qdrant/qdrant-js

JavaScript/Typescript SDK for Qdrant Vector Database

What it solves

It provides a way for developers using JavaScript and TypeScript to interact with the Qdrant vector search engine, allowing them to manage collections and perform vector searches within their applications.

How it works

The project consists of three packages: a main SDK, a lightweight REST client, and a gRPC client. These clients allow users to connect to Qdrant instances running locally via Docker or hosted on Qdrant Cloud, using standard API calls to interact with the engine.

Who it’s for

Developers building AI applications with JavaScript or TypeScript across various environments, including Node.js, Deno, browsers, and Cloudflare Workers.

Highlights

  • Supports multiple communication protocols via REST and gRPC clients.
  • Full TypeScript type support for better developer experience.
  • Compatible with a wide range of environments including Node.js, Deno, and Cloudflare Workers.

Related

  • Project
    qdrant/rust-client

    A native Rust client for Qdrant, enabling high-performance vector search and database management within Rust applications.

  • Project
    qdrant/qdrant-client

    A Python client library and SDK for the Qdrant vector search engine, enabling efficient storage and retrieval of vector embeddings.

  • Project
    qdrant/go-client

    A Go client library for the Qdrant vector search engine, providing utilities to manage collections and perform similarity searches.

  • Project
    openai/openai-node

    The official TypeScript and JavaScript library for the OpenAI REST API, providing type-safe access to text, vision, and real-time AI models.

  • Project
    google/adk-js

    A code-first TypeScript toolkit for building, orchestrating, and deploying AI agents with full type safety and support for both Node.js and browser environments.