Missing semicolon
+  if(!/;\s*$/.test(s.trim())) s = s.trim() + ';';
+
+  // Normalise whitespace
+  s = s.replace(/\s{2,}/g,' ').trim();
+
+  return s;
+}
+
+/* ─── Detect issues ─── */
+function detectIssues(sql) {
+  const issues = [];
+  if(/\bSELCT\b/i.test(sql)) issues.push('typo:SELCT→SELECT');
+  if(/\bFORM\b/g.test(sql)) issues.push('typo:FORM→FROM');
+  if(/\bWHER\b/g.test(sql)) issues.push('typo:WHER→WHERE');
+  if(/==/.test(sql)) issues.push('operator:==→=');
+  if((/\(/g.exec(sql)||[]).length !== (/\)/g.exec(sql)||[]).length) issues.push('syntax:unbalanced_parentheses');
+  if((/'/g.exec(sql)||[]).length%2!==0) issues.push('syntax:unclosed_string_literal');
+  if(!/;\s*$/.test(sql.trim())) issues.push('syntax:missing_semicolon');
+  if(/\bLEFT\s+JION\b/i.test(sql)||/\bINNER\s+JION\b/i.test(sql)) issues.push('typo:JION→JOIN');
+  if(/\bHAVNG\b/i.test(sql)) issues.push('typo:HAVNG→HAVING');
+  if(/\bINTEGR\b/i.test(sql)) issues.push('typo:INTEGR→INTEGER');
+  if(!issues.length) issues.push('no_issues_detected');
+  return issues;
+}
+
+/* ─── Update all UI ─── */
+function updateScores(reward, issues, fixed, data) {
+  runs++;
+  totalScore += reward;
+  const isWin = reward >= (THRESHOLDS[currentTask] || 0.6);
+  if(isWin) wins++;
+  if(bestReward===null || reward > bestReward) bestReward = reward;
+
+  diffScores[currentTask] += reward;
+
+  /* Score cards */
+  document.getElementById('valReward').textContent = reward.toFixed ? reward.toFixed(3) : reward;
+  document.getElementById('valTotal').textContent = totalScore.toFixed(2);
+  document.getElementById('valRuns').textContent = runs;
+  document.getElementById('valBest').textContent = bestReward.toFixed ? bestReward.toFixed(3) : bestReward;
+  document.getElementById('valAcc').textContent = Math.round((wins/runs)*100)+'%';
+
+  document.getElementById('scReward').classList.add('lit');
+  setTimeout(()=>document.getElementById('scReward').classList.remove('lit'),1200);
+
+  /* Progress bar */
+  const pct = Math.min(100, (reward/(THRESHOLDS[currentTask]||1))*100);
+  document.getElementById('progBar').style.width = pct+'%';
+
+  /* Hackathon meter */
+  const hackPct = Math.min(100, (totalScore / (runs * 1)) * 100);
+  document.getElementById('hackFill').style.width = hackPct+'%';
+  document.getElementById('hackScore').textContent = totalScore.toFixed(2);
+
+  /* Status pill */
+  const pill = document.getElementById('statusPill');
+  if(isWin){
+    pill.innerHTML = '<div class="status-pill win">✅ WINNING SCORE ACHIEVED</div>';
+  } else {
+    pill.innerHTML = '<div class="status-pill lose">⚠ BELOW THRESHOLD — TRY AGAIN</div>';
+  }
+
+  /* Output */
+  document.getElementById('out').textContent = fixed;
+
+  /* Reward chart */
+  rewardHistory.push(reward);
+  rewardChart.data.labels.push(`Run ${runs}`);
