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refactor(labs): shape one reading from one shared select
The labs block and a single-reading read now build a reading from the same select and the same shaping, so one reading fetched by its id renders exactly like the latest reading of a marker.
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Marc-André Bombeck committed
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commit
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-59
@@ -56,6 +56,7 @@
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* lookback limit (the whole record when there is none), or, for a named read,
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* when no marker matches the analyte.
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*/
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import type { Prisma } from "@/generated/prisma/client";
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import { sameLabUnit } from "@/lib/labs/unit-normalise";
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import {
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UNBOUNDED_REACH,
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@@ -229,6 +230,77 @@ export function shapeLabHistory(
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};
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}
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/** What a reading is shaped from; `noteEncrypted` is never selected. */
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const LAB_READING_SELECT = {
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id: true,
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analyte: true,
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panel: true,
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value: true,
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valueText: true,
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unit: true,
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referenceLow: true,
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referenceHigh: true,
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sourceReferenceLow: true,
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sourceReferenceHigh: true,
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sourceReferenceText: true,
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sourceUnit: true,
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takenAt: true,
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biomarkerId: true,
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biomarker: {
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select: {
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id: true,
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name: true,
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unit: true,
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lowerBound: true,
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upperBound: true,
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panel: true,
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},
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},
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} as const satisfies Prisma.LabResultSelect;
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type LabReadingRow = Prisma.LabResultGetPayload<{
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select: typeof LAB_READING_SELECT;
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}>;
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/** One stored row as a reading, without its id. */
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function labReading(
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row: LabReadingRow,
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resolved: ReturnType<typeof resolveLabFields>,
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): CoachLabReading {
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return {
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// v1.30.25 — analyte / panel / unit are NOT server-authored. A lab row
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// committed from an uploaded document carries the name a model
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// transcribed out of that PDF (`resolveOrMintBiomarker` stores it
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// verbatim as `Biomarker.name`), so a hostile document chooses this
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// string. It reaches BOTH the snapshot prompt and the `labs_read`
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// tool result, so it is sanitised HERE at the shared source rather
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// than at either consumer. `sanitizeForPrompt` strips control chars
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// and the instruction-shaped patterns; the fence around the block
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// carries the data/instruction contract.
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analyte: sanitizeForPrompt(resolved.analyte, MAX_ANALYTE_CHARS),
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panel: resolved.panel
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? sanitizeForPrompt(resolved.panel, MAX_ANALYTE_CHARS)
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: null,
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value: row.value,
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valueText: row.valueText ? sanitizeValueText(row.valueText) : null,
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// A value without a unit is stored as "1"; the model is shown none,
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// so it never writes "3.6 1".
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unit: sanitizeForPrompt(labUnitText(resolved.unit), MAX_UNIT_CHARS),
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referenceLow: resolved.referenceLow,
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referenceHigh: resolved.referenceHigh,
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// A qualitative row has nothing to compare against the bounds →
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// neutral "unknown", never a fabricated verdict. A numeric row
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// classifies against the window in force for it — the report's own
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// range when it carries one, the catalog band otherwise. Same rule as
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// every other lab surface.
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rangeStatus: classifyAgainstEffectiveRange(
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row.value,
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resolved.effectiveRange,
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),
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takenAt: row.takenAt.toISOString(),
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};
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}
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/**
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* Build the labs context block, or `null` when the account has no readings in
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* the lookback window. Selects label + value + resolved bounds + dates only —
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@@ -283,32 +355,7 @@ export async function buildLabsSnapshotBlock(
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},
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orderBy: { takenAt: "desc" },
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take: MAX_ROWS,
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select: {
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id: true,
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analyte: true,
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panel: true,
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value: true,
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valueText: true,
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unit: true,
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referenceLow: true,
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referenceHigh: true,
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sourceReferenceLow: true,
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sourceReferenceHigh: true,
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sourceReferenceText: true,
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sourceUnit: true,
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takenAt: true,
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biomarkerId: true,
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biomarker: {
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select: {
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id: true,
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name: true,
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unit: true,
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lowerBound: true,
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upperBound: true,
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panel: true,
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},
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},
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},
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select: LAB_READING_SELECT,
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});
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if (rows.length === 0) return null;
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@@ -358,39 +405,7 @@ export async function buildLabsSnapshotBlock(
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unit: resolved.unit,
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takenAt: row.takenAt,
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earlier: [],
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reading: {
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// v1.30.25 — analyte / panel / unit are NOT server-authored. A lab row
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// committed from an uploaded document carries the name a model
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// transcribed out of that PDF (`resolveOrMintBiomarker` stores it
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// verbatim as `Biomarker.name`), so a hostile document chooses this
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// string. It reaches BOTH the snapshot prompt and the `labs_read`
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// tool result, so it is sanitised HERE at the shared source rather
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// than at either consumer. `sanitizeForPrompt` strips control chars
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// and the instruction-shaped patterns; the fence around the block
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// carries the data/instruction contract.
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analyte: sanitizeForPrompt(resolved.analyte, MAX_ANALYTE_CHARS),
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panel: resolved.panel
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? sanitizeForPrompt(resolved.panel, MAX_ANALYTE_CHARS)
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: null,
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value: row.value,
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valueText: row.valueText ? sanitizeValueText(row.valueText) : null,
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// A value without a unit is stored as "1"; the model is shown none,
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// so it never writes "3.6 1".
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unit: sanitizeForPrompt(labUnitText(resolved.unit), MAX_UNIT_CHARS),
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referenceLow: resolved.referenceLow,
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referenceHigh: resolved.referenceHigh,
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// A qualitative row has nothing to compare against the bounds →
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// neutral "unknown", never a fabricated verdict. A numeric row
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// classifies against the window in force for it — the report's own
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// range when it carries one, the catalog band otherwise. Same rule as
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// every other lab surface.
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rangeStatus: classifyAgainstEffectiveRange(
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row.value,
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resolved.effectiveRange,
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),
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takenAt: row.takenAt.toISOString(),
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...id,
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},
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reading: { ...labReading(row, resolved), ...id },
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});
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}
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@@ -410,3 +425,20 @@ export async function buildLabsSnapshotBlock(
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return { recent };
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}
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/**
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* One reading by its lab result id, shaped exactly like a block entry, or
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* `null` when it is not this account's, is deleted, or the labs module is off.
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*/
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export async function readLabReading(
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userId: string,
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labResultId: string,
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): Promise<CoachLabReading | null> {
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if (!(await isModuleEnabled(userId, "labs"))) return null;
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const row = await prisma.labResult.findFirst({
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where: { id: labResultId, userId, deletedAt: null },
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select: LAB_READING_SELECT,
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});
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if (!row) return null;
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return labReading(row, resolveLabFields(row, row.biomarker));
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}
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