Document vault shows a per-file thumbnail: a server-rendered preview,
downscaled and re-encoded so location and camera metadata are dropped,
served only to the file's owner over an authenticated request. Files that
cannot be previewed keep their type icon. Generation is bounded — a header
sniff refuses an over-large source before decode, so a crafted image cannot
exhaust the preview worker.
Also folds in admin-managed central AI access — an administrator connects
one access on the server and each user opts in or keeps their own provider,
off until an admin turns it on — and trims the redundant documents-search
caption and per-file searchable/read badges.
Render a small JPEG preview for each stored document and show it at the
card's leading edge, falling back to the kind icon when none exists.
- Generate previews in the background on upload (new document-thumbnail
pg-boss queue) plus a boot-time corpus backfill for existing documents;
upload never blocks on or fails because of it. Images are downscaled via
@napi-rs/canvas, a PDF's first page is rasterised then downscaled, every
other type is skipped. Generation never throws.
- Store the preview encrypted at rest in a 1:1 DocumentThumbnail side table
(migration 0236) so the list/detail queries that omit the original blob
never drag the preview either. Same AES-256-GCM string codec + fail-closed
decrypt as the content index; wired into the key-rotation walk.
- Serve it through an owner-scoped GET /api/documents/inbound/[id]/thumbnail
(auth + module gate + userId-scoped query + fail-closed decrypt), always
image/jpeg + nosniff + private, no-store; 404 on miss. The card renders an
authed lazy <img>, onError falls back to the icon.
- Add hasThumbnail to the document DTO so the card only fetches a preview
that exists.
Also drop the "search looks inside your documents" caption from the overview
(the index-all prompt stays) and the per-card searchable marker; both were
noise. Remove the now-unused i18n keys across all six locales.
A link created from a document is now document-only: the create route forces an
empty report scope and the served view never aggregates a report, so the
recipient sees the attached document and no health data. Sharing from Settings
keeps the full record form. Earlier document links carry the full record and
should be revoked and re-created.
Sharing a single document from the vault minted a full-record share: the
create form always defaulted `resourceTypes` to ["Patient","Observation"]
and never signalled a documents-only intent, so the served /c/<token> view
aggregated the whole doctor report — every vital, lab, medication and
wellness figure — alongside the attached file. An empty section blob was
indistinguishable from "defaults", so the report always resolved to the
full record.
Introduce an explicit documents-only share:
- add a `documentOnly` flag to the create payload; when set the server
forces an empty report scope (all-off sections, no FHIR resource types,
FHIR API off) and requires at least one document, so a document link can
never widen into a record — whatever the body sends.
- gate the clinician-view aggregation on an enabled section: a share with
no section on never calls the report aggregator, so no health metric
leaves the database. The recipient sees only the attached document(s).
- the document detail Share action opens the create form in documents-only
mode: hide the FHIR toggle, the FHIR resource-type checkboxes and the
history-range selector, keep the picker/label/expiry/passphrase, and
always carry the launched document into the created link.
- Settings sharing keeps the full record-share form unchanged.
Extract the create-payload builder as a pure function and cover the scope
contract, the empty-scope data load, and the served-view metric-free
guarantee with tests; refresh the share e2e and regenerate the OpenAPI
contract.
Introduce an operator-level ChatGPT-subscription (Codex) credential that the
operator connects once and shares server-wide, plus a per-user switch to route
AI egress through it.
- Schema (migration 0235): three encrypted columns on AppSettings for the
operator's central Codex access/refresh tokens and the ChatGPT-Account-ID
claim, plus expiry/connected-at/status; a per-user useCentralCodex flag
(default false). Register the new encrypted columns in the rotation registry
and script.
- Resolution: add the admin-codex chain type; append it to a user's resolved
chain only when they opted in AND the operator connected it. Tokens refresh
server-side against the singleton row (CAS-style), same primitives as the
per-user Codex path.
- Budget: bill an admin-codex primary against the operator cost cap, not the
user plan — it drains the operator's account.
- Consent: admin-codex is server-managed external egress, gated by the existing
consent machinery (self-snapshot and document surfaces alike). No existing
consent path is weakened.
- Document order: rank admin-codex with the subscription tier (last), so the
document class stays local-first.
- UI: admin device-code connect/disconnect card (cookie-only admin routes) with
honest copy on account pooling, shared rate limits, and training-by-default;
a per-user opt-in switch shown only once the operator has connected it, off by
default, behind a one-time honesty confirm.
- i18n across all six locales; unit tests for the chain type, budget cap,
consent gate, vision capability, and document order; a mocked e2e for both
the admin connect surface and the per-user switch.