+  rewardChart.data.datasets[0].data.push(reward);
+  if(rewardHistory.length > 20) {
+    rewardChart.data.labels.shift();
+    rewardChart.data.datasets[0].data.shift();
+  }
+  rewardChart.update();
+
+  /* Diff chart */
+  diffChart.data.datasets[0].data = [
+    diffScores.easy, diffScores.medium, diffScores.hard, diffScores.custom
+  ];
+  diffChart.update();
+
+  /* Issues list */
+  const ul = document.getElementById('issueList');
+  ul.innerHTML = issues.map(i=>`<li>${i.replace(/:/g,' → ')}</li>`).join('');
+
+  /* Log */
+  addLog(isWin?'ok':'err',
+    `run=${runs} task=${currentTask} reward=${typeof reward==='number'?reward.toFixed(3):reward} done=${data.done||false}`);
+}
+
+/* ─── Log helper ─── */
+function addLog(type, msg) {
+  const box = document.getElementById('log');
+  const ts = new Date().toLocaleTimeString();
+  const div = document.createElement('div');
+  div.className = `log-line ${type}`;
+  div.innerHTML = `<span>[${ts}]</span> ${msg}`;
+  box.appendChild(div);
+  box.scrollTop = box.scrollHeight;
+  // Clear placeholder
+  const first = box.querySelector('.log-line:not(.ok):not(.err)');
+  if(first && box.children.length > 1) first.remove();
+}
+
+/* ─── Initial load ─── */
+loadChallenge('easy');
+</script>
+</body>
+</html>"""
+
+
+def main():
+    import uvicorn
+    uvicorn.run("server.app:app", host="0.0.0.0", port=int(os.getenv("PORT", 7860)))
+
+
+if __name__ == "__main__":
+    main()

sql_debugger_env.py

@@ -0,0 +1,613 @@
+"""
+SQL Query Debugger & Optimizer — OpenEnv Environment
+======================================================
+A real-world environment where an AI agent is given broken, inefficient,
+or insecure SQL queries and must:
+  - Fix syntax errors
+  - Correct logical bugs (wrong JOIN, missing GROUP BY, etc.)
+  - Optimize for performance (remove N+1 patterns, add proper indexes hints)
+  - Detect & fix SQL injection vulnerabilities
+
+This is a task real data analysts and backend engineers do every single day.
+
+Tasks:
+  easy   — Fix obvious syntax errors in simple SELECT queries
+  medium — Fix logic bugs (wrong JOINs, incorrect aggregations, missing clauses)
+  hard   — Fix + optimize + secure (injection detection, N+1 queries, subquery rewrites)
+
+Why this beats other environments:
+  - 100% deterministic graders (execute real SQL in SQLite, compare results)
+  - Rich partial rewards at every step (syntax → logic → performance → security)
+  - Real engineering pain point that Meta/HF engineers deal with daily
+  - Novel domain — not in OpenEnv Hub yet
+"""
+
+from __future__ import annotations
+
+import re
+import sqlite3
+import textwrap
+from typing import Any, Dict, List, Literal, Optional, Tuple
+
+from pydantic import BaseModel, Field
+
+# ---------------------------------------------------------------------------
+# Database Schema (in-memory SQLite — fully reproducible)
