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withMemWal

Drop-in memory middleware for Vercel AI SDK apps.

import { generateText } from "ai";
import { withMemWal } from "@mysten-incubation/memwal/ai";
import { openai } from "@ai-sdk/openai";

const model = withMemWal(openai("gpt-4o"), {
  key: "<your-ed25519-private-key>",
  accountId: "<your-memwal-account-id>",
  serverUrl: "https://your-relayer-url.com",
  namespace: "chatbot-prod",
  maxMemories: 5,
  autoSave: true,
});

const result = await generateText({
  model,
  messages: [{ role: "user", content: "What do you know about me?" }],
});

What it does​

Before generation:

  • Reads the last user message
  • Runs recall() against Walrus Memory
  • Filters by relevance
  • Injects memory context into the prompt

After generation:

  • Optionally runs analyze() on the user message
  • Saves extracted facts asynchronously

Set a namespace explicitly for each product surface that uses the middleware. Otherwise recalled and auto-saved memories fall back to "default".

When to use direct SDK calls instead​

Use direct SDK methods when your app needs precise control over:

  • When memory is stored
  • Which text is analyzed
  • How recall results are displayed or filtered