The central credential's tokens are encrypted at rest and never returned to a
non-admin API; the opt-in only takes effect once the operator has connected the
shared account.
Lab-report scanning now uses the configured AI provider, rasterizing a scanned
PDF to images for any non-Anthropic vision provider (parity with the document
vault). Removes the separate lab-scan provider setting and its columns
(migration 0234). The overdue-medication log action stacks directly under its
line on the dashboard instead of far to the right.
Lab-report OCR now rasterizes a PDF to page images for any non-Anthropic
vision provider, exactly as the document vault already does — Anthropic keeps
its native PDF block, every other vision provider (codex/OAuth, OpenAI, local)
reads the rendered pages. The capability probe reports `pdfSupported` whenever
the picked provider reads PDFs natively or the server-side rasterizer is
available, so the "scan a PDF" affordance shows for a codex provider too.
Drop the dedicated document-scan (Lab-OCR) provider: labs OCR always uses the
main configured provider chain. Removes the settings card, the `aiOcr*`
resolution branch, the GET/PATCH handler fields, the OpenAPI schema fields, the
i18n keys across all locales, and the five backing `User` columns (migration
0234). The on-device tesseract fallback is untouched.
Dashboard hero: stack the overdue-dose action directly beneath the verdict
text (tight gap, left-aligned) on every viewport instead of pushing it to the
far container edge on desktop.
Adds a Strava connection (BYO app keys, per-user, mirroring the other
wearables): activities arrive as workouts, de-duplicated against other sources
by the existing source-priority picker, workouts-only. Documents that Garmin has
no direct connector and flows in via Apple Health / Google Health Connect.
Migration 0233; new MeasurementSource STRAVA on /api/sync/changes.
Add Strava as a per-user BYO-OAuth workout source, mirroring the shipped
WHOOP/Oura/Polar pattern. Strava caps every new app at single-player mode, so
each self-hoster registers their own app and pastes the client id/secret into
Settings (falling back to a shared env app). Strava is a workout source only —
it exposes no daily metrics and no training-depth analytics are derived.
- Schema (migration 0233): per-user encrypted client id/secret + access/refresh
tokens, plaintext athlete id, incremental cursor, and backfill marker on
`User`; `STRAVA` added to `MeasurementSource`.
- Token model follows Oura's reactive-refresh-on-401 with a compare-and-set on
the stored refresh ciphertext, because Strava rotates its refresh token on
every refresh.
- Client over safeFetch: authorization-code + refresh, activity list + budget-
aware per-activity detail (for calories/HR), honouring the 200/15min cap; each
activity maps to one `Workout` row. Activity name/description stay in metadata
as data, never surfaced or interpolated.
- Dedup reuses the existing source-agnostic two-layer picker: `STRAVA` slots
into the workout ladder below the device-native wearables and above
MANUAL/IMPORT, so an Apple-Watch + Strava twin collapses to one canonical row.
- Poll-cohort hourly sync (:17) + self-converging boot backfill, wired into the
integration-sync registrar. Webhook deferred.
- OAuth routes (connect/callback/credentials/disconnect/status/test) with signed
state, cross-account re-auth rejection, and a surgical `www.strava.com`
connect-src gated to the Strava surfaces.
- Settings card + consolidated status envelope entry; env + compose whitelist;
i18n across all six locales.
- Garmin: no direct connector is possible (business-partner-only). Add
docs/integrations/garmin.md documenting the Apple Health / Google Health
Connect path and Garmin's withheld proprietary scores, cross-linked from both
platform docs, plus a non-connector info note in the Connections panel.
Regenerate docs/api/openapi.yaml for the new `STRAVA` MeasurementSource value.
The finish screen shows a clearly-labelled static sample briefing (zero egress)
and lays out setup local-first with a plain 'useful without AI' reminder; the
getting-started checklist gains a matching step that satisfies on connect or a
shared operator key.
Close the gap between the welcome carousel's AI promise and the payoff:
a fresh keyless user used to meet "No AI provider connected" on every AI
surface, because the only setup prompt was a skippable card on the final
screen.
Add an "insights" row to the getting-started checklist, derived from real
provider state — any personal key, local model, OAuth sign-in, or the
operator's shared key flips it done via /api/user/ai-provider. It persists
past onboarding, self-satisfies on connect, and dismisses like the others.
Elevate the done-screen AI card into a value-first panel: it leads with a
static, clearly-labelled example briefing (no model call, no egress, no
consent), then the local-first ladder — local model, bring-your-own-key,
subscription sign-in with the training caveat — and the honest line that
HealthLog is fully useful without AI. All three exits stay, so the panel
gates nothing. On a deployment with a shared provider it says so plainly.