+# ---------------------------------------------------------------------------
+
+SCHEMA_SQL = """
+CREATE TABLE IF NOT EXISTS users (
+    id INTEGER PRIMARY KEY,
+    name TEXT NOT NULL,
+    email TEXT UNIQUE NOT NULL,
+    department TEXT NOT NULL,
+    salary REAL NOT NULL,
+    hire_date TEXT NOT NULL,
+    manager_id INTEGER REFERENCES users(id)
+);
+
+CREATE TABLE IF NOT EXISTS orders (
+    id INTEGER PRIMARY KEY,
+    user_id INTEGER NOT NULL REFERENCES users(id),
+    product TEXT NOT NULL,
+    amount REAL NOT NULL,
+    status TEXT NOT NULL CHECK(status IN ('pending','completed','cancelled')),
+    created_at TEXT NOT NULL
+);
+
+CREATE TABLE IF NOT EXISTS products (
+    id INTEGER PRIMARY KEY,
+    name TEXT NOT NULL,
+    category TEXT NOT NULL,
+    price REAL NOT NULL,
+    stock INTEGER NOT NULL DEFAULT 0
+);
+"""
+
+SEED_SQL = """
+INSERT INTO users VALUES
+(1,'Alice Chen','alice@co.com','Engineering',95000,'2021-03-01',NULL),
+(2,'Bob Smith','bob@co.com','Engineering',82000,'2022-06-15',1),
+(3,'Carol Jones','carol@co.com','Marketing',74000,'2020-01-10',NULL),
+(4,'Dan Park','dan@co.com','Engineering',91000,'2019-08-22',1),
+(5,'Eva Liu','eva@co.com','Marketing',68000,'2023-02-28',3),
+(6,'Frank Wu','frank@co.com','HR',61000,'2021-11-05',NULL),
+(7,'Grace Kim','grace@co.com','Engineering',103000,'2018-05-14',1),
+(8,'Hank Patel','hank@co.com','Marketing',72000,'2022-09-30',3);
+
+INSERT INTO products VALUES
+(1,'Laptop Pro','Electronics',1299.99,45),
+(2,'Wireless Mouse','Electronics',29.99,200),
+(3,'Standing Desk','Furniture',549.00,30),
+(4,'Monitor 4K','Electronics',699.99,60),
+(5,'Ergonomic Chair','Furniture',399.00,25),
+(6,'USB Hub','Electronics',49.99,150);
+
+INSERT INTO orders VALUES
+(1,1,'Laptop Pro',1299.99,'completed','2024-01-15'),
+(2,2,'Wireless Mouse',29.99,'completed','2024-01-20'),
+(3,1,'Monitor 4K',699.99,'completed','2024-02-01'),
+(4,3,'Ergonomic Chair',399.00,'pending','2024-02-10'),
+(5,4,'Standing Desk',549.00,'completed','2024-02-14'),
+(6,2,'USB Hub',49.99,'cancelled','2024-02-20'),
+(7,5,'Wireless Mouse',29.99,'completed','2024-03-01'),
+(8,7,'Laptop Pro',1299.99,'completed','2024-03-05'),
+(9,1,'USB Hub',49.99,'completed','2024-03-10'),
+(10,3,'Laptop Pro',1299.99,'pending','2024-03-15'),
+(11,4,'Wireless Mouse',29.99,'completed','2024-03-18'),
+(12,6,'Ergonomic Chair',399.00,'completed','2024-03-20');
+"""
+
+def make_db() -> sqlite3.Connection:
+    """Create fresh in-memory SQLite database."""
+    conn = sqlite3.connect(":memory:")
+    conn.row_factory = sqlite3.Row
+    conn.executescript(SCHEMA_SQL)
+    conn.executescript(SEED_SQL)
+    conn.commit()
+    return conn
+
+def run_query(conn: sqlite3.Connection, sql: str) -> Tuple[List[Dict], Optional[str]]:
+    """Execute SQL, return (rows, error). rows=[] on error."""
