frontend: wire chat to the real agent + lab charts + import approval

Replace the mock chat with the live backend agent:
- chat-panel uses @ai-sdk/react useChat against /api/chat (credentials included),
  passing the selected model + effort per send. The `/patient <file#>` fast-path
  is kept as an instant client-side shortcut.
- Renders the agent's streamed data parts: patientCard → record cards
  (PatientResult), labCard → new LabChartCard (visx area chart with a high/low
  flag badge in the top-right corner + recent values), importPreview →
  ImportPreviewCard (the human approval gate: review counts/issues, then commit
  via POST /api/ai/import — nothing is written until approved).
- Veil consent: a one-time dialog before the first send to a cloud model,
  explaining that identifiers are de-identified before leaving the clinic.
- Attached text files (csv/json/txt…) now include their content in the message
  so the agent can parse an export for import.

Shared chat message/data-part types in lib/ai-chat.ts.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

frontend/components/chat/chat-input.tsx

@@ -55,7 +55,7 @@ export function ChatInput({
   const canSend =
     (value.trim().length > 0 || files.length > 0) && !isGenerating;
 
-  const submit = useCallback(() => {
+  const submit = useCallback(async () => {
     const trimmed = value.trim();
     if ((!trimmed && files.length === 0) || isGenerating) {
       return;
@@ -64,8 +64,24 @@ export function ChatInput({
     if (trimmed) {
       parts.push(trimmed);
     }
-    if (files.length > 0) {
+    // Include the text of attached files so the agent can parse them (e.g. a
-      parts.push(`[Attached: ${files.map((file) => file.name).join(", ")}]`);
+    // database export to import). Read text-like files; cap each so a huge file
+    // can't blow the context. Binary files are referenced by name only.
+    for (const file of files) {
+      const textLike =
+        /\.(csv|tsv|json|txt|md|xml|ndjson|tab)$/i.test(file.name) ||
+        file.type.startsWith("text/") ||
+        file.type === "application/json";
+      if (textLike) {
+        try {
+          const content = (await file.text()).slice(0, 200_000);
+          parts.push(`--- File: ${file.name} ---\n${content}`);
+        } catch {
+          parts.push(`[Attached: ${file.name}]`);
+        }
+      } else {
+        parts.push(`[Attached: ${file.name}]`);
+      }
     }
     onSubmit(parts.join("\n\n"));
     setValue("");

frontend/components/chat/chat-panel.tsx

@@ -1,9 +1,10 @@
 "use client";
 
+import { useChat } from "@ai-sdk/react";
+import { DefaultChatTransport } from "ai";
 import { nanoid } from "nanoid";
-import type { ChatStatus } from "ai";
 import { useSearchParams } from "next/navigation";
-import { useCallback, useEffect, useRef, useState } from "react";
+import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { useTranslation } from "react-i18next";
 
 import {
@@ -17,110 +18,124 @@ import {
   MessageResponse,
 } from "@/components/ai-elements/message";
 import { ChatInput } from "@/components/chat/chat-input";
+import { ImportPreviewCard } from "@/components/chat/import-preview-card";
+import { LabChartCard } from "@/components/chat/lab-chart-card";
 import { PatientResult } from "@/components/chat/patient-cards";
-import { DEFAULT_EFFORT, DEFAULT_MODEL_ID, type Effort } from "@/lib/ai-models";
+import { Button } from "@/components/ui/button";
-import { getPatient, type Patient } from "@/lib/patients";
+import {
+  Dialog,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogPanel,
+  DialogPopup,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import {
+  DEFAULT_EFFORT,
+  DEFAULT_MODEL_ID,
+  type Effort,
+  getModel,
+} from "@/lib/ai-models";
+import type { TemetroUIMessage } from "@/lib/ai-chat";
+import { API_BASE_URL } from "@/lib/api-client";
+import { getPatient } from "@/lib/patients";
 
