pgvector-ruby

pgvector support for Ruby

Supports pg and Sequel

For Rails, check out Neighbor

Installation

Add this line to your application’s Gemfile:

gem "pgvector"

And follow the instructions for your database library:

pg
Sequel

Or check out some examples:

Embeddings with OpenAI
Binary embeddings with Cohere
Sentence embeddings with Informers
Hybrid search with Informers (Reciprocal Rank Fusion)
Sparse search with Transformers.rb
Morgan fingerprints with RDKit.rb
Topic modeling with tomoto.rb
User-based recommendations with Disco
Item-based recommendations with Disco
Horizontal scaling with Citus
Bulk loading with COPY

pg

Enable the extension

conn.exec("CREATE EXTENSION IF NOT EXISTS vector")

Optionally enable type casting for results

registry = PG::BasicTypeRegistry.new.define_default_types
Pgvector::PG.register_vector(registry)
conn.type_map_for_results = PG::BasicTypeMapForResults.new(conn, registry: registry)

Create a table

conn.exec("CREATE TABLE items (id bigserial PRIMARY KEY, embedding vector(3))")

Insert a vector

embedding = [1, 2, 3]
conn.exec_params("INSERT INTO items (embedding) VALUES ($1)", [embedding])

Get the nearest neighbors to a vector

conn.exec_params("SELECT * FROM items ORDER BY embedding <-> $1 LIMIT 5", [embedding]).to_a

Add an approximate index

conn.exec("CREATE INDEX ON items USING hnsw (embedding vector_l2_ops)")
# or
conn.exec("CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100)")

Use vector_ip_ops for inner product and vector_cosine_ops for cosine distance

Sequel

Enable the extension

DB.run("CREATE EXTENSION IF NOT EXISTS vector")

Create a table

DB.create_table :items do
  primary_key :id
  column :embedding, "vector(3)"
end

Add the plugin to your model

class Item < Sequel::Model
  plugin :pgvector, :embedding
end

Insert a vector

Item.create(embedding: [1, 1, 1])

Get the nearest neighbors to a record

item.nearest_neighbors(:embedding, distance: "euclidean").limit(5)

Also supports inner_product, cosine, taxicab, hamming, and jaccard distance

Get the nearest neighbors to a vector

Item.nearest_neighbors(:embedding, [1, 1, 1], distance: "euclidean").limit(5)

Add an approximate index

DB.add_index :items, :embedding, type: "hnsw", opclass: "vector_l2_ops"

Use vector_ip_ops for inner product and vector_cosine_ops for cosine distance

History

View the changelog

Contributing

Everyone is encouraged to help improve this project. Here are a few ways you can help:

Report bugs
Fix bugs and submit pull requests
Write, clarify, or fix documentation
Suggest or add new features

To get started with development:

git clone https://github.com/pgvector/pgvector-ruby.git
cd pgvector-ruby
createdb pgvector_ruby_test
bundle install
bundle exec rake test

To run an example:

cd examples/loading
bundle install
createdb pgvector_example
bundle exec ruby example.rb