Extract the worked example into a shared SampleBriefingCard. Add
onboarding.ai.* copy across all six locales and retire the old
single-card done-screen keys.
Chatting about a document opens the coach chat dialog scoped to that document,
entered from a neutral icon in the document's top-right (matching insights),
instead of a separate inline panel. The document chat's stricter footing is
unchanged — one document only, no health-record context, no tools, plain text.
Replace the collapsed bottom-of-card "Chat about this document" outline
button with a neutral, ghost Coach icon pinned to the top-right of the
document detail-sheet header, mirroring the Insights ask-coach affordance.
The icon uses the muted-foreground token only — never the primary/FAB
gradient — and opens a document-scoped chat drawer.
Present the chat in the Coach chat drawer chrome (right-side sheet on
desktop, bottom sheet on phones; same width caps; close-only, no maximize
or conversations rail) with a quiet "Chatting about: <document>" scope
badge. The drawer reuses the existing pure conversation body and the
existing client hooks, so it still posts /api/documents/inbound/[id]/chat
verbatim: no tools, no health snapshot, fenced document, inbound/replay
refusal, outbound screen, numeric grounding, consent + budget + per-user
rate bucket, indexed-only, plain-text render — the route is untouched.
Thread isolation is unchanged (the general Coach filters documentId: null;
the document route always scopes { documentId: id }).
Add a small reusable headerAction slot to ResponsiveSheet for the header
icon. Retire the DocumentChatPanel container and the AI-section chatSlot;
keep the pure DocumentChatConversation body and documentChatErrorKey.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01KPyLteNeTWwEC154X7vLWc
When automatic AI reading is on, the per-document AI action buttons no longer
appear (reading happens on upload); they return when it is off. The
AI-suggestion review drops its heading and grey sub-caption.
When "read documents automatically with AI" is on, the detail sheet no longer
shows the manual per-document action row (Read / Suggest / Summarise) — reading
already happens on upload, so the buttons only nagged. The section header and
the searchable status pill stay, and content search keeps working. With the
setting off the manual controls render exactly as before.
Drop the "review before saving" heading and its grey sub-caption from the
suggestion panel; the reviewable fields and the apply / dismiss controls stay.
Remove the now-unused documents.assist.reviewTitle / reviewHint keys from every
locale.
The per-view 'not saved · not a diagnosis' note was removed from the document
summary panel; the e2e no longer asserts it, keeping the transient/discard
contract.
The bundled (Turbopack) copy of pdfjs-dist failed its render path in the
standalone image with a bare Error, so a scanned PDF on a non-Anthropic
provider fell back to 'PDF scanning needs a Claude vision provider' — while the
identical un-bundled module rasterizes the same document fine (verified in the
container end to end on the real document). Externalize pdfjs-dist and
@napi-rs/canvas so the server loads the real modules, and hoist pdfjs-dist to
the top level in the image so the runtime import resolves. Also log the render
error message (not just its name) and drop the redundant 'not saved' note from
the document summary panel.
PDF rasterization failed at runtime — pdfjs-dist does a bare
require('@napi-rs/canvas') from its own directory, and the standalone image had
no top-level @napi-rs/canvas for Node's upward resolution to find, so pdfjs
could not polyfill DOMMatrix and every scanned-PDF read fell back to
'PDF scanning needs a Claude vision provider'. Hoist the canvas package and its
musl binary to /app/node_modules/@napi-rs via symlink into the pnpm store (the
prior per-package .node copy only fixed canvas's own loader, not pdfjs's
require). Verified in the container: resolves from pdfjs and renders.
Document reading no longer treats a signed-in subscription model as unable to
see images, so 'read with AI' works on that path instead of erroring; scanned
PDFs and photos are read the same way. Drops two now-redundant blurbs from the
document panel and, on the recovery insights page, moves each metric's
explanation into its own card instead of repeating the heading above it.
Remove the two per-document AI copy blocks in the document detail sheet:
the external-egress notice and the "read this document" explainer. The
settings-toggle honesty confirm already states the egress trade, so the
per-document repeat is redundant. Drop the now-unused `egressExternal`
prop and the `documents.ai.egressNotice` + `documents.ai.available` keys
across all six locales. Keep the capability `egress` DTO field — the API
still reports it.
