A lab runs its own method on its own device, so the window a physician
evaluates a value against is the one printed next to it on that report,
not a catalog band averaged over every lab. Reading a report pulled the
value and dropped that range: the extraction asked for it, the commit
handed it to the biomarker resolver, and the resolver only uses it when
it mints a NEW marker. For every analyte the user already had — the
normal case after a first panel — the printed range was read and then
thrown away.
Add `sourceReferenceLow` / `sourceReferenceHigh` / `sourceReferenceText`
to `LabResult` and carry the range from the report to the reading. The
text is stored whether or not numbers can be read out of it, because
"bis 5,0" and "negativ" state a window too; a range that could not be
parsed is kept verbatim, never replaced with invented bounds.
`resolveEffectiveReferenceRange` is the one place the precedence lives:
the source window wins for that single reading, and the catalog stays
the net for readings without one. A printed string with no derivable
bound does not displace the catalog. Every surface that judges a
reading routes through it — the API verdict, the doctor report, the
insights blocks and per-marker assessment, the coach snapshot, the MCP
read and the FHIR `referenceRange` — so a value cannot read in range on
one surface and out on another.
The API keeps `referenceLow` / `referenceHigh` as the window in force,
so a client that reads only those two renders the right range and the
right verdict with no change of its own; the catalog band, the source
window, its origin and a divergence flag ride alongside for clients
that want to show both.
Read side: the chart draws the source window as a second, visually
distinct band with the reading it came from named beneath it, the
reading rows name the printed range and the catalog band where the two
disagree, and the doctor-report PDF prints the report's own string with
a footnote naming the saved range. Entry side: one optional field on
the lab form, folded away until asked for, and the printed range is
editable on the scan review screen.
The range parser covers the notations German and English reports
actually print — two-sided, one-sided, comma or dot decimals, thousands
separators, trailing units — reads units without ever converting them,
and refuses to guess on anything ambiguous.
Replace the CompletionParams { systemPrompt, userPrompt } string pair with a
structured { system, messages[] } request across all five AI clients. One
refactor unlocks three things: provider prompt-caching (Anthropic cache_control
on the stable system prefix, OpenAI/Codex automatic prefix cache, with
cachedInputTokens surfaced for observability), the tool-calling wire surface,
and clean multi-turn.
Each client maps the new shape to its own wire and degrades unsupported
features silently: the local OpenAI-compatible server never receives a tools
field (most reject unknown keys), and prompt-caching is best-effort everywhere.
CompletionResult gains toolCalls, finishReason and cachedInputTokens; the tool
types and per-provider mapping ship now, the tool-use loop does not.
Vision inputs fold into the user turn's content parts via singleUserTurn, with
each provider's pre-existing block ordering preserved. The corrective-retry
paths append to the last user message rather than a flat string. The Coach
keeps assembling one user turn so its snapshot-once and grounding behaviour is
unchanged. No wire schema visible to API consumers changed.
Behaviour is unchanged across every surface; the full suite stays green.
Add an opt-in in-browser OCR path so a user whose provider cannot read
images (ChatGPT-OAuth/Codex, a text-only model) can still scan a lab
report. The capability probe gains a `mode` field: `vision` when the
provider reads the image directly, `text` when local OCR is enabled and
any provider is configured, or null. The extract route grows a text
branch that accepts the in-browser-OCR'd text as JSON and structures it
through the existing schema + review/commit flow; the raw image never
reaches the server in text mode. New `labsLocalOcrEnabled` user column
(migration 0184, default off) gates it, with a dedicated PATCH endpoint.
Resolve a vision-capable provider, gate with consent + a 6/hour rate bucket +
a reserved per-day token budget, then transcribe an uploaded photo or PDF into
structured proposed rows. The raw upload stays in memory only and is never
persisted. The commit route writes only the rows a human confirmed, resolving
or minting a biomarker per row with source OCR and skipping commit-time
duplicates. The capability probe drives whether the UI shows the scan entry.
Extracted text is treated as untrusted; the review screen is the safety
boundary.
Marc-André Bombeck