-type ChatMessage =
+// Trigger: `/patient 10293` or just `/10293` — a client-side fast-path that
-  | { id: string; role: "user"; text: string }
+// pulls records instantly without the LLM (also works offline).
-  | { id: string; role: "assistant"; kind: "text"; text: string }
-  | {
-      id: string;
-      role: "assistant";
-      kind: "patient";
-      fileNumber: string;
-      status: "loading" | "ready" | "not-found";
-      patient?: Patient;
-    };
-
-// Trigger: `/patient 10293` or just `/10293` pulls up records.
 const PATIENT_COMMAND = /^\/(?:patient\s+)?(\d+)$/i;
 
 export function ChatPanel() {
   const { t } = useTranslation();
-  const [messages, setMessages] = useState<ChatMessage[]>([]);
-  const [status, setStatus] = useState<ChatStatus>("ready");
-  // Model + effort selected in the input; travels with each send (wired to the
-  // backend agent in a later phase). Defaults come from the shared catalog.
   const [model, setModel] = useState<string>(DEFAULT_MODEL_ID);
   const [effort, setEffort] = useState<Effort>(DEFAULT_EFFORT);
 
-  const send = useCallback(async (text: string) => {
+  // Veil consent: cloud models de-identify + send data externally. We ask once
-    const trimmed = text.trim();
+  // per session before the first such send.
-    if (!trimmed) {
+  const [consented, setConsented] = useState(false);
-      return;
+  const [consentOpen, setConsentOpen] = useState(false);
-    }
+  const pendingSend = useRef<string | null>(null);
 
-    setMessages((prev) => [
+  const transport = useMemo(
-      ...prev,
+    () =>
-      { id: nanoid(), role: "user", text: trimmed },
+      new DefaultChatTransport<TemetroUIMessage>({
-    ]);
+        api: `${API_BASE_URL}/api/chat`,
+        credentials: "include",
+      }),
+    [],
+  );
 
-    const match = trimmed.match(PATIENT_COMMAND);
+  const { messages, setMessages, sendMessage, status, stop } =
+    useChat<TemetroUIMessage>({ transport });
 
-    // Patient lookup: append a loading card set, then fill it in once the
+  const isCloudModel = (getModel(model)?.provider ?? "ollama") !== "ollama";
-    // (mock) record comes back.
-    if (match) {
-      const fileNumber = match[1];
-      const resultId = nanoid();
-      setStatus("submitted");
-      setMessages((prev) => [
-        ...prev,
-        {
-          id: resultId,
-          role: "assistant",
-          kind: "patient",
-          fileNumber,
-          status: "loading",
-        },
-      ]);
 
-      let patient: Patient | null = null;
+  // Run the LLM agent for a message (after any consent gate).
-      try {
+  const runAgent = useCallback(
-        patient = await getPatient(fileNumber);
+    (text: string) => {
-      } catch {
+      sendMessage({ text }, { body: { model, effort } });
-        // Network / auth errors fall through as "not found"; a 401 will have
+    },
-        // already redirected to /login via the API client.
+    [sendMessage, model, effort],
-        patient = null;
+  );
+
+  const send = useCallback(
+    async (text: string) => {
+      const trimmed = text.trim();
+      if (!trimmed) return;
+
+      // Fast-path: `/patient <file#>` renders cards directly, no LLM.
+      const match = trimmed.match(PATIENT_COMMAND);
+      if (match) {
+        const fileNumber = match[1];
+        const userId = nanoid();
+        setMessages((prev) => [
+          ...prev,
+          { id: userId, role: "user", parts: [{ type: "text", text: trimmed }] },
+        ]);
+        let patient = null;
+        try {
+          patient = await getPatient(fileNumber);
+        } catch {
+          patient = null;
+        }
+        setMessages((prev) => [
+          ...prev,
+          {
+            id: nanoid(),
+            role: "assistant",
+            parts: patient
+              ? [{ type: "data-patientCard", data: patient }]
+              : [
+                  {
+                    type: "text",
+                    text: t("chat.patientNotFound", { fileNumber }),
+                  },
+                ],
+          },
+        ]);
+        return;
       }
-      setMessages((prev) =>
-        prev.map((message) =>
-          message.id === resultId &&
-          message.role === "assistant" &&
-          message.kind === "patient"
-            ? {
-                ...message,
-                status: patient ? "ready" : "not-found",
-                patient: patient ?? undefined,
-              }
-            : message
-        )
-      );
-      setStatus("ready");
-      return;
-    }
 
