feat(labs): PDF upload, text extraction, LLM draft pipeline

server/test/labs-upload.test.ts

@@ -0,0 +1,70 @@
+import { describe, expect, test } from "bun:test";
+import { mkdtempSync } from "node:fs";
+import { tmpdir } from "node:os";
+import { join } from "node:path";
+import { createApp } from "../src/app";
+import { openDb } from "../src/db";
+import { loadOrCreateKey } from "../src/lib/crypto";
+
+// Minimal one-page PDF with a text object — enough for unpdf to open and read.
+const TINY_PDF = `%PDF-1.4
+1 0 obj<</Type/Catalog/Pages 2 0 R>>endobj
+2 0 obj<</Type/Pages/Kids[3 0 R]/Count 1>>endobj
+3 0 obj<</Type/Page/Parent 2 0 R/MediaBox[0 0 612 792]/Contents 4 0 R/Resources<</Font<</F1 5 0 R>>>>>>endobj
+4 0 obj<</Length 60>>stream
+BT /F1 12 Tf 72 720 Td (Glucose 100 mg/dL 70-99 H) Tj ET
+endstream
+endobj
+5 0 obj<</Type/Font/Subtype/Type1/BaseFont/Helvetica>>endobj
+trailer<</Root 1 0 R>>`;
+
+async function authedApp(fetchImpl: typeof fetch) {
+  const dir = mkdtempSync(join(tmpdir(), "helios-"));
+  const app = createApp({ db: openDb(dir), key: loadOrCreateKey(dir), dataDir: dir, llmFetch: fetchImpl });
+  const j = (b: unknown) => ({ method: "POST", headers: { "content-type": "application/json" }, body: JSON.stringify(b) });
+  await app.request("/api/setup", j({ password: "hunter2hunter2" }));
+  const cookie = (await app.request("/api/login", j({ password: "hunter2hunter2" }))).headers.get("set-cookie")!;
+  return { app, cookie };
+}
+
+const llmOk = (async () => new Response(JSON.stringify({ choices: [{ message: { content: JSON.stringify({
+  collectedDate: "2026-01-15", labName: "Sample Diagnostics",
+  markers: [{ panel: null, name: "Glucose", value: "100", unit: "mg/dL", referenceRange: "70-99", flagged: true }],
+}) } }] }), { status: 200 })) as unknown as typeof fetch;
+
+describe("labs upload", () => {
+  test("PDF upload → pending draft with extracted markers", async () => {
+    const { app, cookie } = await authedApp(llmOk);
+    const fd = new FormData();
+    fd.append("file", new File([TINY_PDF], "results.pdf", { type: "application/pdf" }));
+    const up = await app.request("/api/labs/upload", { method: "POST", headers: { cookie }, body: fd });
+    expect(up.status).toBe(201);
+    const { id } = await up.json();
+
+    const list = await (await app.request("/api/labs/drafts", { headers: { cookie } })).json();
+    expect(list.drafts).toHaveLength(1);
+    expect(list.drafts[0].id).toBe(id);
+    expect(list.drafts[0].status).toBe("pending");
+    expect(list.drafts[0].markerCount).toBe(1);
+  });
+
+  test("non-PDF rejected", async () => {
+    const { app, cookie } = await authedApp(llmOk);
+    const fd = new FormData();
+    fd.append("file", new File(["hi"], "notes.txt", { type: "text/plain" }));
+    const up = await app.request("/api/labs/upload", { method: "POST", headers: { cookie }, body: fd });
+    expect(up.status).toBe(400);
+  });
+
+  test("LLM failure → draft stored with error, not a 500", async () => {
+    const llmDown = (async () => new Response("x", { status: 500 })) as unknown as typeof fetch;
+    const { app, cookie } = await authedApp(llmDown);
+    const fd = new FormData();
+    fd.append("file", new File([TINY_PDF], "r.pdf", { type: "application/pdf" }));
+    const up = await app.request("/api/labs/upload", { method: "POST", headers: { cookie }, body: fd });
+    expect(up.status).toBe(201);
+    const list = await (await app.request("/api/labs/drafts", { headers: { cookie } })).json();
+    expect(list.drafts[0].error).toMatch(/llm_error/);
+    expect(list.drafts[0].markerCount).toBe(0);
+  });
+});