mirror of
https://github.com/temetro/temetro.git
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31d86bb5dd
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>
248 lines
7.7 KiB
TypeScript
248 lines
7.7 KiB
TypeScript
"use client";
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import { useChat } from "@ai-sdk/react";
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import { DefaultChatTransport } from "ai";
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import { nanoid } from "nanoid";
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import { useSearchParams } from "next/navigation";
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import { useCallback, useEffect, useMemo, useRef, useState } from "react";
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import { useTranslation } from "react-i18next";
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import {
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Conversation,
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ConversationContent,
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ConversationScrollButton,
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} from "@/components/ai-elements/conversation";
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import {
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Message,
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MessageContent,
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MessageResponse,
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} from "@/components/ai-elements/message";
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import { ChatInput } from "@/components/chat/chat-input";
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import { ImportPreviewCard } from "@/components/chat/import-preview-card";
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import { LabChartCard } from "@/components/chat/lab-chart-card";
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import { PatientResult } from "@/components/chat/patient-cards";
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import { Button } from "@/components/ui/button";
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import {
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Dialog,
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DialogDescription,
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DialogFooter,
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DialogHeader,
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DialogPanel,
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DialogPopup,
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DialogTitle,
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} from "@/components/ui/dialog";
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import {
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DEFAULT_EFFORT,
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DEFAULT_MODEL_ID,
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type Effort,
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getModel,
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} from "@/lib/ai-models";
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import type { TemetroUIMessage } from "@/lib/ai-chat";
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import { API_BASE_URL } from "@/lib/api-client";
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import { getPatient } from "@/lib/patients";
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// Trigger: `/patient 10293` or just `/10293` — a client-side fast-path that
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// pulls records instantly without the LLM (also works offline).
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const PATIENT_COMMAND = /^\/(?:patient\s+)?(\d+)$/i;
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export function ChatPanel() {
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const { t } = useTranslation();
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const [model, setModel] = useState<string>(DEFAULT_MODEL_ID);
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const [effort, setEffort] = useState<Effort>(DEFAULT_EFFORT);
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// Veil consent: cloud models de-identify + send data externally. We ask once
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// per session before the first such send.
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const [consented, setConsented] = useState(false);
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const [consentOpen, setConsentOpen] = useState(false);
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const pendingSend = useRef<string | null>(null);
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const transport = useMemo(
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() =>
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new DefaultChatTransport<TemetroUIMessage>({
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api: `${API_BASE_URL}/api/chat`,
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credentials: "include",
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}),
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[],
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);
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const { messages, setMessages, sendMessage, status, stop } =
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useChat<TemetroUIMessage>({ transport });
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const isCloudModel = (getModel(model)?.provider ?? "ollama") !== "ollama";
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// Run the LLM agent for a message (after any consent gate).
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const runAgent = useCallback(
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(text: string) => {
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sendMessage({ text }, { body: { model, effort } });
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},
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[sendMessage, model, effort],
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);
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const send = useCallback(
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async (text: string) => {
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const trimmed = text.trim();
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if (!trimmed) return;
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// Fast-path: `/patient <file#>` renders cards directly, no LLM.
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const match = trimmed.match(PATIENT_COMMAND);
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if (match) {
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const fileNumber = match[1];
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const userId = nanoid();
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setMessages((prev) => [
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...prev,
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{ id: userId, role: "user", parts: [{ type: "text", text: trimmed }] },
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]);
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let patient = null;
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try {
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patient = await getPatient(fileNumber);
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} catch {
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patient = null;
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}
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setMessages((prev) => [
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...prev,
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{
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id: nanoid(),
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role: "assistant",
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parts: patient
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? [{ type: "data-patientCard", data: patient }]
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: [
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{
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type: "text",
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text: t("chat.patientNotFound", { fileNumber }),
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},
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],
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},
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]);
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return;
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}
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// Cloud model → ask for Veil consent once before sending externally.
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if (isCloudModel && !consented) {
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pendingSend.current = trimmed;
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setConsentOpen(true);
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return;
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}
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runAgent(trimmed);
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},
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[consented, isCloudModel, runAgent, setMessages, t],
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);
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const confirmConsent = useCallback(() => {
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setConsented(true);
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setConsentOpen(false);
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const text = pendingSend.current;
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pendingSend.current = null;
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if (text) runAgent(text);
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}, [runAgent]);
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// Opening a patient from the Patients page lands here as `/?patient=<file#>`.
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const searchParams = useSearchParams();
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const requestedPatient = searchParams.get("patient");
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const handledPatientRef = useRef<string | null>(null);
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useEffect(() => {
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if (requestedPatient && handledPatientRef.current !== requestedPatient) {
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handledPatientRef.current = requestedPatient;
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send(`/patient ${requestedPatient}`);
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}
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}, [requestedPatient, send]);
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const promptInput = (
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<ChatInput
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effort={effort}
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model={model}
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onEffortChange={setEffort}
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onModelChange={setModel}
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onStop={stop}
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onSubmit={send}
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status={status}
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/>
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);
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const consentDialog = (
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<Dialog onOpenChange={setConsentOpen} open={consentOpen}>
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<DialogPopup>
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<DialogHeader>
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<DialogTitle>{t("chat.consent.title")}</DialogTitle>
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<DialogDescription>
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{t("chat.consent.body", {
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provider: getModel(model)?.label ?? model,
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})}
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</DialogDescription>
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</DialogHeader>
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<DialogPanel>
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<p className="text-sm text-muted-foreground">
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{t("chat.consent.veilNote")}
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</p>
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</DialogPanel>
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<DialogFooter>
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<Button onClick={() => setConsentOpen(false)} variant="outline">
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{t("chat.consent.cancel")}
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</Button>
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<Button onClick={confirmConsent}>{t("chat.consent.confirm")}</Button>
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</DialogFooter>
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</DialogPopup>
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</Dialog>
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);
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if (messages.length === 0) {
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return (
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<div className="flex flex-1 flex-col items-center justify-center px-4">
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<div className="flex w-full max-w-3xl flex-col items-center gap-10">
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<h1 className="text-center text-3xl font-semibold tracking-tight text-balance sm:text-4xl">
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{t("chat.heading")}
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</h1>
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{promptInput}
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</div>
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{consentDialog}
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</div>
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);
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}
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return (
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<div className="flex flex-1 flex-col overflow-hidden">
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<Conversation>
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<ConversationContent className="mx-auto w-full max-w-3xl">
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{messages.map((message) => (
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<Message from={message.role} key={message.id}>
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<MessageContent className="w-full">
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{message.parts.map((part, i) => {
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const key = `${message.id}-${i}`;
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if (part.type === "text") {
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return message.role === "user" ? (
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<span className="whitespace-pre-wrap" key={key}>
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{part.text}
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</span>
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) : (
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<MessageResponse key={key}>{part.text}</MessageResponse>
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);
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}
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if (part.type === "data-patientCard") {
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return (
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<PatientResult
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fileNumber={part.data.fileNumber}
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key={key}
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patient={part.data}
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status="ready"
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/>
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);
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}
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if (part.type === "data-labCard") {
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return <LabChartCard data={part.data} key={key} />;
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}
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if (part.type === "data-importPreview") {
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return <ImportPreviewCard data={part.data} key={key} />;
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}
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return null;
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})}
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</MessageContent>
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</Message>
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))}
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</ConversationContent>
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<ConversationScrollButton />
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</Conversation>
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<div className="mx-auto w-full max-w-3xl px-4 pb-4">{promptInput}</div>
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{consentDialog}
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</div>
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);
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}
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