* fix(deps): upgrade vitest to ^4.1.0 to patch critical Vitest UI advisory (GHSA-5xrq-8626-4rwp) - Bump vitest and @vitest/coverage-v8 to ^4.1.0 across all workspaces (only patched release for the critical 'Vitest UI server arbitrary file read/execute' advisory; no 3.x backport exists) - Widen @sim/testing peer range to ^3.0.0 || ^4.0.0 - Migrate constructor mocks to class expressions: vitest 4 uses Reflect.construct for mocks invoked with new, and arrow/function implementations are not constructable (function expressions also get reverted to arrows by biome's useArrowFunction) - Remove deprecated test.poolOptions from apps/sim/vitest.config.ts (options are now top-level in vitest 4) * fix(deps): exclude vulnerable vitest 4.0.x from @sim/testing peer range Tighten the v4 arm of the peer range to >=4.1.0 <5.0.0 so the peer requirement cannot be satisfied by the unpatched 4.0.x builds that GHSA-5xrq-8626-4rwp affects. * fix(testing): make vitest 4 constructor mocks type-check cleanly - logging-session & mcp-oauth mocks: a class passed to mockImplementation has a construct signature that isn't assignable to its (...args) => any parameter, failing tsc. Use named function declarations instead (constructable via Reflect.construct, assignable to mockImplementation, and not rewritten to arrows by biome's useArrowFunction). - database.mock.ts: vitest 4's generic vi.fn typings no longer break the self-referential cycle on the transaction callback's tx param; loosen tx and annotate the callback's return type to resolve the implicit-any errors. * test(isolated-vm): de-flake queue-capacity scheduler tests The 'queue is full' and 'per-owner queued limit' tests relied on 'await sleep(1)' to assume the first request had reached the queue before submitting the overflow request. The first request only enqueues after an async spawn-failure chain (acquireWorker -> spawn exit -> resolve null -> enqueue), which isn't guaranteed within 1ms under CI load — the overflow request then found an empty queue and hit the 200ms queue-wait timeout instead of the capacity rejection. Replace the wall-clock barrier with a deterministic, event-driven one: hold the single global concurrency slot (IVM_MAX_CONCURRENT=1) with an active worker and await an explicit 'dispatched' signal (fired when the worker receives its execute message, after the scheduler counts it active). The follow-up requests then deterministically hit the synchronous enqueue path. Also drops the queue-wait timeout from 200ms to 50ms, so the tests run faster.
Sim TypeScript SDK
The official TypeScript/JavaScript SDK for Sim, allowing you to execute workflows programmatically from your applications.
Installation
npm install simstudio-ts-sdk
# or
yarn add simstudio-ts-sdk
# or
bun add simstudio-ts-sdk
Quick Start
import { SimStudioClient } from 'simstudio-ts-sdk';
// Initialize the client
const client = new SimStudioClient({
apiKey: 'your-api-key-here',
baseUrl: 'https://sim.ai' // optional, defaults to https://sim.ai
});
// Execute a workflow
try {
const result = await client.executeWorkflow('workflow-id');
console.log('Workflow executed successfully:', result);
} catch (error) {
console.error('Workflow execution failed:', error);
}
API Reference
SimStudioClient
Constructor
new SimStudioClient(config: SimStudioConfig)
config.apiKey(string): Your Sim API keyconfig.baseUrl(string, optional): Base URL for the Sim API (defaults tohttps://sim.ai)
Methods
executeWorkflow(workflowId, input?, options?)
Execute a workflow with optional input data.
// With object input (spread at root level of request body)
const result = await client.executeWorkflow('workflow-id', {
message: 'Hello, world!'
});
// With primitive input (wrapped as { input: value })
const result = await client.executeWorkflow('workflow-id', 'NVDA');
// With options
const result = await client.executeWorkflow('workflow-id', { message: 'Hello' }, {
timeout: 60000
});
Parameters:
workflowId(string): The ID of the workflow to executeinput(any, optional): Input data to pass to the workflow. Objects are spread at the root level, primitives/arrays are wrapped in{ input: value }. File objects are automatically converted to base64.options(ExecutionOptions, optional):timeout(number): Timeout in milliseconds (default: 30000)stream(boolean): Enable streaming responsesselectedOutputs(string[]): Block outputs to stream (e.g.,["agent1.content"])async(boolean): Execute asynchronously and return execution ID
Returns: Promise<WorkflowExecutionResult | AsyncExecutionResult>
getWorkflowStatus(workflowId)
Get the status of a workflow (deployment status, etc.).
