Runs

import { RunsClient, createClient } from '@sylphx/sdk'

// Connection URL bundles credential + slug — no separate ref env var needed
const config = createClient(process.env.SYLPHX_URL!)

// Single run — wait for completion
const result = await RunsClient.runAndWait(config, {
  image: 'ghcr.io/acme/trainer:sha-abc123',
  command: ['python', 'train.py', '--fold', '0'],
  machine: 'large',
  timeoutSeconds: 3600,
})

if (result.exitCode !== 0) {
  throw new Error(`Training failed: ${result.stderr}`)
}
console.log('Accuracy:', JSON.parse(result.stdout).accuracy)

import { RunsClient, createClient } from '@sylphx/sdk'

const config = createClient(process.env.SYLPHX_URL!)

const folds = [0, 1, 2, 3, 4, 5, 6, 7, 8]

// Spawn all runs in parallel
const handles = await Promise.all(
  folds.map((fold) =>
    RunsClient.run(config, {
      image: 'ghcr.io/acme/trainer:sha-abc123',
      command: ['python', 'train.py', '--fold', String(fold)],
      env: { FOLD_ID: String(fold), DATABASE_URL: process.env.DATABASE_URL! },
      machine: 'large',
      // Shared feature cache volume for concurrent access.
      volumeMounts: [{ volumeId: process.env.CACHE_VOLUME_ID!, mountPath: '/cache' }],
      timeoutSeconds: 7200,
    }),
  ),
)

// Wait for all to complete
const results = await Promise.all(handles.map((h) => h.wait()))
const failures = results.filter((r) => r.exitCode !== 0)
if (failures.length > 0) {
  console.error(`${failures.length}/${folds.length} folds failed`)
}
const avgAccuracy = results
  .filter((r) => r.exitCode === 0)
  .map((r) => JSON.parse(r.stdout).accuracy)
  .reduce((a, b) => a + b, 0) / folds.length
console.log('Average accuracy:', avgAccuracy)