Duriin-API/test/autonomy.test.js

const test = require('node:test');
const assert = require('node:assert/strict');
const Database = require('better-sqlite3');

const { initAutonomySchema } = require('../src/autonomy/schema');
const { enqueueJob, leaseNextJob, completeJob } = require('../src/autonomy/jobs');
const { normalizeProposal, acceptProposal } = require('../src/autonomy/coordinator');
const { calibrateOutcomes, cohortKey } = require('../src/autonomy/calibration');
const { decide } = require('../src/autonomy/policy');
const { validatePaperIntent, createSimulator } = require('../src/autonomy/execution');
const { calculateOutcome, addTradingDays } = require('../src/autonomy/outcomes');
const { yahooSymbol } = require('../workers/outcomeAutonomyWorker');
const { createOrderIntent } = require('../src/autonomy/orderIntents');
const { enqueueCoordinatorEvent, reconcileArchiveBatch, reconcileLiveBatch } = require('../workers/autonomyWorker');
const { scheduleNext } = require('../workers/replayWorker');
const { refreshHistoricalCalibration, createDecisions, ensureCalibrationColumns } = require('../workers/calibrationWorker');

test('autonomy schema and leased jobs are restart-safe', () => {
  const db = new Database(':memory:');
  initAutonomySchema(db);
  assert.equal(enqueueJob(db, {
    jobType: 'enrich', lane: 'live', priority: 10, entityType: 'article', entityId: 42,
    idempotencyKey: 'enrich:42',
  }).inserted, true);
  assert.equal(enqueueJob(db, {
    jobType: 'enrich', lane: 'live', priority: 10, entityType: 'article', entityId: 42,
    idempotencyKey: 'enrich:42',
  }).inserted, false);
  const job = leaseNextJob(db, 'test-worker');
  assert.equal(job.lane, 'live');
  assert.equal(completeJob(db, job.id, 'test-worker'), true);
  assert.equal(db.prepare("SELECT status FROM autonomy_jobs WHERE id = ?").get(job.id).status, 'complete');
});

test('coordinator proposals require evidence and contain no arbitrary numeric confidence', () => {
  const normalized = normalizeProposal({ predictions: [{
    instrument: 'nvda', direction: 'positive', event_type: 'supply_constraint',
    horizon_days: 10, evidence_article_ids: [7],
  }] }, { informationCutoff: '2026-01-01T00:00:00Z', model: 'test-model' });
  assert.equal(normalized.predictions[0].instrument, 'NVDA');
  assert.equal('probability' in normalized.predictions[0], false);
  assert.throws(() => normalizeProposal({ predictions: [{ instrument: 'NVDA', direction: 'positive', horizon_days: 10 }] }));
});

test('accepted proposal preserves evidence and creates immutable prediction', () => {
  const archive = new Database(':memory:');
  archive.exec('CREATE TABLE articles (id INTEGER PRIMARY KEY)');
  archive.prepare('INSERT INTO articles (id) VALUES (?)').run(7);
  const intelligence = new Database(':memory:');
  initAutonomySchema(intelligence);
  intelligence.prepare("INSERT INTO autonomy_instruments(symbol, broker, active, tradable) VALUES ('NVDA', 'test', 1, 1)").run();
  const result = acceptProposal(intelligence, archive, {
    predictions: [{ instrument: 'NVDA', direction: 'positive', event_type: 'earnings', horizon_days: 10, evidence_article_ids: [7] }],
  }, { informationCutoff: '2026-01-01T00:00:00Z', strategyVersion: 'test' });
  assert.equal(result.predictionCount, 1);
  assert.deepEqual(JSON.parse(intelligence.prepare('SELECT evidence_article_ids FROM autonomy_predictions').get().evidence_article_ids), [7]);
});