+    try:
+        cur = conn.execute(sql)
+        rows = [dict(r) for r in cur.fetchall()]
+        return rows, None
+    except Exception as e:
+        return [], str(e)
+
+# ---------------------------------------------------------------------------
+# Pydantic Models
+# ---------------------------------------------------------------------------
+
+class SQLChallenge(BaseModel):
+    id: str
+    description: str          # What the query SHOULD do (plain English)
+    broken_sql: str           # The buggy SQL given to the agent
+    expected_row_count: int   # How many rows the correct query returns
+    expected_columns: List[str]  # Column names of correct output
+    hint: str                 # Nudge without giving the answer
+    difficulty: str
+    bugs: List[str]           # Human-readable bug descriptions (shown to agent)
+
+
+class Observation(BaseModel):
+    challenge: SQLChallenge
+    schema_info: str          # DDL so agent knows table structure
+    current_step: int
+    max_steps: int
+    task: str
+    previous_attempts: List[Dict[str, Any]] = Field(default_factory=list)
+    instructions: str
+
+
+class Action(BaseModel):
+    challenge_id: str
+    fixed_sql: str                        # The agent's corrected SQL
+    explanation: Optional[str] = None     # Why the original was wrong
+    detected_issues: List[str] = Field(default_factory=list)  # e.g. ["missing_group_by","sql_injection"]
+
+
+class Reward(BaseModel):
+    value: float
+    breakdown: Dict[str, float]
+
+
+# ---------------------------------------------------------------------------
+# Challenges Dataset
+# ---------------------------------------------------------------------------
+
+CHALLENGES: List[Dict] = [
+
+    # =========== EASY ===========
+    {
+        "id": "sq001",
+        "difficulty": "easy",
+        "description": "Get the names and salaries of all employees in the Engineering department, ordered by salary descending.",
+        "broken_sql": """
+            SELCT name, salary FORM users
+            WHER department = 'Engineering'
+            ORDER BY salary DESC
+        """.strip(),
+        "expected_row_count": 4,
+        "expected_columns": ["name", "salary"],
+        "hint": "Look carefully at the SQL keywords — any typos?",
+        "bugs": [
+            "Typo: SELCT should be SELECT",
+            "Typo: FORM should be FROM",
+            "Typo: WHER should be WHERE",
+        ],
+    },
+    {
+        "id": "sq002",
+        "difficulty": "easy",
+        "description": "Count how many orders each user has made, showing user_id and their order count.",
+        "broken_sql": """
+            SELECT user_id, COUNT(*) as order_count
+            FROM orders
+        """.strip(),
+        "expected_row_count": 7,
+        "expected_columns": ["user_id", "order_count"],
+        "hint": "When using COUNT with a non-aggregate column, something is missing.",
+        "bugs": ["Missing GROUP BY user_id — without it, SQLite returns only 1 row instead of per-user counts"],
+    },
+    {
+        "id": "sq003",
+        "difficulty": "easy",
+        "description": "Get the total revenue from all completed orders.",
+        "broken_sql": """
+            SELECT SUM(amount) AS total_revenue
+            FROM orders
+            WHERE status = 'complete'
+        """.strip(),
+        "expected_row_count": 1,
+        "expected_columns": ["total_revenue"],
+        "hint": "Check the exact value used in the WHERE condition against the schema.",
+        "bugs": ["Wrong status value: 'complete' should be 'completed' (as defined in the CHECK constraint)"],
+    },
+
+    # =========== MEDIUM ===========
+    {
+        "id": "sq004",
+        "difficulty": "medium",
+        "description": "Get each user's name and the total amount they've spent on completed orders. Include users who have no completed orders (show 0 for them).",
+        "broken_sql": """
+            SELECT u.name, SUM(o.amount) AS total_spent
+            FROM orders o
+            INNER JOIN users u ON u.id = o.user_id
+            WHERE o.status = 'completed'
+            GROUP BY u.name
+        """.strip(),
+        "expected_row_count": 8,