-    // UI-only: mock assistant reply for anything that isn't a command.
+      // Cloud model → ask for Veil consent once before sending externally.
-    setStatus("submitted");
+      if (isCloudModel && !consented) {
-    window.setTimeout(() => {
+        pendingSend.current = trimmed;
-      setStatus("streaming");
+        setConsentOpen(true);
-      setMessages((prev) => [
+        return;
-        ...prev,
+      }
-        {
+      runAgent(trimmed);
-          id: nanoid(),
+    },
-          role: "assistant",
+    [consented, isCloudModel, runAgent, setMessages, t],
-          kind: "text",
+  );
-          text: `This is a **UI-only preview** of temetro. Try \`/patient 10293\` to pull up a patient's records.\n\nYou asked:\n\n> ${trimmed}`,
-        },
-      ]);
-      window.setTimeout(() => setStatus("ready"), 250);
-    }, 500);
-  }, []);
 
-  const handleStop = useCallback(() => setStatus("ready"), []);
+  const confirmConsent = useCallback(() => {
+    setConsented(true);
+    setConsentOpen(false);
+    const text = pendingSend.current;
+    pendingSend.current = null;
+    if (text) runAgent(text);
+  }, [runAgent]);
 
-  // Opening a patient from the Patients page lands here as `/?patient=<file#>`;
+  // Opening a patient from the Patients page lands here as `/?patient=<file#>`.
-  // run the lookup once on arrival.
   const searchParams = useSearchParams();
   const requestedPatient = searchParams.get("patient");
   const handledPatientRef = useRef<string | null>(null);
@@ -137,12 +152,38 @@ export function ChatPanel() {
       model={model}
       onEffortChange={setEffort}
       onModelChange={setModel}
-      onStop={handleStop}
+      onStop={stop}
       onSubmit={send}
       status={status}
     />
   );
 
+  const consentDialog = (
+    <Dialog onOpenChange={setConsentOpen} open={consentOpen}>
+      <DialogPopup>
+        <DialogHeader>
+          <DialogTitle>{t("chat.consent.title")}</DialogTitle>
+          <DialogDescription>
+            {t("chat.consent.body", {
+              provider: getModel(model)?.label ?? model,
+            })}
+          </DialogDescription>
+        </DialogHeader>
+        <DialogPanel>
+          <p className="text-sm text-muted-foreground">
+            {t("chat.consent.veilNote")}
+          </p>
+        </DialogPanel>
+        <DialogFooter>
+          <Button onClick={() => setConsentOpen(false)} variant="outline">
+            {t("chat.consent.cancel")}
+          </Button>
+          <Button onClick={confirmConsent}>{t("chat.consent.confirm")}</Button>
+        </DialogFooter>
+      </DialogPopup>
+    </Dialog>
+  );
+
   if (messages.length === 0) {
     return (
       <div className="flex flex-1 flex-col items-center justify-center px-4">
@@ -152,6 +193,7 @@ export function ChatPanel() {
           </h1>
           {promptInput}
         </div>
+        {consentDialog}
       </div>
     );
   }
@@ -160,48 +202,46 @@ export function ChatPanel() {
     <div className="flex flex-1 flex-col overflow-hidden">
       <Conversation>
         <ConversationContent className="mx-auto w-full max-w-3xl">
-          {messages.map((message) => {
+          {messages.map((message) => (
-            if (message.role === "assistant" && message.kind === "patient") {
+            <Message from={message.role} key={message.id}>
-              return (
+              <MessageContent className="w-full">
-                <Message from="assistant" key={message.id}>
+                {message.parts.map((part, i) => {
-                  <MessageContent className="w-full">
+                  const key = `${message.id}-${i}`;
-                    <PatientResult
+                  if (part.type === "text") {
-                      fileNumber={message.fileNumber}
+                    return message.role === "user" ? (
-                      onPatientUpdated={(updated) =>
+                      <span className="whitespace-pre-wrap" key={key}>
-                        setMessages((prev) =>
+                        {part.text}
-                          prev.map((m) =>
+                      </span>
-                            m.id === message.id &&
+                    ) : (
-                            m.role === "assistant" &&
+                      <MessageResponse key={key}>{part.text}</MessageResponse>
-                            m.kind === "patient"
+                    );
-                              ? { ...m, patient: updated, status: "ready" }
+                  }
-                              : m
+                  if (part.type === "data-patientCard") {
-                          )
+                    return (
-                        )
+                      <PatientResult
-                      }
+                        fileNumber={part.data.fileNumber}
-                      patient={message.patient}
+                        key={key}
-                      status={message.status}
+                        patient={part.data}
-                    />
+                        status="ready"
-                  </MessageContent>
+                      />
-                </Message>
+                    );
-              );
+                  }
-            }
+                  if (part.type === "data-labCard") {
-
+                    return <LabChartCard data={part.data} key={key} />;
-            return (
+                  }
-              <Message from={message.role} key={message.id}>
+                  if (part.type === "data-importPreview") {
-                <MessageContent>
+                    return <ImportPreviewCard data={part.data} key={key} />;
-                  {message.role === "user" ? (
+                  }
-                    <span className="whitespace-pre-wrap">{message.text}</span>
+                  return null;
-                  ) : (
+                })}
-                    <MessageResponse>{message.text}</MessageResponse>
+              </MessageContent>
-                  )}
+            </Message>
-                </MessageContent>
+          ))}
-              </Message>
-            );
-          })}
         </ConversationContent>
         <ConversationScrollButton />
       </Conversation>
       <div className="mx-auto w-full max-w-3xl px-4 pb-4">{promptInput}</div>
+      {consentDialog}
     </div>
   );
 }

