A scan sent the whole report to one call under an 8000-token ceiling and
validated the reply against a 100-row envelope. A long multi-panel report
lost everything either way: the reply stopped mid-row and failed to parse,
which the person saw as "try a clearer photo", or it held more than 100
rows and the schema refused all of them. One malformed row refused the lot
as well. Reasoning models made it worse, because the call sent no
reasoning setting and OpenAI, Codex and Claude's 5 generation reason by
default against the same output allowance.
A PDF of more than one page is now rendered and read a page per call on
every provider (up to 20 pages), as many reads as the run's deadline
allows, and the pages are merged in order with a reading printed twice
listed once. A photo, a one-page PDF on a provider that reads PDFs, and
OCR'd text up to 4000 characters stay one read; longer text is split at
line boundaries. Each read carries an explicit reasoning off, so a model
that can stop reasoning does and one that cannot gets its minimum budget
on top of the answer's. A reply cut at the output limit is detected from
the finish reason (Codex's incomplete stream included), keeps the rows
that closed before the cut and is named in the result instead of retried;
when no read produced a row the run fails as labs.ocr.outputLimit. A
provider failure after the first page keeps the pages already read.
Rows are validated one by one, the row cap is 400 for the scan and the
commit, and a report past it keeps its first 400 and says how many it
had. The run settles what the provider reported it spent rather than the
fixed reservation, so a page-by-page read still counts against the day's
budget in full.
Add resolveReasoning, the one decision for how hard a call may think:
the operator's switch, then the provider's ability, then the requested
level (the person's Coach preference, or a background job's own level),
then the operator's cap, then a medium ceiling when the operator pays.
The answer names the layer that decided it.
loadReasoningControls reads the two app_settings columns, memoised per
request, read afresh in background runs, and fails closed to "off".
loadCoachReasoningState resolves the published Coach state from the
memoised provider presence; resolveJobReasoning resolves one background
call and never fails it.
A guard proves the switch and the cap over the whole input space and
requires every call that carries reasoning to take it from the
resolver.
Marc-André Bombeck