Answering a fair question: needing two settings in two repositories to agree
before one number changes is not a design anyone chose. It is two codebases each
assuming it owned the decision, and the symptom was a caller asking for 30
excerpts and silently receiving 12.
rerank_results computes min(reranker_top_k or limit, limit), so RERANKER_TOP_K=0
reads as "however many the caller asked for". The app setting is now the only
knob. Verified: Learning asks 30 and receives 30, the assistant asks 8 and
receives 8.
Zero costs nothing extra — the reranker is billed on documents sent, which is
candidate_limit and unchanged; top_n only decides how many come back. A real
number there is now what it should always have been: an optional hard ceiling
for when someone deliberately wants one, not an invisible default.
docs/retrieval-tuning.md covers the per-feature budgets, why the assistant's are
so much smaller than Learning's, that My Resources deliberately shares the
Learning budget, how to read what actually happened from the MCP logs and the
grounding field, and why raising these is not free.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Dv6sqaY6Vq3ChZHMem3cnU
The pathway existed but was reachable only by API. It now has a tab of its own
next to the Learning Hub — related, not the same thing, and sitting together is
how someone discovers the difference — visible to every signed-in user with no
role gate in the markup.
Generate a deck or an article, see everything you have made, download each as
PowerPoint, Word or PDF, delete what you no longer want. The screen says
"Private to you" and "Nobody else sees these", because the distinction from
published Learning content is the thing a person needs to understand before
typing a patient's condition into it.
Downloads are fetched rather than linked: an <a href> cannot carry the
Authorization header. The blob is saved under the filename the server chose and
the object URL is revoked afterwards. Resource titles come from a model, so rows
are built as elements and a title is only ever assigned to textContent.
The e2e stack now joins danvics_convert too. It could previously reach only
Postgres and Redis, so a PDF download failed there in a way production would
not — which did at least prove the degradation path works: with Gotenberg
unreachable the response is "PDF conversion is unavailable right now. PowerPoint
and Word still work", and the other two formats download unaffected.
Verified in a browser as an ordinary user: the tab appears and opens, the form
swaps slide count for word count when the format changes, the library lists
their own work, and pptx, docx and pdf all download with sensible filenames
(36360, 13285 and 68310 bytes).
Also documents retrieval sizing in docs/retrieval-tuning.md — the per-feature
budgets, and RERANKER_TOP_K, which caps all of them and had until now appeared
in no configuration file at all.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Dv6sqaY6Vq3ChZHMem3cnU