frontend/components/chat/import-preview-card.tsx

@@ -0,0 +1,116 @@
+"use client";
+
+import { AlertTriangle, Check, Database, X } from "lucide-react";
+import { useState } from "react";
+import { useTranslation } from "react-i18next";
+
+import { Button } from "@/components/ui/button";
+import { Card } from "@/components/ui/card";
+import type { ImportPreviewData } from "@/lib/ai-chat";
+import { commitImport } from "@/lib/ai-settings";
+import { notify } from "@/lib/toast";
+
+type Status = "pending" | "committing" | "done" | "rejected";
+
+// The human approval gate for the migration import. The agent proposes records
+// (dry run, nothing written); the clinician reviews counts + issues here and
+// must approve before anything is inserted via POST /api/ai/import.
+export function ImportPreviewCard({ data }: { data: ImportPreviewData }) {
+  const { t } = useTranslation();
+  const [status, setStatus] = useState<Status>("pending");
+  const [result, setResult] = useState<{ created: number; failed: number } | null>(
+    null,
+  );
+
+  const approve = async () => {
+    setStatus("committing");
+    try {
+      const res = await commitImport(data.valid);
+      setResult({ created: res.created.length, failed: res.failed.length });
+      setStatus("done");
+      notify.success(
+        t("chat.importCard.importedTitle"),
+        t("chat.importCard.importedBody", { count: res.created.length }),
+      );
+    } catch {
+      setStatus("pending");
+      notify.error(
+        t("chat.importCard.failedTitle"),
+        t("chat.importCard.failedBody"),
+      );
+    }
+  };
+
+  return (
+    <Card className="w-full gap-3 p-4">
+      <div className="flex items-center gap-2">
+        <Database className="size-4 text-muted-foreground" />
+        <span className="text-sm font-medium">{t("chat.importCard.title")}</span>
+      </div>
+
+      <div className="flex flex-wrap gap-4 text-sm">
+        <span>
+          {t("chat.importCard.ready")}{" "}
+          <strong className="tabular-nums">{data.valid.length}</strong>
+        </span>
+        {data.invalid.length > 0 ? (
+          <span className="flex items-center gap-1 text-warning-foreground">
+            <AlertTriangle className="size-3.5" />
+            {t("chat.importCard.skipped")}{" "}
+            <strong className="tabular-nums">{data.invalid.length}</strong>
+          </span>
+        ) : null}
+        <span className="text-muted-foreground">
+          {t("chat.importCard.total")}{" "}
+          <span className="tabular-nums">{data.total}</span>
+        </span>
+      </div>
+
+      {data.invalid.length > 0 ? (
+        <ul className="space-y-1 rounded-lg bg-muted/50 p-3 text-xs text-muted-foreground">
+          {data.invalid.slice(0, 5).map((issue) => (
+            <li key={issue.index}>
+              {t("chat.importCard.row", { index: issue.index + 1 })}:{" "}
+              {issue.errors.join("; ")}
+            </li>
+          ))}
+        </ul>
+      ) : null}
+
+      {status === "done" && result ? (
+        <p className="flex items-center gap-1.5 text-sm text-foreground">
+          <Check className="size-4" />
+          {t("chat.importCard.importedBody", { count: result.created })}
+          {result.failed > 0
+            ? ` · ${t("chat.importCard.failedCount", { count: result.failed })}`
+            : ""}
+        </p>
+      ) : status === "rejected" ? (
+        <p className="text-sm text-muted-foreground">
+          {t("chat.importCard.rejectedNote")}
+        </p>
+      ) : (
+        <div className="flex items-center gap-2">
+          <Button
+            disabled={status === "committing" || data.valid.length === 0}
+            onClick={approve}
+            size="sm"
+          >
+            {status === "committing"
+              ? t("chat.importCard.importing")
+              : t("chat.importCard.approve", { count: data.valid.length })}
+          </Button>
+          <Button
+            disabled={status === "committing"}
+            onClick={() => setStatus("rejected")}
+            size="sm"
+            variant="outline"
+          >
+            <X className="size-4" />
+            {t("chat.importCard.reject")}
+          </Button>
+        </div>
+      )}
+    </Card>
+  );
+}