+        "expected_columns": ["name", "total_spent"],
+        "hint": "The problem statement says 'Include users who have no completed orders' — does INNER JOIN do that?",
+        "bugs": [
+            "INNER JOIN excludes users with no completed orders — should be LEFT JOIN from users to orders",
+            "The WHERE clause further removes non-matching rows — it should move to an ON clause or be handled with COALESCE",
+        ],
+    },
+    {
+        "id": "sq005",
+        "difficulty": "medium",
+        "description": "Find all Engineering employees who earn more than the average salary of their own department.",
+        "broken_sql": """
+            SELECT name, salary
+            FROM users
+            WHERE department = 'Engineering'
+            AND salary > (SELECT AVG(salary) FROM users)
+        """.strip(),
+        "expected_row_count": 2,
+        "expected_columns": ["name", "salary"],
+        "hint": "The subquery calculates something — but is it the average of the right group?",
+        "bugs": [
+            "Subquery uses AVG(salary) across ALL departments, not just Engineering",
+            "Fix: WHERE department = 'Engineering' AND salary > (SELECT AVG(salary) FROM users WHERE department = 'Engineering')",
+        ],
+    },
+    {
+        "id": "sq006",
+        "difficulty": "medium",
+        "description": "Get the top 3 products by total revenue from completed orders.",
+        "broken_sql": """
+            SELECT product, SUM(amount) AS revenue
+            FROM orders
+            WHERE status = 'completed'
+            GROUP BY product
+            ORDER BY amount DESC
+            LIMIT 3
+        """.strip(),
+        "expected_row_count": 3,
+        "expected_columns": ["product", "revenue"],
+        "hint": "The ORDER BY is using a column — but which column should you order by to rank by total revenue?",
+        "bugs": [
+            "ORDER BY amount DESC orders by the raw column, not the aggregated revenue",
+            "Fix: ORDER BY revenue DESC (or ORDER BY SUM(amount) DESC)",
+        ],
+    },
+
+    # =========== HARD ===========
+    {
+        "id": "sq007",
+        "difficulty": "hard",
+        "description": "For each department, show the department name, number of employees, average salary, and highest salary. Only include departments with more than 1 employee.",
+        "broken_sql": """
+            SELECT department,
+                   COUNT(id),
+                   AVG(salary) AS avg_salary,
+                   MAX(salary)
+            FROM users
+            GROUP BY department
+            HAVING COUNT(*) > 1
+            ORDER BY avg_salary
+        """.strip(),
+        "expected_row_count": 2,
+        "expected_columns": ["department", "COUNT(id)", "avg_salary", "MAX(salary)"],
+        "hint": "The query runs but has style/clarity issues AND a subtle ordering issue. Also check column aliases.",
+        "bugs": [
+            "COUNT(id) and MAX(salary) have no aliases — hard to read, unpredictable column names in results",
+            "ORDER BY avg_salary is ascending by default — descending is typically more useful for salary reports",
+            "Minor: COUNT(id) should be COUNT(*) or COUNT(1) for clarity",
+        ],
+    },
+    {
+        "id": "sq008",
+        "difficulty": "hard",
+        "description": "SECURITY: A web app builds this query using user input for `dept`. Find and fix the SQL injection vulnerability. The query should return employee names for a given department.",
+        "broken_sql": """
+            SELECT name FROM users WHERE department = '\" + dept + \"'
+        """.strip(),
+        "expected_row_count": 4,
+        "expected_columns": ["name"],
+        "hint": "String concatenation of user input into SQL = SQL injection. The fix is parameterized queries.",
+        "bugs": [
+            "SQL injection vulnerability: user input `dept` is directly concatenated into the query string",
+            "Fix: Use parameterized query: SELECT name FROM users WHERE department = ? with parameters=(dept,)",
+            "For this environment, rewrite as: SELECT name FROM users WHERE department = 'Engineering'",
+        ],
+    },
+    {
+        "id": "sq009",
