feat: AI SMS reminder flow with two-message intro, smart reschedule with availability checks
- Reminder flow: send AI self-introduction as message 1 (Twilio REST API), intent response as message 2 (TwiML) so intro always arrives first - LangGraph reminder graph: classify yes/no/other from patient reply; 'no' now asks 'When would you like to reschedule?' directly - Reschedule flow: new asked_reschedule_datetime stage replaces multi-step ASAP/next-week flow - Date-only reply (e.g. '5/18'): ask for time separately, then confirm - Date+time reply (e.g. '5/18 at 10am'): go straight to confirmation - new asked_reschedule_time_for_date and asked_reschedule_confirm_datetime stages - Date/time parsing: regex handles M/D and am/pm formats first; falls back to Gemini for natural language - Day-level office hours check: if requested day is closed (e.g. Sunday), reply 'Our office is closed on [date]. Choose another day?' - Time-level office hours check: if requested time is outside working hours (e.g. 12pm during lunch), reply with actual hours (e.g. '9:00 am – 12:00 pm and 1:00 pm – 5:00 pm') - Slot availability check: verifies no conflicting appointment for same staff member - After appointment confirmed: patient thank-you reply triggers warm closing with upcoming appointment time - Schedule page: office hours summary bar above grid showing today's configured hours with link to settings Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Gitead
@@ -266,12 +266,39 @@ router.post("/webhook/sms", async (req: Request, res: Response): Promise<any> =>
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return res.send(twimlReply(text));
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};
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// ── Stage: reminder_initial → send reminder greeting ─────────────────
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// ── Stage: reminder_initial → two messages: 1) AI intro, 2) intent response ──
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if (stage === "reminder_initial") {
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const rawGreeting = chatTemplates.reminderGreeting ||
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`Hi! My name is Lisa, the dedicated AI assistant at {officeName}. I can confirm or reschedule your appointment and answer general questions 24/7. I will reply your message at any time you need.`;
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`Hi! My name is Lisa, the dedicated AI assistant at {officeName}. I can confirm or reschedule your appointment and answer general questions 24/7.`;
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const introText = applyOfficeName(rawGreeting, officeName);
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return reply(applyOfficeName(rawGreeting, officeName), "greeted");
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// Use Google AI (LangGraph) to read the patient's reply and classify yes/no
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const apptDatetime = await getAppointmentDatetime(patient.id);
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const { reply: intentReply, intent } = await runReminderGraph(
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Body, aiSettings.apiKey, language, apptDatetime,
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chatTemplates.rescheduleGreeting, chatTemplates.generalFallback
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);
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if (intentReply) {
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let nextStage: ConversationStage;
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if (intent === "no") nextStage = "asked_reschedule_datetime";
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else if (intent === "wants_appointment") nextStage = "asked_new_or_existing";
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else nextStage = "done";
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// Send message 1 (AI intro) via REST API — queued FIRST in Twilio so it arrives first
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const twilioSettings = await storage.getTwilioSettings(patient.userId);
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if (twilioSettings) {
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const client = twilio(twilioSettings.accountSid, twilioSettings.authToken);
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await client.messages.create({ body: introText, from: twilioSettings.phoneNumber, to: From });
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await saveOutbound(patient.id, introText);
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}
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// Send message 2 (yes/no response) via TwiML — queued SECOND
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return reply(intentReply, nextStage);
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}
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// No clear intent detected — send only the intro and wait for next reply
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return reply(introText, "greeted");
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}
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// ── Stage: greeted → classify yes/no for appointment reminder ────────
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@@ -283,7 +310,7 @@ router.post("/webhook/sms", async (req: Request, res: Response): Promise<any> =>
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);
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if (aiReply) {
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let nextStage: ConversationStage;
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if (intent === "no") nextStage = "asked_reschedule_confirm";
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if (intent === "no") nextStage = "asked_reschedule_datetime";
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else if (intent === "wants_appointment") nextStage = "asked_new_or_existing";
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else nextStage = "done";
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return reply(aiReply, nextStage);
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@@ -292,9 +319,10 @@ router.post("/webhook/sms", async (req: Request, res: Response): Promise<any> =>
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// ── Rescheduling flow stages ───────────────────────────────────────────
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const rescheduleStages: ConversationStage[] = [
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"asked_reschedule_confirm", "asked_reschedule_preference",
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"asked_reschedule_asap", "asked_reschedule_next_week",
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"asked_reschedule_time",
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"asked_reschedule_confirm", "asked_reschedule_preference",
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"asked_reschedule_asap", "asked_reschedule_next_week",
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"asked_reschedule_time", "asked_reschedule_datetime",
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"asked_reschedule_time_for_date", "asked_reschedule_confirm_datetime",
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];
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if (rescheduleStages.includes(stage)) {
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const { reply: aiReply, nextStage } = await runRescheduleStep(
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@@ -412,6 +440,56 @@ router.post("/webhook/sms", async (req: Request, res: Response): Promise<any> =>
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return reply(aiReply, nextStage);
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}
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// ── Stage: done → closing thank-you reply ────────────────────────────
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// When the patient sends a thank-you / acknowledgement after the conversation
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// is complete, reply warmly with their upcoming appointment time.