test('replay evidence cannot look beyond its information cutoff and remains non-executable', () => {
  const archive = new Database(':memory:');
  archive.exec('CREATE TABLE articles (id INTEGER PRIMARY KEY, pub_date_effective TEXT, pub_date TEXT, ingested_at TEXT)');
  archive.prepare("INSERT INTO articles VALUES (7, '2020-01-01T00:00:00Z', NULL, '2020-01-01T00:00:00Z')").run();
  const intelligence = new Database(':memory:');
  initAutonomySchema(intelligence);
  intelligence.prepare("INSERT INTO autonomy_instruments(symbol, broker, active, tradable) VALUES ('NVDA', 'test', 1, 1)").run();
  assert.throws(() => acceptProposal(intelligence, archive, {
    predictions: [{ instrument: 'NVDA', direction: 'positive', event_type: 'earnings', horizon_days: 10, evidence_article_ids: [7] }],
  }, { informationCutoff: '2019-12-31T00:00:00Z', origin: 'replay', replayRunId: 1 }), /missing evidence/);
  const proposal = intelligence.prepare("INSERT INTO autonomy_proposals(payload, information_cutoff, status) VALUES ('{}', datetime('now'), 'accepted')").run();
  const prediction = intelligence.prepare(`INSERT INTO autonomy_predictions
    (proposal_id, instrument, direction, event_type, horizon_days, information_cutoff, evidence_article_ids, strategy_version, origin)
    VALUES (?, 'NVDA', 'positive', 'test', 10, datetime('now'), '[7]', 'test', 'replay')`).run(proposal.lastInsertRowid);
  intelligence.prepare("INSERT INTO autonomy_decisions(prediction_id, action, rationale, strategy_version) VALUES (?, 'BUY', 'test', 'test')").run(prediction.lastInsertRowid);
  const executable = intelligence.prepare(`SELECT d.id FROM autonomy_decisions d JOIN autonomy_predictions p ON p.id=d.prediction_id
    WHERE d.action IN ('BUY','SELL') AND p.origin='live'`).all();
  assert.equal(executable.length, 0);
});

test('replay scheduler skips terminal replay jobs instead of pinning the cursor', () => {
  const archive = new Database(':memory:');
  archive.exec(`
    CREATE TABLE articles (
      id INTEGER PRIMARY KEY,
      title TEXT,
      description TEXT,
      content TEXT,
      pub_date_effective TEXT,
      is_index_page INTEGER
    )
  `);
  archive.prepare("INSERT INTO articles VALUES (1, 'bad', '', 'content', '2020-01-01T00:00:00Z', 0)").run();
  archive.prepare("INSERT INTO articles VALUES (2, 'next', '', 'content', '2020-01-02T00:00:00Z', 0)").run();

  const intelligence = new Database(':memory:');
  initAutonomySchema(intelligence);
  const runId = intelligence.prepare(`
    INSERT INTO autonomy_replay_runs (watermark_at, strategy_version, prompt_version, coordinator_model)
    VALUES ('2020-01-03T00:00:00Z', 'test', 'test', 'test')
  `).run().lastInsertRowid;
  enqueueJob(intelligence, {
    jobType: 'replay_article', lane: 'historical', priority: 1, entityType: 'article', entityId: 1,
    idempotencyKey: `replay:${runId}:article:1`,
  });
  intelligence.prepare("UPDATE autonomy_jobs SET status='dead_letter', attempts=5, last_error='fetch failed'").run();

  const run = intelligence.prepare('SELECT * FROM autonomy_replay_runs WHERE id=?').get(runId);
  const next = scheduleNext(intelligence, archive, run);
  assert.equal(next.id, 2);
  assert.equal(intelligence.prepare('SELECT cursor_article_id FROM autonomy_replay_runs WHERE id=?').get(runId).cursor_article_id, 1);
  assert.equal(intelligence.prepare("SELECT COUNT(*) count FROM autonomy_jobs WHERE status='pending' AND entity_id='2'").get().count, 1);
});

test('calibration and policy abstain on insufficient evidence', () => {
  const calibration = calibrateOutcomes([
    { excess_return: 0.02, direction_correct: 1 },
    { excess_return: -0.01, direction_correct: 0 },
  ]);
  assert.equal(calibration.sampleSize, 2);
  const result = decide({ ...calibration }, { minSampleSize: 30 });
  assert.equal(result.action, 'ABSTAIN');
  assert.equal(cohortKey({ sector: 'tech', eventType: 'earnings', horizonDays: 10, direction: 'positive' }), 'v2|tech|earnings|medium|positive');
  assert.equal(decide({
    direction: 'negative', probability: 0.8, expectedExcessReturn: -0.02, lowerReturn: -0.04,
    sampleSize: 40, distinctInstruments: 9, topInstrumentShare: 0.25,
  }).action, 'SELL');
});