frontend/components/chat/lab-chart-card.tsx

@@ -0,0 +1,123 @@
+"use client";
+
+import { ArrowDown, ArrowUp } from "lucide-react";
+import { useMemo } from "react";
+import { useTranslation } from "react-i18next";
+
+import { Area, AreaChart } from "@/components/charts/area-chart";
+import { Grid } from "@/components/charts/grid";
+import { ChartTooltip } from "@/components/charts/tooltip";
+import { XAxis } from "@/components/charts/x-axis";
+import { Badge } from "@/components/ui/badge";
+import { Card } from "@/components/ui/card";
+import type { LabCardData } from "@/lib/ai-chat";
+import type { LabFlag } from "@/lib/patients";
+import { cn } from "@/lib/utils";
+
+type BadgeVariant = "default" | "secondary" | "destructive" | "outline";
+
+const labFlagVariant: Record<LabFlag, BadgeVariant> = {
+  normal: "outline",
+  low: "secondary",
+  high: "secondary",
+  critical: "destructive",
+};
+
+// Plot the headline lab series. labTrend.points are most-recent-last numbers; we
+// synthesise evenly spaced dates ending today purely so the date x-axis spaces
+// the readings — the values are what matter.
+function toChartData(points: number[]): { date: Date; value: number }[] {
+  const today = new Date();
+  return points.map((value, i) => {
+    const date = new Date(today);
+    date.setDate(today.getDate() - (points.length - 1 - i));
+    return { date, value };
+  });
+}
+
+// The flag of the most recent reading of the headline lab, for the corner badge.
+function headlineFlag(data: LabCardData): LabFlag | null {
+  const matching = data.labs.filter((l) => l.name === data.labTrend.label);
+  const last = matching[matching.length - 1] ?? data.labs[data.labs.length - 1];
+  return last?.flag ?? null;
+}
+
+export function LabChartCard({ data }: { data: LabCardData }) {
+  const { t } = useTranslation();
+  const chartData = useMemo(
+    () => toChartData(data.labTrend.points),
+    [data.labTrend.points],
+  );
+  const flag = headlineFlag(data);
+  const latest = data.labTrend.points[data.labTrend.points.length - 1];
+
+  return (
+    <Card className="w-full gap-3 p-4">
+      <div className="flex items-start justify-between gap-2">
+        <div className="space-y-0.5">
+          <span className="text-sm font-medium text-foreground">
+            {data.name}
+          </span>
+          <p className="text-xs text-muted-foreground">
+            {data.labTrend.label} · {data.labTrend.unit}
+          </p>
+        </div>
+        {/* High/low indicator, top-right corner. */}
+        {flag && flag !== "normal" ? (
+          <Badge className="gap-1" variant={labFlagVariant[flag]}>
+            {flag === "low" ? (
+              <ArrowDown className="size-3" />
+            ) : (
+              <ArrowUp className="size-3" />
+            )}
+            {t(`chat.labCard.flags.${flag}`)}
+          </Badge>
+        ) : (
+          <span className="font-semibold text-foreground tabular-nums">
+            {latest}
+          </span>
+        )}
+      </div>
+
+      <AreaChart aspectRatio="2 / 1" data={chartData}>
+        <Grid horizontal />
+        <Area dataKey="value" fill="var(--chart-line-primary)" />
+        <XAxis tickMode="data" />
+        <ChartTooltip showDatePill={false} />
+      </AreaChart>
+
+      {data.labs.length > 0 ? (
+        <ul className="space-y-1.5">
+          {data.labs.slice(-6).map((lab, i) => (
+            <li
+              className="flex items-center justify-between gap-2 text-sm"
+              key={`${lab.name}-${i}`}
+            >
+              <span className="text-muted-foreground">{lab.name}</span>
+              <span className="flex items-center gap-2">
+                <span
+                  className={cn(
+                    "tabular-nums",
+                    lab.flag === "critical"
+                      ? "text-destructive-foreground"
+                      : "text-foreground",
+                  )}
+                >
+                  {lab.value}
+                </span>
+                {lab.flag !== "normal" ? (
+                  <Badge
+                    className="px-1.5 py-0 text-[11px]"
+                    variant={labFlagVariant[lab.flag]}
+                  >
+                    {t(`chat.labCard.flags.${lab.flag}`)}
+                  </Badge>
+                ) : null}
+              </span>
+            </li>
+          ))}
+        </ul>
+      ) : null}
+    </Card>
+  );
+}

