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Quickstart

In five minutes you will build a graph where an agent drafts a reply to a customer, the run stops for a human to review the draft, and then finishes.

1. Create the project​

mkdir refund-desk && cd refund-desk
npm init -y && npm pkg set type=module
npm install @ailu-ai/graph-sdk

2. Write the graph​

Save this as app.ts:

app.ts
import { createGraph, finalAnswer, model } from "@ailu-ai/graph-sdk";

const app = createGraph({ name: "refund-desk" })
  .channel("request", { type: "string", default: "" })
  .channel("reply", { type: "string", default: "" })
  .agentNode("draft", {
    model: model.anthropic("claude-sonnet-4-6"),
    prompt: { system: "Draft a one-sentence reply to the customer's refund request." }
  })
  .humanGate("review") // the run stops here until a human approves
  .node("send", async (_input, state) => ({ reply: finalAnswer(state.channels.agentResult) }))
  .edge("draft", "review")
  .edge("review", "send")
  .compile();

// 1. Run: the agent drafts, then the run suspends at the gate.
const paused = await app.run({ request: "Please refund order #1024." });
console.log(paused.status); // "suspended"
console.log(finalAnswer(paused.channels.agentResult)); // the draft a human reviews

// 2. A human approved: resume from the checkpoint.
const done = await app.resume(paused.runId);
console.log(done.status); // "completed"
console.log(done.channels.reply);

What each part does:

  • channel declares a piece of run state. Nodes read channels and return the ones they change.
  • agentNode runs an LLM agent. It writes its result to the agentResult channel; finalAnswer() reads the answer out of it.
  • humanGate stops the run. run() returns with status "suspended".
  • resume continues from the checkpoint saved at the gate.

3. Run it​

With an Anthropic key:

ANTHROPIC_API_KEY=sk-ant-... npx tsx app.ts

Or offline, with the deterministic mock:

AILU_LLM_MOCK=1 npx tsx app.ts

You should see suspended, the draft, then completed and the reply.

What you just used​

In a real app, the gap between run() and resume() is where a person reviews the draft in your UI. Your server keeps the CompiledGraph and calls resume(runId) when they approve. To resume in a different process, after a deploy or a restart, see Long-running runs.

Next​