Midlibrary Explorer

This is a demo of Discovery Search powered by Qdrant. It demonstrates how you can use vector similarity search in a scenario, where it is hard to construct a search query.

The demo uses the following major components

• NextJS
• Qdrant JS Client

Quick Start

Set up a Qdrant instance

You can create a free instance at https://cloud.qdrant.io/.

OR

For local deployment

docker run -p 6333:6333 qdrant/qdrant

Prepare Qdrant Collection

Download the Midjourney dataset snapshot using the Qdrant dashboard.

Run The Project

OR

For local deployment

• Set the required environment variables in a .env file.
• Run the following commands.

$ npm install

$ npm run dev

The application should now be accessible at http://localhost:3000

⚖️ LICENSE

Apache 2.0 © Qdrant