Quick start

This page describes how to get up and running quickly with Aerospike Vector Search (AVS) using Docker.

Tip

Request a 60-day free trial feature-key file with the vector-service option enabled to install AVS locally.

1. Clone the examples repository.

   The AVS repository contains several pre-configured example applications for deploying and using AVS.

   git clone https://github.com/aerospike/aerospike-vector

2. Copy your feature-key file.

   Your feature-key file must be named features.conf and be located in following location.

   cp ~/Downloads/features.conf ./aerospike-vector/prism-image-search/container-volumes/avs/etc/aerospike-vector-search

3. Index your photos.

   Use the prism-image-search application to index your photos. This application uses the OpenAI CLIP model to create embeddings for your photos. These embeddings are indexed in AVS, and you can perform a semantic search on the index. The sample application included in the Docker Compose file already implements a semantic search feature.

   Use the following command to copy .jpeg and .jpg files from your ~/Pictures directory to be indexed.

   rsync -av --include='*/' --include='*.jp*' --exclude='*' ~/Pictures ./aerospike-vector/prism-image-search/container-volumes/prism/images/static/data

4. Start the database, AVS, and the search application.

   docker-compose -f ./aerospike-vector/prism-image-search/docker-compose.yml up -d

5. After a few minutes, navigate to http://localhost:8080/search and search your photos.

Next Steps

After completing the quick start, you can do the following:

Install asvec The asvec command line interface (CLI) is a tool for managing AVS.

Create a data pipeline This page outlines various approaches for generating vector embeddings that you can use on your own data.