Skip to main content

Examples

Basic: store and recall​

The shortest working Walrus Memory example using the default relayer-backed SDK.

import { MemWal } from "@mysten-incubation/memwal";

const memwal = MemWal.create({
  key: process.env.MEMWAL_PRIVATE_KEY!,
  accountId: process.env.MEMWAL_ACCOUNT_ID!,
  serverUrl: process.env.MEMWAL_SERVER_URL,
  namespace: "demo",
});

await memwal.health();

const accepted = await memwal.remember(
  "User prefers dark mode and works in TypeScript."
);
const stored = await memwal.waitForRememberJob(accepted.job_id);

const recalled = await memwal.recall({
  query: "What do we know about this user?",
  limit: 5,
});

console.log(stored.blob_id);
console.log(recalled.results);

What you should see:

  • health() succeeds
  • remember() returns a job_id immediately
  • waitForRememberJob() returns a blob_id
  • recall() returns plaintext results for the same namespace

Manual registration​

Use rememberManual() when you already have an encrypted payload plus vector, and recallManual() when you already have a query vector.

Fact extraction​

Use analyze() when you want the relayer to extract facts from longer text and store them as memories.

const analyzed = await memwal.analyze(
  "I live in Hanoi, prefer dark mode, and usually work late at night."
);
console.log(analyzed.facts, analyzed.job_ids);

AI Middleware​

Use withMemWal when you want recall before generation and optional auto-save after generation. See AI Integration for the full setup.

Research app pattern​

Use this when you want to store structured research findings and recall them in later sessions.

  1. Submit a structured summary with remember() and wait for completion when immediate recall is needed
  2. Generate targeted queries later
  3. Use recall() to pull relevant findings back into context

Structured summaries usually recall better than raw transcripts because they keep the signal high.