SDK Examples

import { CtrlAI } from '@ctrlai/sdk';

const client = new CtrlAI({ apiKey: process.env.CTRLAI_API_KEY! });

// 1. Run the assessment
const result = await client.inference.query({
  query: `Assess credit risk for:
    - Annual income: $85,000
    - Credit score: 720
    - DTI ratio: 28%
    - Employment: 5 years at current employer`,
  domainId: 'finance',
});

// 2. Check coverage
if (result.coveragePercent < 50) {
  console.warn('Low coverage — response may contain unverified reasoning');
}

// 3. Extract trust-tagged segments
for (const segment of result.segments) {
  if (segment.trustLevel === 'verified') {
    // Deterministic, program-computed — safe to use in automated decisions
    console.log(`[VERIFIED] ${segment.text}`);
  } else if (segment.trustLevel === 'neural') {
    // Unverified LLM output — flag for human review
    console.log(`[UNVERIFIED] ${segment.text}`);
  }
}

// 4. Log the audit trail
console.log('Units fired:', result.unitsUsed.map(u => u.name));
console.log('Models used:', result.modelsUsed);

const units = [
  {
    name: 'DTI Threshold Check',
    unitType: 'program' as const,
    domainId: 'finance',
    given: 'Applicant financial data is available',
    when: 'DTI ratio needs to be evaluated against regulatory thresholds',
    then: 'Classify risk level based on DTI',
  },
  {
    name: 'Income Stability Assessment',
    unitType: 'framework' as const,
    domainId: 'finance',
    given: 'Employment and income history is available',
    when: 'Income stability needs to be evaluated for lending decision',
    then: 'Produce income stability score across 6 factors',
  },
];

for (const unit of units) {
  const created = await client.units.create(unit);
  console.log(`Created: ${created.name} (${created.id})`);
}