@langchain/turbopuffer

This package contains the LangChain.js integration for the turbopuffer vector database.

Installation

npm install @langchain/turbopuffer @turbopuffer/turbopuffer

Usage

import { Turbopuffer } from "@turbopuffer/turbopuffer";
import { TurbopufferVectorStore } from "@langchain/turbopuffer";
import { OpenAIEmbeddings } from "@langchain/openai";

const client = new Turbopuffer({ apiKey: process.env.TURBOPUFFER_API_KEY });

const vectorStore = new TurbopufferVectorStore(new OpenAIEmbeddings(), {
  namespace: client.namespace("my-namespace"),
});

const ids = await vectorStore.addDocuments([
  { pageContent: "Hello world", metadata: { source: "greeting" } },
]);

const results = await vectorStore.similaritySearch("hello", 1);

await vectorStore.delete({ ids });

Configuration

Option	Description	Default
namespace	A configured turbopuffer Namespace instance	Required
distanceMetric	"cosine_distance" or "euclidean_squared"	"cosine_distance"

Add Options

Option	Description	Default
ids	Custom IDs for documents	Auto-generated UUIDs
batchSize	Batch size for upserts	3000

Filtering

const results = await vectorStore.similaritySearch("query", 10, [
  "category",
  "Eq",
  "books",
]);

Development

pnpm install
pnpm build
pnpm test
pnpm test:int
pnpm lint && pnpm format