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Documentation Index

Fetch the complete documentation index at: https://docs.memwal.ai/llms.txt

Use this file to discover all available pages before exploring further.

The recommended default client. The relayer handles embeddings, SEAL encryption, Walrus upload, and vector indexing.

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How It Works

  1. The SDK signs each request with your delegate key
  2. The relayer verifies delegate access
  3. remember returns an accepted job while the relayer encrypts, uploads, and indexes in the background
  4. recall searches by Memory Space and returns decrypted matches
import { MemWal } from "@mysten-incubation/memwal";

const memwal = MemWal.create({
  key: "<your-ed25519-private-key>",
  accountId: "<your-memwal-account-id>",
  serverUrl: "https://your-relayer-url.com",
  namespace: "chatbot-prod",
});

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Core Methods

// Store a memory
const job = await memwal.remember("User prefers dark mode and works in TypeScript.");
await memwal.waitForRememberJob(job.job_id);

// Recall relevant memories
const result = await memwal.recall("What do we know about this user?", 5);

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

// Check relayer health
await memwal.health();

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Restore

Rebuild missing indexed entries for one namespace. Incremental, namespace-scoped, and meant to repair PostgreSQL vector state from Walrus-backed memory. 
const result = await memwal.restore("chatbot-prod", 50);

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Lower-Level Methods

Use these when you already have a vector or encrypted payload:
  • rememberManual({ blobId, vector, namespace? })
  • recallManual({ vector, limit?, namespace? })
  • embed(text)