TypeScript SDK

The official TypeScript/JavaScript SDK for Runcrate. Zero runtime dependencies, native fetch, full type safety.

Installation

npm install @runcrate/sdk

Requires Node.js 18+.

Quick Start

import Runcrate from '@runcrate/sdk';

const rc = new Runcrate({ apiKey: 'rc_live_YOUR_API_KEY' });

// Chat completion
const response = await rc.models.chatCompletion({
  model: 'deepseek-ai/DeepSeek-V3',
  messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0].message.content);

// List GPU instances
const instances = await rc.instances.list();
instances.forEach(i => console.log(`${i.name} — ${i.status}`));

You can also set the RUNCRATE_API_KEY environment variable instead of passing apiKey.

Configuration

const rc = new Runcrate({
  apiKey: 'rc_live_...',                       // or RUNCRATE_API_KEY env var
  baseUrl: 'https://runcrate.ai',              // infrastructure API
  inferenceUrl: 'https://api.runcrate.ai',     // model inference API
  timeout: 30,                                 // seconds
  maxRetries: 3,                               // retry on 429/5xx
  customHeaders: {},                           // extra headers
  environment: 'production',                   // optional — target a specific environment
});

Environments

API keys are workspace-scoped. By default, requests target the workspace’s default environment (usually main). Pass environment at client construction to target a different one:

// Default environment
const rc = new Runcrate({ apiKey: 'rc_live_...' });

// Specific environments
const staging = new Runcrate({ apiKey: 'rc_live_...', environment: 'staging' });
const prod    = new Runcrate({ apiKey: 'rc_live_...', environment: 'production' });

// Each client only sees resources in its own environment
await staging.instances.list();   // only staging instances
await prod.instances.list();      // only production instances

Environment-scoped: instances, crates, storage volumes. Workspace-wide: SSH keys, billing, API keys, templates.

Model Inference

All inference methods hit api.runcrate.ai.

Chat Completions

const response = await rc.models.chatCompletion({
  model: 'deepseek-ai/DeepSeek-V3',
  messages: [{ role: 'user', content: 'Explain quantum computing' }],
  maxTokens: 500,
  temperature: 0.7,
});
console.log(response.choices[0].message.content);

Streaming

const stream = await rc.models.chatCompletion({
  model: 'deepseek-ai/DeepSeek-V3',
  messages: [{ role: 'user', content: 'Tell me a story' }],
  stream: true,
});

for await (const chunk of stream) {
  const content = (chunk.choices as any[])?.[0]?.delta?.content ?? '';
  process.stdout.write(content);
}

Image Generation

const image = await rc.models.generateImage({
  model: 'black-forest-labs/FLUX.1-schnell',
  prompt: 'A futuristic cityscape at sunset',
  width: 1024,
  height: 768,
});

// Save directly — handles base64, data URIs, and URLs automatically
await image.save('output.webp');

Model-Specific Parameters

All inference methods accept extra parameters that get passed through to the provider. Different models support different parameters:

// Seed for reproducibility
const image = await rc.models.generateImage({
  model: 'black-forest-labs/FLUX.1-schnell',
  prompt: 'A cat in space',
  seed: 42,
  numInferenceSteps: 4,
  guidance: 3.5,
});

// Image editing — pass a file path, URL, or base64 string
const edited = await rc.models.generateImage({
  model: 'black-forest-labs/FLUX.1-kontext-pro',
  prompt: 'Make the sky purple',
  image: './photo.png',              // file path (auto base64-encoded)
});

// Image editing with URL
const result = await rc.models.generateImage({
  model: 'Wan-AI/Wan2.6-Image-Edit',
  prompt: 'Remove the background',
  image: 'https://example.com/photo.png',  // URL (passed as-is)
});

The image, startImage, mask, and controlImage fields accept three formats:

File path — "./photo.png" (auto-detected, read and base64-encoded)
URL — "https://..." (passed through as-is)
Base64 string — raw base64 data (passed through as-is)

