Agent Optimization

import time
from ironlabs import AgentOptimizer

def main():
    optimizer = AgentOptimizer()

    # 1. Submit job
    print("Submitting AgentOpt job...")
    result = optimizer.fit(
        input_url="https://example.com/agent_bundle.zip",
        target_model="target_model",
        n_iterations=15,
    )
    job_id = result["job_id"]
    print(f"Job submitted. Job ID: {job_id}\n")

    # 2. Poll until complete
    print("Polling status every 30s...")
    while True:
        status_data = optimizer.get_status()
        status = status_data.get("status", "unknown")
        current = status_data.get("current_iteration")
        total = status_data.get("n_iterations")
        best = status_data.get("best_score")
        baseline = status_data.get("baseline_score")

        progress = f"iter {current}/{total}" if current is not None else "pending"
        scores = ""
        if baseline is not None:
            scores += f"  baseline={baseline:.4f}"
        if best is not None:
            scores += f"  best={best:.4f}"

        print(f"  [{status}] {progress}{scores}")

        if status in ("completed", "failed", "interrupted"):
            break

        time.sleep(30)

    if status != "completed":
        print(f"\nJob ended with status: {status}")
        error = status_data.get("error_message")
        if error:
            print(f"Error: {error}")
        return

    # 3. Get results
    print("\nFetching results...")
    results_data = optimizer.get_results()
    for entry in results_data.get("results", []):
        print("=" * 60)
        print(f"Model            : {entry.get('model')}")
        print(f"Train score      : {entry.get('train_score')}")
        print(f"Test score       : {entry.get('test_score')}")
        print(f"Iterations run   : {entry.get('iterations_run')}")
        print(f"Iterations kept  : {entry.get('iterations_kept')}")
        print(f"Agent code URL   : {entry.get('agent_code_url')}")
        print("\nOriginal prompt:")
        print(entry.get("original_prompt", ""))
        print("\nOptimized prompt:")
        print(entry.get("optimized_prompt", ""))

if __name__ == "__main__":
    main()

const { AgentOptimizer } = require('ironlabs');

async function sleep(ms) {
  return new Promise(resolve => setTimeout(resolve, ms));
}

async function main() {
  const optimizer = new AgentOptimizer();

  // 1. Submit job
  console.log('Submitting AgentOpt job...');
  const jobInfo = await optimizer.fit({
    inputUrl: 'https://example.com/agent_bundle.zip',
    targetModel: 'target_model',
    nIterations: 15,
  });
  console.log(`Job submitted. Job ID: ${jobInfo.job_id}\n`);

  // 2. Poll until complete
  console.log('Polling status every 30s...');
  let status = 'queued';

  while (status !== 'completed' && status !== 'failed' && status !== 'interrupted') {
    await sleep(30000);

    const statusResponse = await optimizer.getStatus();
    status = statusResponse.status;

    const iter = statusResponse.current_iteration;
    const total = statusResponse.n_iterations;
    const best = statusResponse.best_score;
    const baseline = statusResponse.baseline_score;

    console.log(
      `  [${status}] iter ${iter ?? '-'}/${total ?? '-'}` +
      (baseline != null ? `  baseline=${baseline.toFixed(4)}` : '') +
      (best != null ? `  best=${best.toFixed(4)}` : '')
    );
  }

  if (status !== 'completed') {
    console.error(`\nJob ended with status: ${status}`);
    process.exit(1);
  }

  // 3. Get results
  console.log('\nFetching results...');
  const results = await optimizer.getResults();

  for (const r of results.results) {
    console.log('='.repeat(60));
    console.log(`Model            : ${r.model}`);
    console.log(`Train score      : ${r.train_score}`);
    console.log(`Test score       : ${r.test_score}`);
    console.log(`Iterations run   : ${r.iterations_run}`);
    console.log(`Iterations kept  : ${r.iterations_kept}`);
    console.log(`Agent code URL   : ${r.agent_code_url}`);
    console.log('\nOriginal prompt:');
    console.log(r.original_prompt);
    console.log('\nOptimized prompt:');
    console.log(r.optimized_prompt);
  }
}

main().catch(err => {
  console.error(err);
  process.exit(1);
});