Redis VSS

Redis offers low-latency vector search capabilities. This tutorial shows how to add Redis VSS to a Relevance AI chain.

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Prerequisites

A running Redis instance with RediSearch (v2.6+) and RedisJSON (v2.4+) module installed. See Redis VSS for more information.

You can also run Redis on a cloud provider such as Redis Enterprise Cloud.

Alternatively, you can run Redis locally using Docker (we recommend redis-stack):

docker run -d --name redis-stack -p 6379:6379 -p 8001:8001 redis/redis-stack:latest # to run Redis with RediSearch and RedisJSON modules

ngrok tcp 6379 # to expose Redis port to the internet

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Setting up the integration

To connect Relevance AI to your Redis cluster, you need to provide the connection string. This will be in the following format:

redis://<username>:<password>@<host>:<port>/<db>

Once you have your connection string, you can head to Keys in the Relevance AI dashboard and look for Redis connection string. Paste in your connection string and hit enter.

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Adding Redis VSS to a chain

If you’re using the SDK, to add Redis VSS you can simply do the following:

const { results } = step('redis_search', {
    index: 'redis-index-prefix',
    query: 'what is the capital of France?',
    vector_field: 'embedding_field',
    model: 'text-embedding-ada-002', // make sure to provide your OpenAI API key to use this model
    page_size: 4
});

If you’re using the Notebook, go to the transformation library from the sidebar and search for “Redis”. You will now see the Redis VSS step where you can fill out the variables.