Video Generation

// Submit, poll, and save in one call
const job = await rc.models.generateVideoAndSave('output.mp4', {
  model: 'google/veo-3.0',
  prompt: 'A drone flying over mountains',
  duration: 8,
  onStatus: (j) => console.log(`Status: ${j.status}`),
});

Or manage the lifecycle manually:

const job = await rc.models.generateVideo({
  model: 'google/veo-3.0',
  prompt: 'Ocean waves at sunset',
});

// Poll until done
let status = job;
while (status.status !== 'completed' && status.status !== 'failed') {
  await new Promise(r => setTimeout(r, 5000));
  status = await rc.models.getVideoStatus(job.id);
}

// Download
const videoBuffer = await rc.models.downloadVideo(job.id);

Extra parameters (e.g., seed, negative_prompt, image for image-to-video) are passed through:

const job = await rc.models.generateVideo({
  model: 'some-img2vid-model',
  prompt: 'Animate this scene',
  image: './first_frame.png',   // image-to-video
  seed: 42,
  negative_prompt: 'blurry',
});

Text-to-Speech

// One-liner save
await rc.models.textToSpeechAndSave('speech.mp3', {
  model: 'hexgrad/Kokoro-82M',
  input: 'Hello from Runcrate!',
  voice: 'af_heart',
});

// Or get raw Buffer
const audio = await rc.models.textToSpeech({
  model: 'hexgrad/Kokoro-82M',
  input: 'Hello from Runcrate!',
  voice: 'af_heart',
});

Extra parameters like speed or language are passed through:

await rc.models.textToSpeechAndSave('speech.mp3', {
  model: 'hexgrad/Kokoro-82M',
  input: 'Hello!',
  voice: 'af_heart',
  speed: 1.5,           // model-specific
  language: 'en',       // model-specific
});

Transcription

import { readFile } from 'node:fs/promises';

const audioFile = await readFile('recording.wav');
const result = await rc.models.transcribe({
  model: 'openai/whisper-1',
  file: audioFile,
  filename: 'recording.wav',
  language: 'en',              // hint language
  responseFormat: 'srt',       // text, json, srt, vtt
});
console.log(result.text);

Infrastructure Management

GPU Instances

// List instances
const instances = await rc.instances.list();
const filtered = await rc.instances.list({ search: 'training' });

// Browse available GPU types
const types = await rc.instances.listTypes({ gpuType: 'A100' });
types.forEach(t => console.log(`${t.id} — ${t.gpuType} x${t.gpuCount} — $${t.hourlyRate}/hr`));

// Create an instance
const instance = await rc.instances.create({
  name: 'training-run',
  sshKeyId: 'your-key-id',
  gpuType: 'A100',
  gpuCount: 1,
  startupCommands: ['pip install torch'],
});
console.log(`Created: ${instance.id} — ${instance.status}`);

// Check status
const status = await rc.instances.getStatus(instance.id);
console.log(`Status: ${status.status}, IP: ${status.ip}`);

// Terminate
await rc.instances.terminate(instance.id);

SSH Keys

// List keys
const keys = await rc.sshKeys.list();

// Add a key
const key = await rc.sshKeys.create({
  name: 'my-laptop',
  publicKey: 'ssh-ed25519 AAAA...',
});

// Delete a key
await rc.sshKeys.delete(key.id);

Storage

Storage volumes are environment-scoped. Your workspace’s storage provider (AWS S3, Wasabi, or Backblaze B2) must be configured in the dashboard first — the SDK picks it up automatically.

// List available regions (with friendly names)
const regions = await rc.storage.listRegions();
regions.forEach(r => console.log(`${r.name} (${r.provider})`));

// List volumes in the current environment
const volumes = await rc.storage.list();
const filtered = await rc.storage.list({ search: 'datasets' });

// Get a specific volume
const volume = await rc.storage.get('volume-id');

// Create a 100GB volume
const created = await rc.storage.create({
  name: 'datasets',
  sizeGb: 100,
  region: 'us-east-1',
});

// Resize (increase capacity only)
await rc.storage.resize(created.id, 200);

// Delete (refunds unused prepaid days pro-rata)
const result = await rc.storage.delete(created.id);
console.log(`Refunded $${result.refundAmount}`);

Billing: $0.03/GB/month, charged weekly in advance. Deletion refunds the unused portion of the current billing week.