+        "difficulty": "hard",
+        "description": "Rewrite this inefficient N+1 style subquery pattern into a single efficient JOIN query. Get user names and their most recent order's product name and amount.",
+        "broken_sql": """
+            SELECT
+                u.name,
+                (SELECT product FROM orders WHERE user_id = u.id ORDER BY created_at DESC LIMIT 1) AS last_product,
+                (SELECT amount FROM orders WHERE user_id = u.id ORDER BY created_at DESC LIMIT 1) AS last_amount
+            FROM users u
+        """.strip(),
+        "expected_row_count": 8,
+        "expected_columns": ["name", "last_product", "last_amount"],
+        "hint": "Two correlated subqueries hit the orders table twice per user. Use a CTE or subquery with ROW_NUMBER() or a ranked join instead.",
+        "bugs": [
+            "N+1 query pattern: two correlated subqueries each scan orders once per user = O(n) full scans",
+            "Fix: Use a single subquery that gets the latest order per user, then LEFT JOIN it",
+        ],
+    },
+]
+
+CHALLENGE_MAP: Dict[str, Dict] = {c["id"]: c for c in CHALLENGES}
+
+# Correct reference SQL for each challenge (used internally for grading)
+REFERENCE_SQL: Dict[str, str] = {
+    "sq001": "SELECT name, salary FROM users WHERE department = 'Engineering' ORDER BY salary DESC",
+    "sq002": "SELECT user_id, COUNT(*) as order_count FROM orders GROUP BY user_id",
+    "sq003": "SELECT SUM(amount) AS total_revenue FROM orders WHERE status = 'completed'",
+    "sq004": """
+        SELECT u.name, COALESCE(SUM(o.amount), 0) AS total_spent
+        FROM users u
+        LEFT JOIN orders o ON u.id = o.user_id AND o.status = 'completed'
+        GROUP BY u.id, u.name
+    """,
+    "sq005": """
+        SELECT name, salary FROM users
+        WHERE department = 'Engineering'
+        AND salary > (SELECT AVG(salary) FROM users WHERE department = 'Engineering')
+    """,
+    "sq006": """
+        SELECT product, SUM(amount) AS revenue
+        FROM orders WHERE status = 'completed'
+        GROUP BY product ORDER BY revenue DESC LIMIT 3
+    """,
+    "sq007": """
+        SELECT department, COUNT(*) AS employee_count, AVG(salary) AS avg_salary, MAX(salary) AS max_salary
+        FROM users GROUP BY department HAVING COUNT(*) > 1 ORDER BY avg_salary DESC
+    """,
+    "sq008": "SELECT name FROM users WHERE department = 'Engineering'",
+    "sq009": """
+        SELECT u.name, latest.product AS last_product, latest.amount AS last_amount
+        FROM users u
+        LEFT JOIN (
+            SELECT user_id, product, amount,
+                   ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY created_at DESC) AS rn
+            FROM orders
+        ) latest ON latest.user_id = u.id AND latest.rn = 1
+    """,
+}
+
+# =========== Task Config ===========
+TASK_CONFIGS = {
+    "easy":   {"challenge_ids": ["sq001", "sq002", "sq003"], "max_steps": 3},
+    "medium": {"challenge_ids": ["sq004", "sq005", "sq006"], "max_steps": 3},
+    "hard":   {"challenge_ids": ["sq007", "sq008", "sq009"], "max_steps": 3},
+}
+
+SCHEMA_INFO = textwrap.dedent("""
+    TABLE users(id, name, email, department, salary, hire_date, manager_id)
+      - department: 'Engineering' | 'Marketing' | 'HR'
+      - salary: REAL
+      - manager_id: FK → users.id (nullable)
+
+    TABLE orders(id, user_id, product, amount, status, created_at)
+      - status: 'pending' | 'completed' | 'cancelled'
+      - user_id: FK → users.id
+
+    TABLE products(id, name, category, price, stock)
+      - category: 'Electronics' | 'Furniture'
+""").strip()
+
+INSTRUCTIONS = {
+    "easy": (
+        "EASY TASK — Fix SQL Syntax Errors\n"
+        "Each challenge gives you a broken SQL query with typos or missing keywords.\n"
+        "Fix the SQL so it runs correctly and returns the expected results.\n"
+        "Set fixed_sql to your corrected query."
+    ),
+    "medium": (
+        "MEDIUM TASK — Fix Logic Bugs\n"
+        "Each query runs without error but produces WRONG results due to logic bugs:\n"
+        "wrong JOIN type, wrong column in ORDER BY, missing GROUP BY, wrong subquery scope.\n"
+        "Fix the SQL to return the correct, expected result set."
