@ledgermem/vercel-ai

LedgerMem adapter for the Vercel AI SDK. Drop-in tool() definitions that let any model search and write persistent memory, plus a small React hook for client-side memory views.

Install

npm install @ledgermem/vercel-ai @ledgermem/memory ai

Set LEDGERMEM_API_KEY and LEDGERMEM_WORKSPACE_ID in your environment, or pass them explicitly.

Quickstart (30 seconds)

import { streamText } from "ai";
import { openai } from "@ai-sdk/openai";
import { ledgermemTools } from "@ledgermem/vercel-ai";

const result = await streamText({
  model: openai("gpt-4o"),
  tools: ledgermemTools, // memorySearch + memoryAdd
  maxSteps: 5,
  messages: [{ role: "user", content: "What did I tell you about my coffee?" }],
});

for await (const chunk of result.textStream) process.stdout.write(chunk);

Per-user memory (route handler)

import { createLedgerMemTools } from "@ledgermem/vercel-ai";

export async function POST(req: Request) {
  const { messages, userId } = await req.json();
  const tools = createLedgerMemTools({ metadata: { userId } });
  return streamText({ model: openai("gpt-4o"), tools, messages }).toDataStreamResponse();
}

React hook

"use client";
import { useLedgerMem } from "@ledgermem/vercel-ai/react";

export function MemorySidebar() {
  const { results, search, loading } = useLedgerMem({ initialQuery: "preferences" });
  return (
    <ul>
      {results.map((m: any) => <li key={m.id}>{m.content}</li>)}
    </ul>
  );
}

License

MIT