turbomem

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Embedded agent memory for TypeScript. Local-first by default, runs inside your Node or Bun process or in the browser with IndexedDB-backed PGlite. Pluggable to edge and serverless with Upstash Vector or Pinecone. No separate memory server, no Python sidecar.

Install

npm install turbomem

Set OPENAI_API_KEY for the default OpenAI embeddings and fact-extraction stack. PGlite is included; no extra database setup. For the optional sqlite-vec backend: npm install better-sqlite3 sqlite-vec. For edge deployment with Upstash Vector: npm install @upstash/vector - see the Edge guide. For Pinecone: npm install @pinecone-database/pinecone@^8 see the Storage guide. For browser apps, import from turbomem/browser see the Browser guide.

Providers: embeddings via OpenAI, local (transformers), Voyage AI (VOYAGE_API_KEY), or Google Gemini (GEMINI_API_KEY); fact extraction via OpenAI, Anthropic, or Google Gemini (plus any OpenAI-compatible endpoint via a custom baseURL). See the Providers reference.

Quick start

import { TurboMemory } from "turbomem";

const memory = new TurboMemory({
  embeddings: "openai", // or "local" | "voyage" | "google"
  storage: "pglite",
  extraction: { provider: "openai", model: "gpt-4.1-mini" },
  openai: { apiKey: process.env.OPENAI_API_KEY },
});

await memory.init();

await memory.add(
  [{ role: "user", content: "I love hiking and I'm training for a half marathon this fall." }],
  { userId: "user_123" },
);

const results = await memory.search("What outdoor activities is the user into?", {
  userId: "user_123",
  limit: 5,
});

for (const { memory: m, score } of results) {
  console.log(`[${score.toFixed(3)}] ${m.content}`);
}

await memory.close();

The example above uses OpenAI (text-embedding-3-small by default). You can also use local transformers, Voyage AI, or Google Gemini via the embeddings preset, or pass a custom adapter for a specific model, see the Providers reference.

Framework adapters

| Package | Use case | | -------------------------------------------------------------------------- | ---------------------- | | @turbomem/mastra | Mastra memory provider | | @turbomem/vercel-ai | Vercel AI SDK tools |

CLI

| Package | Use case | | -------------------------------------------------------------- | -------------------------- | | @turbomem/cli | Terminal memory management |

Documentation

Full guides, configuration reference, and runnable examples:

https://turbomem.dev · https://docs.turbomem.dev

Requirements

Node.js 20+ or Bun. TypeScript recommended.

License

Apache License 2.0