Billing

// Check balance
const balance = await rc.billing.getBalance();
console.log(`Credits: $${balance.creditsBalance}`);

// List transactions (paginated)
const txns = await rc.billing.listTransactions({ limit: 20 });
txns.data.forEach(t => console.log(`${t.type}: $${t.amount}`));
console.log(`Has more: ${txns.hasMore}`);

// Usage summary
const usage = await rc.billing.usage({ from: '2025-01-01', to: '2025-01-31' });
console.log(`Total cost: $${usage.totalCost}`);

Templates

// List templates with search
const templates = await rc.templates.list({
  search: 'finetune',
  category: 'ml',
  page: 1,
  pageSize: 10,
});
templates.data.forEach(t => console.log(`${t.name} — ${t.category}`));
console.log(`Total: ${templates.total}`);

Error Handling

All API errors include the actual error message from the server — never a generic fallback.

import {
  NotFoundError,
  AuthenticationError,
  RateLimitError,
  InsufficientCreditsError,
  BadRequestError,
  UnprocessableEntityError,
} from '@runcrate/sdk';

try {
  await rc.instances.get('nonexistent');
} catch (err) {
  if (err instanceof NotFoundError) {
    console.log(`Not found: ${err.message}`);
  } else if (err instanceof AuthenticationError) {
    console.log('Invalid API key');
  } else if (err instanceof RateLimitError) {
    console.log('Rate limited — retry later');
  } else if (err instanceof InsufficientCreditsError) {
    console.log(`Not enough credits: ${err.message}`);
  } else if (err instanceof UnprocessableEntityError) {
    console.log(`Validation error: ${err.message}`);  // e.g. invalid model params
  } else if (err instanceof BadRequestError) {
    console.log(`Bad request: ${err.message}`);
  }
}

Every error exposes:

err.message — human-readable error description from the API
err.statusCode — HTTP status code
err.code — machine-readable error code (e.g. not_found, rate_limited)
err.details — additional details (when available)

Error Hierarchy

Exception	Status Code	Description
`BadRequestError`	400	Invalid parameters
`AuthenticationError`	401	Invalid or missing API key
`InsufficientCreditsError`	402	Not enough credits
`PermissionDeniedError`	403	Insufficient permissions
`NotFoundError`	404	Resource not found
`ConflictError`	409	Resource conflict
`UnprocessableEntityError`	422	Validation error (e.g. invalid model params)
`RateLimitError`	429	Rate limit exceeded
`InternalServerError`	500	Server error
`ConnectionError`	—	Network failure
`TimeoutError`	—	Request timed out

Welcome

SDKs

CLI

Inference

Compute

Storage

Dedicated Clusters

Billing

Account

FAQ

Installation

Quick Start

Configuration

Environments

Model Inference

Chat Completions

Streaming

Image Generation

Model-Specific Parameters

Video Generation

Text-to-Speech

Transcription

Infrastructure Management

GPU Instances

SSH Keys

Storage

Billing

Templates

Error Handling

Error Hierarchy

​Installation

​Quick Start

​Configuration

​Environments

​Model Inference

​Chat Completions

​Streaming

​Image Generation

​Model-Specific Parameters

​Video Generation

​Text-to-Speech

​Transcription

​Infrastructure Management

​GPU Instances

​SSH Keys

​Storage

​Billing

​Templates

​Error Handling

​Error Hierarchy

Installation

Quick Start

Configuration

Environments

Model Inference

Chat Completions

Streaming

Image Generation

Model-Specific Parameters

Video Generation

Text-to-Speech

Transcription

Infrastructure Management

GPU Instances

SSH Keys

Storage

Billing

Templates

Error Handling

Error Hierarchy