Quickstart for Vector
This page describes how to get up and running quickly with Aerospike Vector Search (AVS) using Docker.
Request a 60-day free trial feature-key file with the vector-service
option enabled to install AVS locally.
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
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
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.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
Start the database, AVS, and the search application.
docker-compose -f ./aerospike-vector/prism-image-search/docker-compose.yml up -d
After a few minutes, navigate to http://localhost:8080/search and search your photos.
Next Steps
After completing the quickstart, you can do the following:
Install
asvec
: Theasvec
tool is a command line interface (CLI) for managing AVS.Create a data pipeline: This page outlines various approaches for generating vector embeddings that you can use on your own data.