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if (stage === "done") {
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const isThanks = /\b(thank|thanks|thank you|ty|ok|okay|great|perfect|sounds good|got it|understood|alright|appreciate|wonderful|excellent|awesome|cool|nice|good)\b/i.test(Body);
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if (isThanks) {
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const apptDatetime = await getAppointmentDatetime(patient.id);
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const CLOSING: Record<string, string> = {
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English: apptDatetime
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? `Thank you for choosing our office! We look forward to seeing you on ${apptDatetime}.`
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: `Thank you for choosing our office! We look forward to seeing you soon.`,
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Spanish: apptDatetime
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? `¡Gracias por elegirnos! Le esperamos el ${apptDatetime}.`
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: `¡Gracias por elegirnos! Le esperamos pronto.`,
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Portuguese: apptDatetime
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? `Obrigado por nos escolher! Aguardamos sua visita em ${apptDatetime}.`
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: `Obrigado por nos escolher! Aguardamos sua visita em breve.`,
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Mandarin: apptDatetime
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? `感谢您选择我们！期待在 ${apptDatetime} 见到您。`
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: `感谢您选择我们！期待很快见到您。`,
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Cantonese: apptDatetime
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? `感謝您選擇我們！期待在 ${apptDatetime} 見到您。`
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: `感謝您選擇我們！期待很快見到您。`,
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Arabic: apptDatetime
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? `شكراً لاختيارك عيادتنا! نتطلع إلى رؤيتك في ${apptDatetime}.`
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: `شكراً لاختيارك عيادتنا! نتطلع إلى رؤيتك قريباً.`,
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"Haitian Creole": apptDatetime
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? `Mèsi dèske ou chwazi nou! N'ap tann ou ${apptDatetime}.`
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: `Mèsi dèske ou chwazi nou! N'ap tann ou byento.`,
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};
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const fallback = CLOSING[language] ?? CLOSING["English"]!;
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if (aiSettings?.apiKey && apptDatetime) {
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try {
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const { ChatGoogleGenerativeAI } = await import("@langchain/google-genai");
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const llm = new ChatGoogleGenerativeAI({ model: "gemini-1.5-flash", apiKey: aiSettings.apiKey });
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const res = await llm.invoke([
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{
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role: "system",
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content: `You are a friendly dental office AI assistant. The patient just said "${Body}" after completing a conversation. Reply warmly in ${language}, thanking them for choosing the office and reminding them of their upcoming appointment on ${apptDatetime}. 1-2 sentences, no formatting.`,
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},
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{ role: "user", content: Body },
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]);
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const aiMsg = String(res.content).trim();
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if (aiMsg) return reply(aiMsg, "done");
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} catch { /* fall through to fallback */ }
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}
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return reply(fallback, "done");
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}
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}
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// ── Stage: initial (no active conversation) ───────────────────────────
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// Check after-hours: if enabled and currently outside office hours → start new-patient flow
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if (stage === "initial" || stage === "done") {
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