+    ),
+    "hard": (
+        "HARD TASK — Fix, Optimize & Secure\n"
+        "Each query has logic bugs AND performance/security issues:\n"
+        "SQL injection vulnerabilities, N+1 correlated subqueries, missing aliases.\n"
+        "Fix ALL issues. For SQL injection: rewrite using safe parameterized form.\n"
+        "For N+1 queries: rewrite as a single efficient JOIN. List all detected_issues."
+    ),
+}
+
+
+# ---------------------------------------------------------------------------
+# Environment
+# ---------------------------------------------------------------------------
+
+class SQLDebuggerEnv:
+    """OpenEnv-compliant SQL Debugger & Optimizer environment."""
+
+    def __init__(self, task: str = "easy"):
+        if task not in TASK_CONFIGS:
+            raise ValueError(f"Unknown task '{task}'. Choose: {list(TASK_CONFIGS)}")
+        self.task = task
+        self._cfg = TASK_CONFIGS[task]
+        self._challenges: List[SQLChallenge] = []
+        self._step = 0
+        self._done = False
+        self._history: List[Dict] = []
+        self._results: Dict[str, Dict] = {}
+        self._db: Optional[sqlite3.Connection] = None
+        self.reset()
+
+    # ------------------------------------------------------------------
+    # OpenEnv interface
+    # ------------------------------------------------------------------
+
+    def reset(self) -> Observation:
+        self._db = make_db()
+        self._challenges = [
+            SQLChallenge(**CHALLENGE_MAP[cid])
+            for cid in self._cfg["challenge_ids"]
+        ]
+        self._step = 0
+        self._done = False
+        self._history = []
+        self._results = {}
+        return self._make_observation(0)
+
+    def step(self, action: Action) -> Tuple[Observation, float, bool, Dict]:
+        if self._done:
+            raise RuntimeError("Episode done. Call reset().")
+
+        self._step += 1
+        challenge = self._find_challenge(action.challenge_id)
+        idx = self._challenge_index(action.challenge_id)
+
+        if challenge is None or idx is None:
+            reward = -0.1
+            info = {"error": "invalid challenge_id", "breakdown": {}}
+        else:
+            breakdown = self._grade(challenge, action)
+            reward = max(0.0, min(1.0, sum(breakdown.values())))
+            info = {"breakdown": breakdown, "step": self._step}
+            self._results[action.challenge_id] = {
+                "action": action.model_dump(),
+                "reward": reward,
+                "breakdown": breakdown,
+            }
+
+        self._history.append({
+            "step": self._step,
+            "challenge_id": action.challenge_id,
+            "reward": reward,
+            "info": info,
+        })
+
+        next_idx = min(idx + 1 if idx is not None else 0, len(self._challenges) - 1)
+        self._done = (
+            self._step >= self._cfg["max_steps"]
+            or len(self._results) >= len(self._challenges)
+        )
+
+        obs = self._make_observation(next_idx if not self._done else idx)
+        return obs, round(reward, 4), self._done, info
+
+    def state(self) -> Dict[str, Any]:
+        return {
+            "task": self.task,
+            "step": self._step,
+            "done": self._done,
+            "challenges_total": len(self._challenges),
+            "challenges_solved": len(self._results),
+            "history": self._history,
+        }
+
+    def close(self):
+        if self._db:
+            self._db.close()
+
+    def episode_score(self) -> float:
+        if not self._results:
+            return 0.0
+        total = sum(r["reward"] for r in self._results.values())
+        return round(total / len(self._challenges), 4)
+
+    # ------------------------------------------------------------------
+    # Grading (deterministic — runs real SQL)
+    # ------------------------------------------------------------------
+
+    def _grade(self, challenge: SQLChallenge, action: Action) -> Dict[str, float]:
+        bd: Dict[str, float] = {}
+        fixed_sql = action.fixed_sql.strip()
+
+        # 1. Syntax check — does the fixed SQL run at all?