const status = await client.getWorkflowStatus('workflow-id');
console.log('Is deployed:', status.isDeployed);
Parameters:
workflowId(string): The ID of the workflow
Returns: Promise<WorkflowStatus>
validateWorkflow(workflowId)
Validate that a workflow is ready for execution.
const isReady = await client.validateWorkflow('workflow-id');
if (isReady) {
// Workflow is deployed and ready
}
Parameters:
workflowId(string): The ID of the workflow
Returns: Promise<boolean>
executeWorkflowSync(workflowId, input?, options?)
Execute a workflow and poll for completion (useful for long-running workflows).
const result = await client.executeWorkflowSync('workflow-id', { data: 'some input' }, {
timeout: 60000
});
Parameters:
workflowId(string): The ID of the workflow to executeinput(any, optional): Input data to pass to the workflowoptions(ExecutionOptions, optional):timeout(number): Timeout for the initial request in milliseconds
Returns: Promise<WorkflowExecutionResult>
getJobStatus(jobId)
Get the status of an async job.
const status = await client.getJobStatus('job-id-from-async-execution');
console.log('Job status:', status);
Parameters:
jobId(string): The job ID returned from async execution
Returns: Promise<any>
executeWithRetry(workflowId, input?, options?, retryOptions?)
Execute a workflow with automatic retry on rate limit errors.
const result = await client.executeWithRetry('workflow-id', { message: 'Hello' }, {
timeout: 30000
}, {
maxRetries: 3,
initialDelay: 1000,
maxDelay: 30000,
backoffMultiplier: 2
});
Parameters:
workflowId(string): The ID of the workflow to executeinput(any, optional): Input data to pass to the workflowoptions(ExecutionOptions, optional): Execution optionsretryOptions(RetryOptions, optional):maxRetries(number): Maximum retry attempts (default: 3)initialDelay(number): Initial delay in ms (default: 1000)maxDelay(number): Maximum delay in ms (default: 30000)backoffMultiplier(number): Backoff multiplier (default: 2)
Returns: Promise<WorkflowExecutionResult | AsyncExecutionResult>
getRateLimitInfo()
Get current rate limit information from the last API response.
const rateInfo = client.getRateLimitInfo();
if (rateInfo) {
console.log('Remaining requests:', rateInfo.remaining);
}
Returns: RateLimitInfo | null
getUsageLimits()
Get current usage limits and quota information.
const limits = await client.getUsageLimits();
console.log('Current usage:', limits.usage);
Returns: Promise<UsageLimits>
setApiKey(apiKey)
Update the API key.
client.setApiKey('new-api-key');
setBaseUrl(baseUrl)
Update the base URL.
client.setBaseUrl('https://my-custom-domain.com');
Types
WorkflowExecutionResult
interface WorkflowExecutionResult {
success: boolean;
output?: any;
error?: string;
logs?: any[];
metadata?: {
duration?: number;
executionId?: string;
[key: string]: any;
};
traceSpans?: any[];
totalDuration?: number;
}
LargeValueRef
Oversized execution values may be returned as a versioned reference inside output, logs, streaming events, or async job status responses.
The key field is an opaque execution-scoped server storage pointer, not a client-readable download URL.
interface LargeValueRef {
__simLargeValueRef: true;
version: 1;
id: string;
kind: 'array' | 'object' | 'string' | 'json';
size: number;
key?: string;
executionId?: string;
preview?: unknown;
}
WorkflowStatus
interface WorkflowStatus {
isDeployed: boolean;
deployedAt?: string;
needsRedeployment: boolean;
}
SimStudioError
class SimStudioError extends Error {
code?: string;
status?: number;
}
AsyncExecutionResult
interface AsyncExecutionResult {
success: boolean;
jobId: string;
statusUrl: string;
executionId?: string;
message: string;
async: true;
}
RateLimitInfo
interface RateLimitInfo {
limit: number;
remaining: number;
reset: number;
retryAfter?: number;
}
UsageLimits
interface UsageLimits {
success: boolean;
rateLimit: {
sync: {
isLimited: boolean;
limit: number;
remaining: number;
resetAt: string;
};
async: {
isLimited: boolean;
limit: number;
remaining: number;
resetAt: string;
};
authType: string;
};
usage: {
currentPeriodCost: number;
limit: number;
plan: string;
};
}
ExecutionOptions
interface ExecutionOptions {
timeout?: number;
stream?: boolean;
selectedOutputs?: string[];
async?: boolean;
}
RetryOptions
interface RetryOptions {
maxRetries?: number;
initialDelay?: number;
maxDelay?: number;
backoffMultiplier?: number;
}
Examples
Basic Workflow Execution
import { SimStudioClient } from 'simstudio-ts-sdk';
const client = new SimStudioClient({
apiKey: process.env.SIM_API_KEY!
