npm install @usfbios/sdk

import { USFBios } from '@usfbios/sdk';

const client = new USFBios({
  apiKey: process.env.USFBIOS_API_KEY,  // sk_live_...
});

const info = await client.introspect();
console.log(`Org: ${info.org.name}`);
console.log(`Workspace: ${info.workspace.name}`);
console.log(`Scopes: ${info.scopes.join(', ')}`);

// Search for models
const results = await client.models.search({
  query: 'llama',
  type: 'llm',
  limit: 10,
});
for (const m of results.models) {
  console.log(`${m.id} - ${m.totalParams}B params`);
}

// Get model config for GPU planning
const config = await client.models.getConfig('meta-llama/Llama-3.1-8B');
console.log(`${config.totalParams}B params, MoE: ${config.isMoE}`);

// Check adapter compatibility
const compat = await client.models.getAdapterCompatibility({
  modelType: 'llama',
  trainingMethod: 'rlhf',
  rlhfAlgorithm: 'dpo',
});
const usable = compat.adapters.filter(a => a.compatible);
console.log(`${usable.length} compatible adapters`);

// Upload a local dataset file
const ds = await client.datasets.upload({
  filePath: './training_data.jsonl',
  name: 'Customer Support SFT',
});
console.log(`Uploaded: ${ds.id}`);

// List all datasets
const datasets = await client.datasets.list();
console.log(`${datasets.length} datasets`);

// Preview rows before training
const preview = await client.datasets.preview('ds_abc123', {
  page: 1,
  pageSize: 5,
});
console.log(preview.columns);

// Validate a file before uploading
const result = await client.datasets.validate('./data.jsonl');
if (result.valid) {
  console.log(`Valid ${result.format} - ${result.row_count} rows`);
} else {
  console.error('Errors:', result.errors);
}

// Import from HuggingFace
const imported = await client.datasets.importFromHuggingFace({
  repoId: 'databricks/dolly-15k',
  integrationId: 'int_abc123',
  name: 'Dolly 15k',
});

// Search HuggingFace Hub
const hubResults = await client.datasets.searchHub({ query: 'code instruct' });

// Delete a dataset
await client.datasets.delete('ds_abc123');

// Create a training job
const job = await client.training.create({
  idempotencyKey: 'training-create-20260711-0001',
  model: 'meta-llama/Llama-3.1-8B-Instruct',
  datasetId: 'ds_abc123',
  method: 'sft',
  adapter: 'lora',
  epochs: 3,
  learningRate: 2e-4,
  loraRank: 16,
  loraAlpha: 32,
  gpuType: 'A100_80GB',
});
console.log(`Job ${job.id} created - status: ${job.status}`);

// Monitor training
const metrics = await client.training.getMetrics(job.id);
console.log(`Loss: ${metrics.current_loss}`);

// View logs
const logs = await client.training.getLogs(job.id);
for (const line of logs.logs) {
  console.log(line);
}

// List checkpoints
const checkpoints = await client.training.getCheckpoints(job.id);
for (const cp of checkpoints) {
  console.log(`Step ${cp.step}: loss ${cp.loss}`);
}

// Stop and resume
await client.training.stop(job.id);
await client.training.resume(job.id, 'training-resume-20260711-0001');

// Check wallet balance
const balance = await client.wallet.getBalance();
console.log(`Balance: $${(balance.balance_cents / 100).toFixed(2)}`);
console.log(`Available: $${(balance.available_cents / 100).toFixed(2)}`);

// View transaction history
const txns = await client.wallet.getTransactions({ limit: 20 });
for (const t of txns) {
  console.log(`${t.type}: $${(t.amount_cents / 100).toFixed(2)} - ${t.description}`);
}

// Get GPU pricing
const pricing = await client.gpu.getPricing();
for (const gpu of pricing.gpus) {
  console.log(`${gpu.display_name}: ${gpu.price_display} - ${gpu.vram_gb}GB VRAM`);
}

// Get recommended GPU for a model
const rec = await client.gpu.getRecommended('meta-llama/Llama-3.1-8B-Instruct');
if (rec) {
  console.log(`Recommended: ${rec.display_name} x${rec.recommended_count}`);
  console.log(`Estimated cost: $${(rec.estimated_cost_per_hour_cents / 100).toFixed(2)}/hr`);
}

// Import from a connected HuggingFace account
const imported = await client.datasets.importFromHuggingFace({
  repoId: 'your-org/private-dataset',
  integrationId: 'int_abc123',   // from connected HF account
  name: 'My Private Dataset',
  split: 'train',
  maxSamples: 10000,
});
console.log(`Imported: ${imported.id} - ${imported.row_count} rows`);

import { USFBios, ApiError } from '@usfbios/sdk';

const client = new USFBios({ apiKey: process.env.USFBIOS_API_KEY });

try {
  const job = await client.training.get('job_nonexistent');
} catch (err) {
  if (err instanceof ApiError) {
    console.error(`HTTP ${err.status}: ${err.message}`);
    console.error(`Code: ${err.code}`);           // e.g. "NOT_FOUND"
    console.error(`Request ID: ${err.requestId}`); // for support
  }
}

// Common error status codes:
// 401 - Invalid or expired API key
// 403 - Key missing required scope
// 404 - Resource not found
// 422 - Validation error
// 429 - Rate limit exceeded

import type {
  USFBiosConfig,
  ModelSearchParams,
  ModelSearchResponse,
  ModelConfig,
  Dataset,
  DatasetUploadParams,
  TrainingJob,
  TrainingCreateParams,
  TrainingMetrics,
  TrainingCheckpoint,
  WalletBalance,
  Transaction,
  GPUPricingResponse,
  ApiKeyIntrospection,
} from '@usfbios/sdk';