108733a2a2
Those extensions don't support building with PostgreSQL 18, yet. To make sure the broken status is updated on the next upgrade, they all have version checks in the form of an evaluation warning, so that there has be explicit action regarding its PG18 compatibility.
81 lines
2.4 KiB
Nix
81 lines
2.4 KiB
Nix
{
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buildPgrxExtension,
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cargo-pgrx_0_12_6,
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postgresql,
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fetchFromGitHub,
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lib,
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postgresqlTestExtension,
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}:
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buildPgrxExtension (finalAttrs: {
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pname = "pgvectorscale";
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version = "0.7.0";
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src = fetchFromGitHub {
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owner = "timescale";
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repo = "pgvectorscale";
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tag = finalAttrs.version;
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hash = "sha256-dy481k2SvyYXwwcsyLZSl3XlhSk9C5+4LfEfciB1DK4=";
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};
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doCheck = false;
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cargoHash = "sha256-CeRyDn9VhxfjWFJ1/Z/XvOUQOSnDoHHZAqgfYTeKU0o=";
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cargoPatches = [
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./add-Cargo.lock.patch
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];
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cargoPgrxFlags = [
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"-p"
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"vectorscale"
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];
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inherit postgresql;
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cargo-pgrx = cargo-pgrx_0_12_6;
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passthru.tests.extension = postgresqlTestExtension {
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inherit (finalAttrs) finalPackage;
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withPackages = [ "pgvector" ];
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sql = ''
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CREATE EXTENSION vectorscale CASCADE;
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CREATE TABLE document_embedding (
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id BIGINT PRIMARY KEY GENERATED BY DEFAULT AS IDENTITY,
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embedding VECTOR(3)
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);
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INSERT INTO document_embedding (id, embedding) VALUES
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(10, '[1,2,4]'),
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(20, '[1,2,5]');
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CREATE INDEX document_embedding_idx ON document_embedding
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USING diskann (embedding vector_cosine_ops);
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'';
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asserts = [
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{
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query = "SELECT id FROM document_embedding WHERE embedding <-> '[1,2,3]' = 1";
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expected = "10";
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description = "Expected vector of row with ID=10 to have an euclidean distance from [1,2,3] of 1.";
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}
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{
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query = "SELECT id FROM document_embedding WHERE embedding <-> '[1,2,3]' = 2";
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expected = "20";
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description = "Expected vector of row with ID=20 to have an euclidean distance from [1,2,3] of 2.";
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}
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];
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};
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meta = {
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# PostgreSQL 18 support issue upstream: https://github.com/timescale/pgvectorscale/issues/249
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# Check after next package update.
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broken =
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lib.warnIf (finalAttrs.version != "0.7.0") "Is postgresql18Packages.pgvectorscale still broken?"
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(lib.versionAtLeast postgresql.version "18");
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homepage = "https://github.com/timescale/pgvectorscale";
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teams = [ lib.teams.flyingcircus ];
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description = "Complement to pgvector for high performance, cost efficient vector search on large workloads";
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license = lib.licenses.postgresql;
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platforms = postgresql.meta.platforms;
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changelog = "https://github.com/timescale/pgvectorscale/releases/tag/${finalAttrs.version}";
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};
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})
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