frontend/lib/ai-chat.ts

@@ -0,0 +1,37 @@
+import type { UIMessage } from "ai";
+
+import type { Lab, Patient, Trend } from "@/lib/patients";
+
+// Custom data parts the backend agent streams alongside its text. They carry
+// REAL (un-redacted) record data straight to the clinician's screen for rich
+// rendering — the model itself only ever sees Veil-redacted tool results.
+
+export type LabCardData = {
+  fileNumber: string;
+  name: string;
+  labs: Lab[];
+  labTrend: Trend;
+};
+
+export type ImportPreviewData = {
+  // Validated, ready-to-commit records (server re-validates on commit).
+  valid: unknown[];
+  invalid: { index: number; errors: string[] }[];
+  total: number;
+};
+
+export type VeilNoticeData = {
+  provider: string;
+  level: string;
+};
+
+// Maps each data part name → its payload. Part `type` strings are the key
+// prefixed with `data-` (e.g. `data-patientCard`), per the AI SDK convention.
+export type TemetroDataParts = {
+  patientCard: Patient;
+  labCard: LabCardData;
+  importPreview: ImportPreviewData;
+  veilNotice: VeilNoticeData;
+};
+
+export type TemetroUIMessage = UIMessage<never, TemetroDataParts>;

frontend/lib/ai-settings.ts

@@ -50,3 +50,14 @@ export async function testAiConnection(input: {
     body: JSON.stringify(input),
   });
 }
+
+// Commit records the clinician approved in a chat import preview. The backend
+// re-validates and writes via the audited patient service.
+export async function commitImport(
+  records: unknown[],
+): Promise<{ created: string[]; failed: { fileNumber?: string; error: string }[] }> {
+  return apiFetch("/api/ai/import", {
+    method: "POST",
+    body: JSON.stringify({ records }),
+  });
+}

