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The ILLA SDK is the fastest way to add ILLA to your product. It wraps the Core API with chat session management, tool-result loops, context persistence, and polling helpers so you can focus on your product logic instead of request orchestration. Use IllaSDK when you want one client that can:
  • start and continue chats
  • return pendingTools for your app to execute
  • send tool outcomes back to ILLA
  • poll long-running actions
  • manage chat context for you
Use the lower-level SDK components only if you need custom transport, custom context storage, or tighter control over how requests are assembled.

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Install

npm install @illalabs/sdk

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First request

Start with IllaSDK. It is the primary integration surface for most applications. 
import { IllaSDK } from '@illalabs/sdk'

const sdk = new IllaSDK({
  apiKey: process.env.ILLA_API_KEY!
})

const result = await sdk.sendMessage(
  'Swap 0.5 ETH to USDC',
  { userContext: { address: '0xYourAddress' } }
)

if (!result.response.isError) {
  console.log(result.response.data.text)
}

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What the SDK gives you

  • IllaSDK for the full chat and tool loop
  • Chat for lower-level request handling
  • CoreApiProvider for HTTP transport and route overrides
  • ContextManager for persisted chat state
  • Prompt for structured user and tool messages
  • AsyncToolChecker for long-running action polling

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Use lower-level components when needed

If you need custom transport, storage, or request construction, you can compose the building blocks directly: 
import {
  Chat,
  ContextManager,
  CoreApiProvider,
  InMemoryCache,
  Prompt,
} from '@illalabs/sdk'

const provider = new CoreApiProvider({
  headers: { 'x-api-key': process.env.ILLA_API_KEY! },
})

const context = new ContextManager(new InMemoryCache())

const chat = new Chat({
  coreApiProvider: provider,
  contextManager: context,
  userContext: { address: '0xYourAddress' },
})

const prompt = new Prompt({ text: 'Swap 0.5 ETH to USDC' })
const result = await chat.sendMessage(prompt)

if (!result.response.isError) {
  console.log(result.response.data.text)
}

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Next steps