pghybrid

Hybrid search on the Postgres you already have.

Vector similarity + full-text search, combined by Reciprocal Rank Fusion, on plain pgvector. No pg_search, no VectorChord, no Elasticsearch, no vector database, no extension you need superuser to install.

npm install pghybrid

Zero runtime dependencies. pghybrid generates SQL and hands it to the driver you already use, node-postgres, postgres.js, Drizzle, Supabase. It never opens a connection of its own and never calls an embedding provider.

import { HybridSearch } from "pghybrid";

const search = new HybridSearch(
  { table: "chunks", textColumn: "content", vectorColumn: "embedding", tsvectorColumn: "fts" },
  (sql, params) => pool.query(sql, params).then((result) => result.rows),
);

const rows = await search.search("renewal notice period", { embedding, limit: 10 });
for (const row of rows) {
  console.log(row.score, row.matchedBy, row.row.title);
}

Read the statement instead of running it:

const { sql, params } = search.buildQuery("renewal notice period", { embedding, limit: 10 });

This package is the TypeScript half of pghybrid. It generates byte-identical SQL to the Python package, which is checked on every commit rather than assumed.

Full documentation, the reasoning, and the copy-and-paste SQL: github.com/pavangupta352/pghybrid.

MIT © Pavan Gupta