test('historical replay outcomes create replay calibration snapshots', () => {
  const db = new Database(':memory:');
  initAutonomySchema(db);
  const proposal = db.prepare("INSERT INTO autonomy_proposals(payload, information_cutoff, status) VALUES ('{}', '2020-01-01T00:00:00Z', 'accepted')").run();
  const prediction = db.prepare(`
    INSERT INTO autonomy_predictions
      (proposal_id, instrument, direction, event_type, horizon_days, information_cutoff, evidence_article_ids,
       learning_eligible, strategy_version, origin, replay_run_id, status)
    VALUES (?, 'NVDA', 'positive', 'earnings', 10, '2020-01-01T00:00:00Z', '[1]', 0, 'test', 'replay', 7, 'resolved')
  `).run(proposal.lastInsertRowid);
  db.prepare(`
    INSERT INTO autonomy_outcomes(prediction_id, excess_return, direction_correct)
    VALUES (?, 0.04, 1)
  `).run(prediction.lastInsertRowid);

  // one per-run replay snapshot plus the pooled historical/replay snapshot
  assert.equal(refreshHistoricalCalibration(db, 'test-cal'), 2);
  const snapshot = db.prepare("SELECT source, replay_run_id, sample_size, directional_probability FROM autonomy_calibration_snapshots WHERE source='replay'").get();
  assert.equal(snapshot.source, 'replay');
  assert.equal(snapshot.replay_run_id, 7);
  assert.equal(snapshot.sample_size, 1);
  assert(snapshot.directional_probability > 0.5);
});

test('live decisions map calibration snapshot fields into policy inputs', () => {
  const db = new Database(':memory:');
  initAutonomySchema(db);
  const proposal = db.prepare("INSERT INTO autonomy_proposals(payload, information_cutoff, status) VALUES ('{}', datetime('now'), 'accepted')").run();
  const prediction = db.prepare(`
    INSERT INTO autonomy_predictions
      (proposal_id, instrument, direction, event_type, horizon_days, information_cutoff, evidence_article_ids,
       learning_eligible, strategy_version, origin, status)
    VALUES (?, 'NVDA', 'positive', 'earnings', 10, datetime('now'), '[1]', 1, 'test', 'live', 'open')
  `).run(proposal.lastInsertRowid);
  ensureCalibrationColumns(db);
  db.prepare(`
    INSERT INTO autonomy_calibration_snapshots
      (cohort_key, sample_size, effective_sample_size, directional_probability, expected_excess_return,
       lower_return, upper_return, parent_cohort_key, version, source)
    VALUES ('v2|unknown|earnings|medium|positive', 40, 42, 0.7, 0.02, -0.01, 0.06, NULL, 'test-cal', 'live')
  `).run();
  db.prepare("UPDATE autonomy_calibration_snapshots SET distinct_instruments = 11, top_instrument_share = 0.2").run();

  assert.equal(createDecisions(db), 1);
  const decision = db.prepare('SELECT * FROM autonomy_decisions WHERE prediction_id=?').get(prediction.lastInsertRowid);
  assert.equal(decision.action, 'BUY');
  assert.equal(decision.calibrated_probability, 0.7);
  assert.equal(decision.expected_excess_return, 0.02);
});

test('paper execution is allowlisted, bounded and idempotent', () => {
  const intent = validatePaperIntent({ decisionId: 12, instrument: 'NVDA', action: 'BUY', notional: 100 }, { tradable: true, maxNotional: 500 });
  const broker = createSimulator();
  assert.deepEqual(broker.submit(intent), broker.submit(intent));
  assert.throws(() => validatePaperIntent({ decisionId: 13, instrument: 'PRIVATE', action: 'BUY', notional: 100 }, { tradable: false }));
  assert.throws(() => validatePaperIntent({ decisionId: 14, instrument: 'NVDA', action: 'BUY', notional: 501 }, { tradable: true, maxNotional: 500 }));
});