});
async function runWorkflow() {
try {
// Check if workflow is ready
const isReady = await client.validateWorkflow('my-workflow-id');
if (!isReady) {
throw new Error('Workflow is not deployed or ready');
}
// Execute the workflow
const result = await client.executeWorkflow('my-workflow-id', {
message: 'Process this data',
userId: '12345'
});
if (result.success) {
console.log('Output:', result.output);
console.log('Duration:', result.metadata?.duration);
} else {
console.error('Workflow failed:', result.error);
}
} catch (error) {
console.error('Error:', error);
}
}
runWorkflow();
Error Handling
import { SimStudioClient, SimStudioError } from 'simstudio-ts-sdk';
const client = new SimStudioClient({
apiKey: process.env.SIM_API_KEY!
});
async function executeWithErrorHandling() {
try {
const result = await client.executeWorkflow('workflow-id');
return result;
} catch (error) {
if (error instanceof SimStudioError) {
switch (error.code) {
case 'UNAUTHORIZED':
console.error('Invalid API key');
break;
case 'TIMEOUT':
console.error('Workflow execution timed out');
break;
case 'USAGE_LIMIT_EXCEEDED':
console.error('Usage limit exceeded');
break;
case 'INVALID_JSON':
console.error('Invalid JSON in request body');
break;
default:
console.error('Workflow error:', error.message);
}
} else {
console.error('Unexpected error:', error);
}
throw error;
}
}
Environment Configuration
// Using environment variables
const client = new SimStudioClient({
apiKey: process.env.SIM_API_KEY!,
baseUrl: process.env.SIM_BASE_URL // optional
});
File Upload
File objects are automatically detected and converted to base64 format. Include them in your input under the field name matching your workflow's API trigger input format:
The SDK converts File objects to this format:
{
type: 'file',
data: 'data:mime/type;base64,base64data',
name: 'filename',
mime: 'mime/type'
}
Alternatively, you can manually provide files using the URL format:
{
type: 'url',
data: 'https://example.com/file.pdf',
name: 'file.pdf',
mime: 'application/pdf'
}
import { SimStudioClient } from 'simstudio-ts-sdk';
import fs from 'fs';
const client = new SimStudioClient({
apiKey: process.env.SIM_API_KEY!
});
// Node.js: Read file and create File object
const fileBuffer = fs.readFileSync('./document.pdf');
const file = new File([fileBuffer], 'document.pdf', { type: 'application/pdf' });
// Include files under the field name from your API trigger's input format
const result = await client.executeWorkflow('workflow-id', {
documents: [file], // Field name must match your API trigger's file input field
instructions: 'Process this document'
});
// Browser: From file input
const handleFileUpload = async (event: Event) => {
const inputEl = event.target as HTMLInputElement;
const files = Array.from(inputEl.files || []);
const result = await client.executeWorkflow('workflow-id', {
attachments: files, // Field name must match your API trigger's file input field
query: 'Analyze these files'
});
};
Getting Your API Key
- Log in to your Sim account
- Navigate to your workflow
- Click on "Deploy" to deploy your workflow
- Select or create an API key during the deployment process
- Copy the API key to use in your application
Development
Running Tests
To run the tests locally:
-
Clone the repository and navigate to the TypeScript SDK directory:
cd packages/ts-sdk -
Install dependencies:
bun install -
Run the tests:
bun run test
Building
Build the TypeScript SDK:
bun run build
This will compile TypeScript files to JavaScript and generate type declarations in the dist/ directory.
Development Mode
For development with auto-rebuild:
bun run dev
Requirements
- Node.js 18+
- TypeScript 5.0+ (for TypeScript projects)
License
Apache-2.0