What this verified tutorial builds

This tutorial builds a small support-workflow application using Next.js and React. An agent can enter a customer message, choose a support category, select a reply style, submit the request to a server route, and review the normalized result. The completed project is intentionally useful without pretending that a language model has been connected when its provider contract has not been verified.

The verified context supports Next.js as a React framework used to build modern web applications. It identifies capabilities including App Router, server-side rendering, static generation, API routes, TypeScript support, and image optimization. This guide uses the App Router and a route handler because they provide a clear separation between an interactive browser interface and server-side application logic.

The verified OpenAI context also describes an OpenAI DevDay example in which a FastAPI server was connected to a Next.js front end. That example is an important architectural lesson: a Next.js interface can work with a dedicated backend service. It does not, however, verify a particular OpenAI JavaScript SDK, model name, endpoint, parameter, response schema, price, or quota. For that reason, this article creates a dependable integration boundary rather than publishing unverified provider code.

The result is a foundation for a support product: a browser form, a typed request contract, a server route, a predictable response shape, and a review panel. Once your organization has verified the current OpenAI API documentation and its own handling requirements for customer data, the sample route can be replaced with a server-side adapter that calls the approved provider service.

Prerequisites

• A current Node.js LTS installation and npm.
• Basic familiarity with React components, TypeScript, and the command line.
• A new Next.js project created with TypeScript and App Router enabled.
• A code editor capable of editing TypeScript and TSX files.
• Non-sensitive example support messages for local testing.

Do not use real passwords, access tokens, payment-card data, or confidential customer records in a local demonstration. This tutorial processes example text only. A production support workflow needs its own approved data-handling, retention, access-control, and review processes.

Step 1: Create the Next.js project

Create a new application with the current Next.js project generator. Select TypeScript and App Router when prompted. The exact generator prompts can change between releases, so review them before confirming your choices.

npx create-next-app@latest nextjs-support-workflow
cd nextjs-support-workflow
npm run dev

Open http://localhost:3000 after the development server starts. Next.js provides a file-based application structure. In this tutorial, the home page is rendered from src/app/page.tsx, while the server endpoint is implemented in src/app/api/support-request/route.ts.

Keep the initial application narrow. A support interface does not need authentication, a customer database, an AI provider, a CRM integration, or automatic sending in order to validate its first workflow. Start by making the request and review experience clear. Then add independently tested capabilities one at a time.

Step 2: Define a shared support contract

A support interface benefits from a stable contract between the browser and server. TypeScript provides compile-time feedback, but the route handler still checks incoming values at runtime. The browser is not a trusted enforcement point: a user can alter form values or send a request directly to the route.

Create src/lib/support.ts:

export const productAreas = [
  "Billing",
  "Account access",
  "Technical issue",
  "General question",
] as const;

export const tones = ["Warm", "Concise", "Formal"] as const;

export type ProductArea = (typeof productAreas)[number];
export type Tone = (typeof tones)[number];

export type SupportRequest = {
  ticket: string;
  productArea: ProductArea;
  tone: Tone;
};

export type SupportReview = {
  received: boolean;
  ticketLength: number;
  productArea: ProductArea;
  tone: Tone;
  nextStep: string;
};

export function isProductArea(value: unknown): value is ProductArea {
  return typeof value === "string" && productAreas.includes(value as ProductArea);
}

export function isTone(value: unknown): value is Tone {
  return typeof value === "string" && tones.includes(value as Tone);
}

export function parseSupportRequest(value: unknown): SupportRequest | null {
  if (!value || typeof value !== "object") return null;

  const input = value as Record<string, unknown>;
  const ticket = typeof input.ticket === "string" ? input.ticket.trim() : "";

  if (ticket.length < 20 || ticket.length > 8000) return null;
  if (!isProductArea(input.productArea) || !isTone(input.tone)) return null;

  return { ticket, productArea: input.productArea, tone: input.tone };
}

This module gives the form and route handler one vocabulary. The request contains ticket text, a bounded category, and a bounded tone. The response is deliberately operational rather than AI-generated: it confirms receipt, records the text length, repeats the selected options, and provides a next-step message. That makes the application testable without representing simulated content as an AI answer.

The 20-to-8,000-character range is a product decision in this sample, not an OpenAI limit. Adjust it after evaluating the types of messages your own support team receives and the constraints of any approved backend service.

Step 3: Add the server route handler

Route handlers provide a server-side HTTP boundary in an App Router project. Create src/app/api/support-request/route.ts:

import { NextRequest } from "next/server";
import {
parseSupportRequest,
type SupportReview,
} from "@/lib/support";export async function POST(request: NextRequest) {
let body: unknown;try {
body = await request.json();
} catch {
return Response.json(
{ error: "Send a valid JSON request body." },
{ status: 400 },
);
}const input = parseSupportRequest(body);if (!input) {
return Response.json(
{
error:
"Enter 20 to 8,000 characters and select a supported product area and tone.",
},
{ status: 400 },
...
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