On /insights/recovery, the metric block rendered an outer heading plus an
explainer above a tile whose own header repeated the same title. Move the
explainer inside the tile as a `description` beneath its `TileHeader` and
promote the tile title to a real `<h2>` (new `titleAs` affordance), so each
metric shows one heading with the blurb under it and the h1->h2 outline
stays nested. Applies to every metric the block renders.
The document/lab-OCR vision gate excluded every `-codex` slug from the
GPT-5.x line as text-only. That is stale: the `codex/responses` wire reads
an `input_image` block on these slugs (docs/codex-protocol-spec.md plus the
current model lineup), and the 5.2-Codex line is vision-tuned. An operator
pinned to a `-codex` slug therefore resolved no vision-capable provider and
hit a 422 "No vision-capable AI provider is configured" when reading a
document with AI.
Drop the `-codex` exclusion from the gpt-5 branch so a codex-only chain
resolves a document-vision provider; keep the `-mini`/`-preview`
reasoning-slug guard. Lab-OCR on a `-codex` pin gains vision the same way.
Per-medication effect view: plots the target metric/lab with start, dose
changes, and pauses marked, a before/after-start comparison, and adherence
overlaid — descriptive only, never a verdict or dose advice. Compact summary on
the medication insights area. Target resolved from ATC class or name, with a
per-user override. Migration 0232.
Add the per-medication "Wirkung" tab (hidden for one-shot and no-target meds)
rendering the target series with a start marker, dose-change markers, shaded
pause bands and a faint reference band, an adherence lane, a neutral
before/after-start card with honest empty states, an optional level-shift note,
and a retarget chooser. Weave a compact, read-only efficacy summary into the
Insights medication surface that reads the same DTO and links through to the
tab. All copy is descriptive; add a banned-verdict-verb guard test over the
medications.efficacy namespace across all six locales.
Add the migration (0232), Prisma model MedicationEfficacyTarget (persists ONLY
the user's explicit target override; everything else derives each read), and
the server builder buildMedicationEfficacy that composes the target's series,
a before/after-start comparison, the cadence-aware adherence lane (never
recomputed), an optional conservative level-shift note, honest data-floor
states and the retarget options into one strictly-descriptive DTO — no
verdict/score field by construction. Expose GET /api/medications/[id]/efficacy
and PUT /api/medications/[id]/efficacy/target, regenerate the OpenAPI contract.
Add an additive efficacy-target resolver alongside the existing metric-only
class map: a discriminated metric|lab target type, a WHO ATC class-prefix
table (consuming Medication.atcCode), and the statin/thyroid/supplement lab
classes the v1.22 map documented as a follow-on. Resolution order is ATC
prefix then whole-word name inference, conservative-fail to no target. The
existing MED_TARGET_MAP / inferMedTargetClass path stays byte-identical so the
adherence-storyline safety posture is untouched.
A layout-audit-driven consistency pass: one shared left edge for insight cards
(headings and body align, worst on mobile), no scroll past content on settings
and admin pages, Settings/Notifications only in the account menu on mobile, the
dashboard action beside its greeting text, and preventive-care/cycle/onboarding
cards on the shared card anatomy. The spacing and alignment rules are recorded
in the standards. Also stages the document rasterization native binding in the
image so a scanned PDF is read on an image-only AI provider.
Bring the structural card-anatomy offenders onto the spacing scale. The
cycle wellness-tile family (ring tile, phase-education, insight summary,
cycle view) and the insights wellness-scores tile drop banned p-5/px-5
py-5 for p-4 md:p-6 and keep their premium hue surface; their header and
info glyphs move off text-primary to foreground, spinners to muted. The
onboarding hand-rolled shells (anamnesis card, baseline form,
getting-started checklist, tour tooltip) drop p-5/space-y-5/rounded-2xl
for p-4 md:p-6/space-y-4/rounded-xl. settings/anamnesis-section moves its
three raw Card+CardTitle shells onto SettingsCard + SettingsCardHeader.
Establish one inset system on the Insights surface. SubPageShell's flat
px-6 header sat 8 px right of every card body on mobile — track the card
slot inset (px-4 md:px-6) so the heading-vs-body step disappears.
DeviceScoreTile and ResilienceTile hand-rolled a muted h-4 header row;
route them through TileHeader size=sm (foreground icon, shared gutter),
latest reading in the right slot. ScoreAnatomyView dropped its banned p-5
+ centred uppercase title for a left-aligned TileHeader on p-4 md:p-6, so
the ring hero stays a centred identity block while the header shares the
reading edge with the stacked assessment card. SparklineDeltaTile swaps
its hand-copied header row for the TileHeader primitive so it can't
drift, and its contributor label rounds off the sub-xs size.
Marc-André Bombeck