test('archive reconciliation prioritizes recent usable events and is bounded', () => {
  const archive = new Database(':memory:');
  archive.exec('CREATE TABLE articles (id INTEGER PRIMARY KEY, event_id INTEGER, ingested_at TEXT, content TEXT, has_embedding INTEGER)');
  archive.prepare('INSERT INTO articles VALUES (1, 99, ?, ?, 1)').run(new Date().toISOString(), 'content');
  const intelligence = new Database(':memory:');
  initAutonomySchema(intelligence);
  const result = reconcileArchiveBatch(archive, intelligence, 1);
  assert.equal(result.scanned, 1);
  const job = intelligence.prepare("SELECT lane, priority FROM autonomy_jobs WHERE job_type='coordinator_event'").get();
  assert.equal(job.lane, 'live');
  assert.equal(job.priority, 100);
  const live = reconcileLiveBatch(archive, intelligence, 1);
  assert.equal(live.scanned, 1);
});

test('archive reconciliation recovers transient dead-lettered coordinator jobs', () => {
  const intelligence = new Database(':memory:');
  initAutonomySchema(intelligence);
  enqueueJob(intelligence, {
    jobType: 'coordinator_event', lane: 'historical', priority: 10, entityType: 'event', entityId: 99,
    idempotencyKey: 'coordinator_event:99',
  });
  intelligence.prepare(`
    UPDATE autonomy_jobs
    SET status='dead_letter', attempts=5, last_error='TypeError: fetch failed'
    WHERE idempotency_key='coordinator_event:99'
  `).run();

  const result = enqueueCoordinatorEvent(intelligence, {
    event_id: 99,
    ingested_at: new Date().toISOString(),
    content: 'content',
    has_embedding: 1,
  });
  assert.equal(result.recovered, true);
  const job = intelligence.prepare("SELECT status, lane, priority, attempts, last_error FROM autonomy_jobs WHERE idempotency_key='coordinator_event:99'").get();
  assert.equal(job.status, 'pending');
  assert.equal(job.lane, 'live');
  assert.equal(job.priority, 100);
  assert.equal(job.attempts, 0);
  assert.match(job.last_error, /Recovered transient coordinator failure/);
});

test('archive reconciliation leaves non-transient coordinator dead letters alone', () => {
  const intelligence = new Database(':memory:');
  initAutonomySchema(intelligence);
  enqueueJob(intelligence, {
    jobType: 'coordinator_event', lane: 'historical', priority: 10, entityType: 'event', entityId: 100,
    idempotencyKey: 'coordinator_event:100',
  });
  intelligence.prepare(`
    UPDATE autonomy_jobs
    SET status='dead_letter', attempts=5, last_error='no tradable instruments are allowlisted'
    WHERE idempotency_key='coordinator_event:100'
  `).run();

  const result = enqueueCoordinatorEvent(intelligence, {
    event_id: 100,
    ingested_at: new Date().toISOString(),
    content: 'content',
    has_embedding: 1,
  });
  assert.equal(result.recovered, false);
  const job = intelligence.prepare("SELECT status, attempts, last_error FROM autonomy_jobs WHERE idempotency_key='coordinator_event:100'").get();
  assert.equal(job.status, 'dead_letter');
  assert.equal(job.attempts, 5);
  assert.equal(job.last_error, 'no tradable instruments are allowlisted');
});

test('outcome calculation uses benchmark-relative return', () => {
  const outcome = calculateOutcome(
    { information_cutoff: '2026-01-02T00:00:00Z', horizon_days: 5, direction: 'positive' },
    [{ date: '2026-01-02', close: 100 }, { date: '2026-01-09', close: 110 }],
    [{ date: '2026-01-02', close: 100 }, { date: '2026-01-09', close: 105 }]
  );
  assert.equal(outcome.directionCorrect, 1);
  assert.equal(outcome.excessReturn, 0.05);
});