frontend/lib/i18n/locales/en/translation.json

@@ -640,6 +640,39 @@
         "gemini15Pro": "Google long-context model",
         "ollama": "Runs locally on your infrastructure"
       }
+    },
+    "patientNotFound": "I couldn't find a patient with file number {{fileNumber}}.",
+    "consent": {
+      "title": "Send to external AI provider?",
+      "body": "This message will be processed by {{provider}}, an external provider.",
+      "veilNote": "Veil de-identifies patient information (names, MRNs, providers) before it leaves your infrastructure, and restores it in the answer. Local Ollama models avoid this entirely.",
+      "cancel": "Cancel",
+      "confirm": "De-identify & send"
+    },
+    "labCard": {
+      "flags": {
+        "low": "Low",
+        "high": "High",
+        "critical": "Critical",
+        "normal": "Normal"
+      }
+    },
+    "importCard": {
+      "title": "Import patient records",
+      "ready": "Ready to import",
+      "skipped": "Skipped",
+      "total": "Parsed",
+      "row": "Row {{index}}",
+      "approve": "Import {{count}} record(s)",
+      "approve_one": "Import 1 record",
+      "reject": "Discard",
+      "importing": "Importing…",
+      "rejectedNote": "Import discarded. Nothing was written.",
+      "importedTitle": "Records imported",
+      "importedBody": "Imported {{count}} patient record(s).",
+      "failedCount": "{{count}} failed",
+      "failedTitle": "Import failed",
+      "failedBody": "The records could not be imported. Please try again."
     }
   },
   "patientCard": {

