Asking the Coach about a document opened a separate, half-finished chat panel
that never appeared in Coach history. The bespoke drawer is gone; a document
conversation now opens the real Coach view, appears in the Coach list with a
document badge and a "Chatting about: <title>" note, and is read back through
the same history rail as any other thread.
The prompt-injection fence is unchanged and stays server-side. A document turn
is still sent through the hardened fenced endpoint (no tools, no health
snapshot, grounded in the document text only); the coach tool route continues
to fetch with documentId null, so a document-scoped conversation can never be
continued through the tool loop even from a hostile client. Only the surface
moved into the Coach; the boundary did not.
The relaxed conversation-list and detail filters drop only the documentId
predicate — userId scoping is unchanged, so a document thread is still visible
only to its owner. CoachConversationDTO gains documentId + documentTitle
(server-derived, title/filename only); no schema change (documentId exists
since 0230). OpenAPI regenerated.
Add a single switch in AI settings — off by default — that turns on ambient AI
reading of uploaded vault documents. Turning it on reveals a once-shown,
vendor-blind honesty confirm (subscription providers may use the content to
improve their models; a self-hosted local model never egresses) that must be
acknowledged before the setting is written. Copy is translated across all six
locales.
Add a scoped 'Chat about this document' panel beneath the Read-with-AI
actions. Opens a conversation grounded only in the document's stored text:
a message list + input streaming the assistant reply token-by-token over
the SSE route, with prior turns loaded via GET.
- Availability: the panel renders in the provider-available branch of the
AI section (a pure chatSlot keeps the section statically renderable), and
gates internally on whether the document is content-indexed. Not indexed
shows a calm read-it-first hint, never an error.
- Plain-text only: assistant prose renders via ProseBlocks / StreamedProse
as React children (no markdown library, no dangerouslySetInnerHTML).
- Streaming reuses the Coach SSE frame parser; the wire frames are a subset.
- A one-line safety note states answers describe the document and are not
medical advice, consistent with the summary panel's not-a-diagnosis.
- Query keys via the central factory; history invalidated on the done frame.
- i18n x6 for every new string.
Add GET /api/documents/inbound/capability (document provider order + vendor-blind
egress class), repoint the vault capability hook to it, and show a per-egress
notice in the detail sheet before a document read leaves the machine. Cover the
document provider order, the egress consent gate, and the notice with tests.
i18n x6 + OpenAPI regenerated.
Co-Authored-By: Marc-André Bombeck
The illness-episode detail gains a Dokumente card: the episode's most
recent linked documents as compact rows (deep-linking into the vault,
where ?doc= now opens the detail sheet directly), a link-existing picker
(searchable, toggle rows driving the idempotent bulk link/unlink), an
upload entry that lands pre-linked via the episode filter, and a
filtered show-all view. Module-gated — accounts without the documents
module see nothing. An episode without documents keeps a quiet one-line
affordance instead of an empty card. The preview and picker reads get
their own query keys; reusing the vault list key would collide with the
infinite-query shape.
Refs: document-vault plan W3-T4
URL-backed facets (q / kind / episode / year) parse and serialise through
one pure helper pair so deep links round-trip byte-stable; the API search
builder pins the timeline sort. Month bucketing + row chunking feed the
virtualized grid as a flat item list. The upload-response parser owns the
duplicate contract: HTTP 200 with envelope-level meta.duplicate returns
the existing row, every 413/415 reason maps to a translated-copy class,
and proxy-stripped bodies fall back to the HTTP status. Query keys move
to the vault filter shape and gain the usage read.
Plan-Task: W2-T1 (URL state), W2-T5 (keys)
Evolve the inbound-documents screen into a real document library on top of
the store-first backend.
- Upload stays store-only and always works: the form now files a document
with an optional title, category, and document date in one step. Extraction
is a separate, explicit action.
- List becomes an organized library: documents grouped by date, with a title
(filename fallback), category and status badges, and pending/fact counts. A
toolbar adds title/filename search, a category filter, and a sort control
(document date / date added / title, asc/desc). Keyset pagination loads more
via the returned cursor through useInfiniteQuery.
- Detail panel: view or download the original, edit metadata (rename,
recategorise, set the document date), optionally run extraction, then the
existing review-then-confirm flow. When no scan provider is configured,
extraction surfaces a calm inline note instead of a hard error; the stored
document is untouched. Discard stays.
- Add a parameterised list key to the query-key factory so each filter/sort
combination keeps its own cache bucket while staying under the documents
prefix for invalidation.
- Rename the surface to "Documents" across all six locales (title, subtitle,
module label/description) and add the new toolbar, edit, extract, and
date-group strings. Route, model, and module key stay internal.
Add component and unit coverage for the grouped list, the detail/review
surface, the metadata edit form, the provider-unsupported note, and the
search-param/grouping/error-classification helpers.
Add the opt-in inboundDocuments module (off by default, like the MCP
endpoint): ingesting a clinical document egresses it to the OCR/vision
provider, so the surface ships dark and the user turns it on from the
Modules hub. The born-gated /documents page carries the prominent
non-diagnostic disclaimer (we read, we don't interpret; nothing is saved
until you approve it; only your clinician can interpret these results),
uploads a document, and walks each extracted fact: source provenance and
confidence are shown, low-confidence facts are blocked from approval until
edited, and the confirm step commits the approved facts.
Marc-André Bombeck