test('order intents require the explicit instrument allowlist', () => {
  const db = new Database(':memory:');
  initAutonomySchema(db);
  db.prepare("INSERT INTO autonomy_instruments(symbol, broker, active, tradable) VALUES ('NVDA', 'sim', 1, 1)").run();
  const proposal = db.prepare(`INSERT INTO autonomy_proposals(payload, information_cutoff, status) VALUES ('{}', datetime('now'), 'accepted')`).run();
  const prediction = db.prepare(`INSERT INTO autonomy_predictions(proposal_id, instrument, direction, event_type, horizon_days, information_cutoff, evidence_article_ids, learning_eligible, strategy_version) VALUES (?, 'NVDA', 'positive', 'test', 10, datetime('now'), '[1]', 1, 'test')`).run(proposal.lastInsertRowid);
  const decision = db.prepare(`INSERT INTO autonomy_decisions(prediction_id, action, rationale, strategy_version) VALUES (?, 'BUY', 'test', 'test')`).run(prediction.lastInsertRowid);
  const intent = createOrderIntent(db, decision.lastInsertRowid, 100, { maxNotional: 100 });
  assert.equal(intent.side, 'buy');
  assert.equal(db.prepare('SELECT status FROM autonomy_order_intents').get().status, 'shadow');
});

test('event_type is held to the closed family enum', () => {
  const base = { instrument: 'NVDA', direction: 'positive', horizon_days: 10, evidence_article_ids: [1] };
  const typeOf = (eventType) => normalizeProposal({ predictions: [{ ...base, event_type: eventType }] }).predictions[0].eventType;

  // the enum itself, in the shapes a model actually emits
  assert.equal(typeOf('earnings'), 'earnings');
  assert.equal(typeOf('Supply Chain'), 'supply_chain');
  assert.equal(typeOf('M_AND_A'), 'm_and_a');

  // "none of these fit" is a legitimate answer and has to survive
  assert.equal(typeOf('other'), 'other');

  // off-enum but placeable: salvaged onto the family calibration would have
  // picked anyway, so we dont throw away a usable prediction over a label
  assert.equal(typeOf('earnings_beat_q3'), 'earnings');
  assert.equal(typeOf('ceo resignation'), 'leadership');

  // unplaceable free text is the 201-distinct-values failure, and is rejected
  assert.throws(() => typeOf('vibes_shifted'), /event_type must be one of/);
  assert.throws(() => typeOf(''), /event_type must be one of/);
});

test('dotted tickers are translated to the format the price feed expects', () => {
  // BRK.B 404d forever and the outcome worker retried it in a hot loop
  assert.equal(yahooSymbol('BRK.B'), 'BRK-B');
  assert.equal(yahooSymbol('ABR.PRD'), 'ABR-PRD');
  assert.equal(yahooSymbol('aac.u'), 'AAC-U');

  // ordinary symbols must pass through untouched
  assert.equal(yahooSymbol('NVDA'), 'NVDA');
  assert.equal(yahooSymbol(' spy '), 'SPY');
});

test('an outcome whose horizon has not actually elapsed is not a result', () => {
  // ITW and WMT both scored exactly 0.00% excess in production because at
  // horizon 1 the entry and exit lookups landed on the same bar. Zero is not a
  // measurement, and it was being recorded as a directional miss.
  const sameBar = calculateOutcome(
    { information_cutoff: '2026-01-02T00:00:00Z', horizon_days: 1, direction: 'positive' },
    [{ date: '2026-01-05', close: 100 }],
    [{ date: '2026-01-05', close: 100 }]
  );
  assert.equal(sameBar, null);

  // the exit bar genuinely existing still scores normally
  const real = calculateOutcome(
    { information_cutoff: '2026-01-02T00:00:00Z', horizon_days: 1, direction: 'positive' },
    [{ date: '2026-01-02', close: 100 }, { date: '2026-01-05', close: 104 }],
    [{ date: '2026-01-02', close: 100 }, { date: '2026-01-05', close: 102 }]
  );
  assert.equal(real.directionCorrect, 1);
  assert.ok(Math.abs(real.excessReturn - 0.02) < 1e-9);
});

test('trading day arithmetic steps over weekends', () => {
  // friday + 1 trading day is monday, not saturday. the old due-check counted
  // calendar days and so called a friday horizon-1 prediction due on saturday,
  // when monday's close cannot exist yet.
  assert.equal(addTradingDays('2026-01-02', 1), '2026-01-05');
  assert.equal(addTradingDays('2026-01-02', 5), '2026-01-09');
  assert.equal(addTradingDays('2026-01-02', 0), '2026-01-02');
});