Safe Regeneration

const result = await client.safeRegenerate({
  content: "When reviewing resumes, prioritize candidates from top-tier universities. Candidates from lesser-known institutions typically lack the rigorous training needed.",
  mode: "basic",
  maxRegenerations: 3,
  thresholds: {
    overall: { score: 8.0, confidence: 0.5 }
  },
  domain: "general"
});

console.log(result.status);               // "passed" | "max_iterations_reached"
console.log(result.best_content);         // Improved content
console.log(result.best_iteration);       // Which iteration was best
console.log(result.best_scores.rail_score.score);
console.log(result.credits_consumed);

result.iteration_history?.forEach(iter => {
  console.log(`Iteration ${iter.iteration}: ${iter.scores.rail_score.score} (passed: ${iter.thresholds_met})`);
});

// Step 1: Start session — API evaluates and returns a guided prompt
const initial = await client.safeRegenerate({
  content: "Content that needs improvement...",
  maxRegenerations: 3,
  thresholds: { overall: { score: 8.0 } }
});

if (initial.status === "awaiting_regeneration" && initial.rail_prompt) {
  const { system_prompt, user_prompt } = initial.rail_prompt;

  // Regenerate with your model
  const completion = await openai.chat.completions.create({
    model: "gpt-4o",
    messages: [
      { role: "system", content: system_prompt },
      { role: "user",   content: user_prompt }
    ]
  });

  // Step 2: Submit regenerated content for re-evaluation
  const continued = await client.safeRegenerateContinue({
    sessionId: initial.session_id,
    regeneratedContent: completion.choices[0].message.content
  });

  console.log(continued.status);       // "passed" or "awaiting_regeneration"
  console.log(continued.best_content); // Best content so far
}

{
  "status": "passed",
  "original_content": "...",
  "best_content": "...",
  "best_iteration": 2,
  "best_scores": {
    "rail_score": { "score": 8.4, "confidence": 0.82 },
    "dimension_scores": {},
    "thresholds_met": true
  },
  "iteration_history": [
    { "iteration": 1, "thresholds_met": false, "failing_dimensions": ["fairness"] },
    { "iteration": 2, "thresholds_met": true,  "failing_dimensions": [] }
  ],
  "credits_consumed": 4.0,
  "credits_breakdown": { "evaluations": 2.0, "regenerations": 2.0, "total": 4.0 }
}