Collapsing the caption text into `get_pictures_grouped` served the enrichment
path, which uses it, but the multimodal reranker discards the second return value
while still paying to read the column. That is the widest fan-out in the codebase,
`limit * 10` candidates, and it previously projected self_ref and picture_data
alone.
`with_text` is opt-in and off by default, so the cheap projection is what a caller
gets unless it asks for more. The reranker test asserts the projection as well as
the query count, since a count alone would not notice the column coming back.
Splitting the assembly into a passthrough pass and an expandable pass reordered
equal-scored results: the score sort that follows is stable, so the order results
arrive in is the tiebreak. Results are assembled in document_groups order again,
after the batched fetch rather than around it.
Also ports the caption negative cases the removed single-document test carried: a
table's caption and an ordinary text reference map to no picture.
`_populate_image_data` ran its stages once per result document, so a result set
spanning N documents cost 4N `document_items` queries. Measured on a remote
object-store corpus, a limit=5 search with expansion was 18 queries, 16 of them
against `document_items`.
The stages now run once each across every document, and flat in document count:
two queries for the dependent caption-to-picture mapping when results ranked on a
caption, one for the picture bytes. Two queries for a picture-ref result set,
three at most.
Picture text comes back with the bytes rather than from a second query, since it
is on the same rows.
Predicates are per document, `(document_id = 'a' AND self_ref IN (…)) OR (…)`,
rather than `self_ref IN (union)`. self_ref and position values repeat across
documents, so a union predicate would return other documents' rows: for
picture_data that fetches blobs nobody asked for, and it can hand one document
another document's picture.