frontend/package-lock.json

@@ -8,6 +8,7 @@
       "name": "frontend",
       "version": "0.1.0",
       "dependencies": {
+        "@ai-sdk/react": "^3.0.206",
         "@base-ui/react": "^1.5.0",
         "@number-flow/react": "^0.6.0",
         "@radix-ui/react-use-controllable-state": "^1.2.2",
@@ -73,13 +74,13 @@
       }
     },
     "node_modules/@ai-sdk/gateway": {
-      "version": "3.0.121",
+      "version": "3.0.130",
-      "resolved": "https://registry.npmjs.org/@ai-sdk/gateway/-/gateway-3.0.121.tgz",
+      "resolved": "https://registry.npmjs.org/@ai-sdk/gateway/-/gateway-3.0.130.tgz",
-      "integrity": "sha512-uY248djJRxa5W68MHiyqO8WLdOeKQoRClGg7PVX/VPhVW8SJNM7/l5DcrA5WAM3YfQrLyNkgZa2VOu8T0t8LUw==",
+      "integrity": "sha512-qenRdpoYM+2y8Ibj3Y7XngvfcG4NIpejaM+YqAKWXi3/N1qZYeIelrm19jxhIwQW0W/g7WUz0L2Agl7+FnwrQA==",
       "license": "Apache-2.0",
       "dependencies": {
         "@ai-sdk/provider": "3.0.10",
-        "@ai-sdk/provider-utils": "4.0.27",
+        "@ai-sdk/provider-utils": "4.0.29",
         "@vercel/oidc": "3.2.0"
       },
       "engines": {
@@ -102,9 +103,9 @@
       }
     },
     "node_modules/@ai-sdk/provider-utils": {
-      "version": "4.0.27",
+      "version": "4.0.29",
-      "resolved": "https://registry.npmjs.org/@ai-sdk/provider-utils/-/provider-utils-4.0.27.tgz",
+      "resolved": "https://registry.npmjs.org/@ai-sdk/provider-utils/-/provider-utils-4.0.29.tgz",
-      "integrity": "sha512-ubkAJ+xODouwtmN1tYlvTPphH1hPOBfZaEQe8U7skGvFAnIRs9PPpsq57bC2+Ky/MB4yzhd6YOsxTAx9sGpazw==",
+      "integrity": "sha512-uhukHaCBvqkwBHkT8C2PrnqKTCoLn3pdHXqtcR9I8ErH+flbzgW4o7VHSNIup9LRu+WBvZIZDQLsx6rwl2tiOA==",
       "license": "Apache-2.0",
       "dependencies": {
         "@ai-sdk/provider": "3.0.10",
@@ -118,6 +119,24 @@
         "zod": "^3.25.76 || ^4.1.8"
       }
     },
+    "node_modules/@ai-sdk/react": {
+      "version": "3.0.206",
+      "resolved": "https://registry.npmjs.org/@ai-sdk/react/-/react-3.0.206.tgz",
+      "integrity": "sha512-26gbPT876BZVXJlSNjqkCDOFiqfxAAhYn+a/ryV6ce5TWo6EfWQZeEiLrZOS6bxaOi7xxkB5uPZaZKFaIJndjQ==",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@ai-sdk/provider-utils": "4.0.29",
+        "ai": "6.0.204",
+        "swr": "^2.2.5",
+        "throttleit": "2.1.0"
+      },
+      "engines": {
+        "node": ">=18"
+      },
+      "peerDependencies": {
+        "react": "^18 || ~19.0.1 || ~19.1.2 || ^19.2.1"
+      }
+    },
     "node_modules/@alloc/quick-lru": {
       "version": "5.2.0",
       "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
@@ -5222,14 +5241,14 @@
       }
     },
     "node_modules/ai": {
-      "version": "6.0.193",
+      "version": "6.0.204",
-      "resolved": "https://registry.npmjs.org/ai/-/ai-6.0.193.tgz",
+      "resolved": "https://registry.npmjs.org/ai/-/ai-6.0.204.tgz",
-      "integrity": "sha512-VQOTOse8+X8kMtg61DNSXlYJzwOW4NjMLDJNk/qxClWsFe4oiyFJDHGGG1oezfGcFzuYuQe/8Z7r4kwiZWh2YQ==",
+      "integrity": "sha512-SudB8rUwaVhpWF8+qTJcxUptXPIdN9rWMknzTT3WbKa2QwiGRshyepFKNkDILWm882LgqlEyRZgKhNT14j0jpQ==",
       "license": "Apache-2.0",
       "dependencies": {
-        "@ai-sdk/gateway": "3.0.121",
+        "@ai-sdk/gateway": "3.0.130",
         "@ai-sdk/provider": "3.0.10",
-        "@ai-sdk/provider-utils": "4.0.27",
+        "@ai-sdk/provider-utils": "4.0.29",
         "@opentelemetry/api": "^1.9.0"
       },
       "engines": {
@@ -14605,6 +14624,19 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/swr": {
+      "version": "2.4.1",
+      "resolved": "https://registry.npmjs.org/swr/-/swr-2.4.1.tgz",
+      "integrity": "sha512-2CC6CiKQtEwaEeNiqWTAw9PGykW8SR5zZX8MZk6TeAvEAnVS7Visz8WzphqgtQ8v2xz/4Q5K+j+SeMaKXeeQIA==",
+      "license": "MIT",
+      "dependencies": {
+        "dequal": "^2.0.3",
+        "use-sync-external-store": "^1.6.0"
+      },
+      "peerDependencies": {
+        "react": "^16.11.0 || ^17.0.0 || ^18.0.0 || ^19.0.0"
+      }
+    },
     "node_modules/tagged-tag": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/tagged-tag/-/tagged-tag-1.0.0.tgz",
@@ -14648,6 +14680,18 @@
         "url": "https://opencollective.com/webpack"
       }
     },
+    "node_modules/throttleit": {
+      "version": "2.1.0",
+      "resolved": "https://registry.npmjs.org/throttleit/-/throttleit-2.1.0.tgz",
+      "integrity": "sha512-nt6AMGKW1p/70DF/hGBdJB57B8Tspmbp5gfJ8ilhLnt7kkr2ye7hzD6NVG8GGErk2HWF34igrL2CXmNIkzKqKw==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=18"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
     "node_modules/tiny-invariant": {
       "version": "1.3.3",
       "resolved": "https://registry.npmjs.org/tiny-invariant/-/tiny-invariant-1.3.3.tgz",

frontend/package.json

@@ -9,6 +9,7 @@
     "lint": "eslint"
   },
   "dependencies": {
+    "@ai-sdk/react": "^3.0.206",
     "@base-ui/react": "^1.5.0",
     "@number-flow/react": "^0.6.0",
     "@radix-ui/react-use-controllable-state": "^1.2.2",