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  <div class="hfTopbar">
    <div class="left">
      <span class="brand">🗄️ GRPO SQL Optimizer</span>
      <a class="pill" href="https://huggingface.co/spaces/laterabhi/grpo-sql-optimizer/blob/main/README.md" target="_blank" rel="noopener">📝 Writeup</a>
      <a class="pill" href="https://huggingface.co/spaces/laterabhi/grpo-sql-optimizer/blob/main/Blog.md" target="_blank" rel="noopener">📄 Blog.md</a>
      <a class="pill" href="https://huggingface.co/laterabhi/grpo-sql-optimizer" target="_blank" rel="noopener">🤗 Model</a>
      <a class="pill" href="https://github.com/OfficialAbhinavSingh/SQL-Query-Optimization-Environment-" target="_blank" rel="noopener">💻 GitHub</a>
    </div>
    <div class="muted">DuckDB-verifiable rewards · OpenEnv</div>
  </div>

  <div class="wrap">
    <h1>GRPO Training for SQL Query Optimization</h1>
    <p class="sub">
      Fine-tuned <code>Qwen/Qwen2.5-0.5B-Instruct</code> using GRPO (Group Relative Policy Optimization)
      to optimize SQL queries using a DuckDB execution environment.
    </p>

    <div class="grid">
      <div class="card">
        <h3>Overview</h3>
        <p>
          This project trains/evaluates SQL optimization with <strong>execution-grounded</strong> rewards:
          the environment executes both original and rewritten SQL on real DuckDB data, and scores
          speedup + correctness + structured diagnostics.
        </p>
        <div class="kpiRow">
          <div class="kpi">
            <div class="v">5</div>
            <div class="l">tasks (easy → expert)</div>
          </div>
          <div class="kpi">
            <div class="v">DuckDB</div>
            <div class="l">verifiable execution</div>
          </div>
          <div class="kpi">
            <div class="v">GRPO</div>
            <div class="l">group-relative RL</div>
          </div>
        </div>
      </div>

      <div class="card">
        <h3>Training curve</h3>

        <!-- Prefer local image if you uploaded it to this Space -->
        <img src="grpo_results.png" alt="GRPO training curve" />

        <p class="note" style="margin-top:10px">
          If this image ever breaks, the canonical plot is also in the GitHub repo:
          <a href="https://raw.githubusercontent.com/OfficialAbhinavSingh/SQL-Query-Optimization-Environment-/main/results/grpo_reward_curve.png" target="_blank" rel="noopener">
            results/grpo_reward_curve.png
          </a>.
        </p>
      </div>
    </div>

    <h2>Training progress (100 episodes)</h2>
    <table>
      <tr><th>Metric</th><th>Value</th></tr>
      <tr><td>Start avg (ep 1–10)</td><td>0.3090</td></tr>
      <tr><td>End avg (ep 91–100)</td><td>0.5962</td></tr>
      <tr><td><strong>Improvement</strong></td><td><strong>+93%</strong></td></tr>
    </table>

    <h2>Final evaluation (per task)</h2>
    <p class="note">
      These task scores are aligned to the GitHub repo README (source of truth). Task 5 is the expert scenario,
      so it is expected to be the lowest — that is not an error.
    </p>
    <table>
      <tr><th>Task</th><th>Difficulty</th><th>Score</th></tr>
      <tr><td>task_1_basic_antipatterns</td><td>easy</td><td><span class="ok">0.7500 ✅</span></td></tr>
      <tr><td>task_2_correlated_subqueries</td><td>medium</td><td><span class="ok">0.8313 ✅</span></td></tr>
      <tr><td>task_3_wildcard_scan</td><td>medium-hard</td><td><span class="ok">0.6563 ✅</span></td></tr>
      <tr><td>task_4_implicit_join</td><td>hard</td><td><span class="ok">0.6563 ✅</span></td></tr>
      <tr><td>task_5_window_functions</td><td>expert</td><td><span class="ok">0.6500 ✅</span></td></tr>
    </table>

    <h2>Before / After (environment-only, reproducible)</h2>
    <p class="note">
      To avoid hand-wavy baselines, we provide a reproducible before/after contrast in the GitHub repo:
      “before” = analysis-only (no optimized SQL), “after” = deterministic fallback with a real optimized query.
      Chart:
      <a href="https://raw.githubusercontent.com/OfficialAbhinavSingh/SQL-Query-Optimization-Environment-/main/results/before_after_chart.png" target="_blank" rel="noopener">
        results/before_after_chart.png
      </a>
    </p>
    <img
      src="https://raw.githubusercontent.com/OfficialAbhinavSingh/SQL-Query-Optimization-Environment-/main/results/before_after_chart.png"
      alt="Before/after chart"
    />

    <h2>Approach</h2>
    <div class="card">
      <h3>GRPO setup</h3>
      <ul class="note">
        <li><strong>Algorithm:</strong> GRPO (Group Relative Policy Optimization)</li>
        <li><strong>Base model:</strong> Qwen/Qwen2.5-0.5B-Instruct</li>
        <li><strong>Group size:</strong> 4 completions per prompt</li>
        <li><strong>Hardware:</strong> Kaggle GPU T4 x2 (see repo links)</li>
      </ul>

      <h3 style="margin-top:12px">Reward components</h3>
      <ul class="note">
        <li><code>execution_speedup</code>: measured DuckDB timing ratio</li>
        <li><code>result_correctness</code>: results match check (order-independent for large sets)</li>
        <li><code>issue_detection</code>: anti-pattern detection vs ground truth keywords</li>
        <li><code>approval_correctness</code>, <code>summary_quality</code>, <code>severity_labels</code></li>
      </ul>
    </div>

    <h2>Links</h2>
    <ul class="note">
      <li><a href="https://huggingface.co/laterabhi/grpo-sql-optimizer" target="_blank" rel="noopener">Model on Hugging Face</a></li>
      <li><a href="https://github.com/OfficialAbhinavSingh/SQL-Query-Optimization-Environment-" target="_blank" rel="noopener">GitHub repo (source of truth)</a></li>
      <li><a href="https://arxiv.org/abs/2402.03300" target="_blank" rel="noopener">GRPO paper</a></li>
    </ul>

    <footer>
      Tip: If you want all images to load instantly (no GitHub raw), upload the PNGs into this Space repo and change the <code>src</code> to local file paths.
    </footer>
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