+        rows, error = run_query(self._db, fixed_sql)
+        if error:
+            bd["syntax_error"] = 0.0
+            bd["parse_penalty"] = -0.05
+            return bd
+        bd["syntax_ok"] = 0.20
+
+        # 2. Row count match
+        ref_rows, _ = run_query(self._db, REFERENCE_SQL[challenge.id])
+        if len(rows) == len(ref_rows):
+            bd["row_count_correct"] = 0.25
+        elif abs(len(rows) - len(ref_rows)) <= 1:
+            bd["row_count_close"] = 0.10
+
+        # 3. Column names match
+        if rows and ref_rows:
+            pred_cols = set(rows[0].keys())
+            ref_cols = set(ref_rows[0].keys())
+            col_overlap = len(pred_cols & ref_cols) / max(len(ref_cols), 1)
+            bd["columns"] = round(col_overlap * 0.15, 4)
+
+        # 4. Data correctness — compare sorted string representations
+        if rows and ref_rows and len(rows) == len(ref_rows):
+            pred_str = sorted(str(sorted(r.items())) for r in rows)
+            ref_str  = sorted(str(sorted(r.items())) for r in ref_rows)
+            if pred_str == ref_str:
+                bd["data_exact"] = 0.30
+            else:
+                # Partial: at least first-column values match
+                pred_first = sorted(str(list(r.values())[0]) for r in rows)
+                ref_first  = sorted(str(list(r.values())[0]) for r in ref_rows)
+                if pred_first == ref_first:
+                    bd["data_partial"] = 0.15
+
+        # 5. Security grading (hard task: injection)
+        if challenge.id == "sq008":
+            sql_lower = fixed_sql.lower()
+            injection_pattern = "dept"
+            if injection_pattern not in fixed_sql and "concat" not in sql_lower:
+                bd["injection_removed"] = 0.10
+            # Reward parameterized hint in explanation
+            if action.explanation and any(
+                kw in action.explanation.lower()
+                for kw in ["parameterized", "prepared", "placeholder", "?", "injection"]
+            ):
+                bd["security_explanation"] = 0.05
+
+        # 6. Optimization grading (hard task: N+1)
+        if challenge.id == "sq009":
+            sql_lower = fixed_sql.lower()
+            # Penalize correlated subquery pattern still present
+            if "select" in sql_lower[sql_lower.find("select")+6:]:  # nested SELECT
+                subq_count = sql_lower.count("select")
+                if subq_count <= 2:  # CTE or single subquery = OK
+                    bd["optimization_ok"] = 0.05
+                else:
+                    bd["n_plus_1_penalty"] = -0.10
+            if "join" in sql_lower:
+                bd["uses_join"] = 0.05
+
+        # 7. Explanation quality bonus
+        if action.explanation and len(action.explanation.split()) >= 8:
+            bd["explanation_bonus"] = 0.05
+
+        # 8. Bug detection quality (hard task)
+        if self.task == "hard" and action.detected_issues:
+            bd["issues_detected"] = min(0.05, len(action.detected_issues) * 0.02)
+
+        return bd
+
+    # ------------------------------------------------------------------
+    # Helpers
+    # ------------------------------------------------------------------
+
+    def _find_challenge(self, cid: str) -> Optional[SQLChallenge]:
+        for c in self._challenges:
+            if c.id == cid:
+                return c
+        return None
+
+    def _challenge_index(self, cid: str) -> Optional[int]:
+        for i, c in enumerate(self._challenges):
+            if c.id == cid:
+                return i
+        return None
+
+    def _make_observation(self, idx: int) -> Observation:
+        challenge = self._challenges[min(idx, len(self._challenges) - 1)]
+        return Observation(
+            challenge=challenge,
+            schema_info=SCHEMA_INFO,
+            current_step=self._step,
+            max_steps=self._cfg["max_steps"],
+            task=self.task,
+            previous_attempts=[
+                h for h in self._history
+                if h["challenge_id"] == challenge.id
+            ],
+            instructions=INSTRUCTIONS[self.task],
+        )

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