Compute Embeddings for Records

Compute embedding vectors for records using an Embedding_Strategy. This is a backend-specific generic that handles data retrieval, text assembly, and embedding computation via tidyllm.

Embedding is the expensive part of a vector match, so each record is embedded once and the vector is reused on later calls. The data.table and tibble backends keep a per-session cache keyed by model and record content; the DuckDB backend reuses through its persisted embeddings column. Reuse is controlled by the joinery.embedding_reuse and joinery.embedding_cache_dir options (see joinery package options) and can be cleared with clear_embedding_cache().

Usage

compute_embeddings(data, id, strategy, ...)

Arguments

data

A data.frame / tibble / data.table (or db table in other backends).

id

Character scalar naming the ID column in data.

strategy

An Embedding_Strategy object specifying columns, embedding model, and normalization settings.

...

Additional arguments passed to backend-specific methods.

Value

A backend-specific table with columns: id and embedding (where embedding contains numeric vectors).

See also

clear_embedding_cache()