SqlHydra.Query.Pgvector 0.1.0-alpha.1

SqlHydra.Query.Pgvector

Vector similarity search for SqlHydra.Query, powered by pgvector.

Write select and ORDER BY queries that compare embeddings by cosine, L2 (Euclidean), or inner-product distance — all in strongly-typed F#, with the native pgvector operators (<=>, <->, <#>) generated for you. It also teaches the SqlHydra code generator about vector columns so they come through as Pgvector.Vector in your generated types.

Before you start

You'll need:

• A PostgreSQL database with the pgvector extension enabled (CREATE EXTENSION vector;) and a table with a vector column.
• SqlHydra.Query set up for that database. If you're new to SqlHydra, start with its docs — this package just adds vector search on top of the queries you already write.

Installation

dotnet add package SqlHydra.Query.Pgvector

Searching by similarity

Open the package alongside SqlHydra.Query, then use the distance functions in a query. queryVector below is your search embedding — the Pgvector.Vector you want to find the nearest rows to.

open SqlHydra.Query
open SqlHydra.Query.Pgvector.PgvectorExtensions
open type SqlHydra.Query.Pgvector.PgvectorExtensions.PgvectorFn

// Return each document together with how far it is from your query vector:
select {
    for d in documents do
        select (cosine_distance (d.embedding, queryVector))
}

// Find the 10 closest documents (nearest-neighbour search):
select {
    for d in documents do
        orderByCosineDistance d.embedding (box queryVector)
        take 10
}

That's it — no setup or registration call is required.

Available distance functions

Use these inside select to get a distance back as a column:

Use these to order results from closest to farthest:

The query vector is always sent as a query parameter, so it's safe to pass user input.

Generating types for vector columns

So that SqlHydra generates a Pgvector.Vector property for each vector column, add this package to the [extensions] section of your SqlHydra generator TOML:

[extensions]
type_mappings = ["SqlHydra.Query.Pgvector"]

Re-run dotnet sqlhydra and your vector columns will come through as Pgvector.Vector.

Building this project

Tasks are driven by mise:

mise run build    # build the solution
mise run test     # run all tests (the integration tests need Docker)
mise run ci       # the full gate: format check + build + test
mise run format   # format with Fantomas

The integration tests spin up a real PostgreSQL + pgvector container via Testcontainers, so they need a running Docker daemon. To run only the in-process unit tests without Docker:

dotnet test --solution SqlHydra.Query.Pgvector.slnx \
    --filter-not-trait "Category=Integration"

License

MIT