OpenUI Forge — OpenAI

Build generative UI apps with OpenUI + OpenAI SDK. One backend, one adapter, streaming out of the box.

Activation Triggers

• "openui openai", "openui gpt", "openui chatgpt"
• "generative ui openai", "openai streaming ui"

Prerequisites

• Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
• OPENAI_API_KEY environment variable set
• Optional: OPENAI_BASE_URL to route via an OpenAI-compatible provider (Gemini, OpenRouter, xAI, DeepSeek, etc.) without code changes. OPENAI_BASE_URL is the correct env var; the legacy OPENAI_API_BASE was removed in openai v6. See Provider Routing below.
• Optional: OPENAI_MODEL to pin a specific model (defaults to gpt-5.5)
• Next.js project (App Router recommended)

Provider Routing

This is the OpenAI-compatible variant: the same OpenAI client and chat.completions.create code talks to any provider below by setting OPENAI_BASE_URL (and OPENAI_MODEL). No code changes. OPENAI_BASE_URL is the correct env var; the old OPENAI_API_BASE was removed in openai v6.

Provider	OPENAI_BASE_URL	Example OPENAI_MODEL
Gemini	https://generativelanguage.googleapis.com/v1beta/openai/	gemini-3.5-flash
OpenRouter	https://openrouter.ai/api/v1	anthropic/claude-opus-4.7
xAI (Grok)	https://api.x.ai/v1	grok-4.3
DeepSeek	https://api.deepseek.com	deepseek-v4-pro
Groq	https://api.groq.com/openai/v1	llama-3.3-70b-versatile
Mistral	https://api.mistral.ai/v1	mistral-large-latest
Together	https://api.together.ai/v1	openai/gpt-oss-20b
Fireworks	https://api.fireworks.ai/inference/v1	accounts/fireworks/models/glm-5
Ollama (local)	http://localhost:11434/v1/	llama3.3 (any placeholder API key)
LM Studio (local)	http://localhost:1234/v1	loaded model id (any placeholder API key)

Model ids drift; check each provider's current catalog. Base-url routing covers chat completions only, not full OpenAI API parity.

Azure OpenAI is not a generic drop-in. Use OPENAI_BASE_URL=https://YOUR-RESOURCE.openai.azure.com/openai/v1/, set OPENAI_MODEL to your deployment name (not a catalog id like gpt-5.5), and prefer the AzureOpenAI client. The legacy data-plane path also needs an ?api-version= query param.

Quick Start

1. Install dependencies:

npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod openai

2. Add the CSS import to app/layout.tsx:

import "@openuidev/react-ui/components.css";

3. Create the API route (Step 4 below)
4. Create the frontend page (Step 5 below)
5. Run npm run dev and test

Full Code

Backend: app/api/chat/route.ts

import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import OpenAI from "openai";

const client = new OpenAI();

export async function POST(req: Request) {
  const { messages } = await req.json();

  const systemPrompt = openuiChatLibrary.prompt({
    preamble: "You are a helpful assistant that generates interactive UIs.",
    additionalRules: ["Always use Stack as root when combining multiple components."],
  });

  const response = await client.chat.completions.create({
    model: process.env.OPENAI_MODEL ?? "gpt-5.5",
    stream: true,
    messages: [{ role: "system", content: systemPrompt }, ...messages],
  });

  // response.toReadableStream() produces NDJSON (one JSON object per line, no SSE `data:` prefix).
  // Pair with openAIReadableStreamAdapter() on the frontend.
  return new Response(response.toReadableStream(), {
    headers: { "Content-Type": "application/x-ndjson" },
  });
}

Frontend: app/chat/page.tsx

"use client";
import { FullScreen } from "@openuidev/react-ui";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import {
  openAIReadableStreamAdapter,
  openAIMessageFormat,
} from "@openuidev/react-headless";

export default function ChatPage() {
  return (
    <FullScreen
      componentLibrary={openuiChatLibrary}
      streamProtocol={openAIReadableStreamAdapter()}
      messageFormat={openAIMessageFormat}
      apiUrl="/api/chat"
    />
  );
}

Component Creation

import { defineComponent } from "@openuidev/react-lang";
import { z } from "zod";

export const MyCard = defineComponent({
  name: "MyCard",
  description: "A card displaying a title and body text",
  props: z.object({
    title: z.string().describe("The card heading"),
    body: z.string().describe("The card body content"),
  }),
  component: ({ props }) => (
    <div style={{ border: "1px solid #ddd", borderRadius: 8, padding: 16 }}>
      <h3>{props.title}</h3>
      <p>{props.body}</p>
    </div>
  ),
});

Add to a custom library with createLibrary([MyCard, ...others]) or use the built-in openuiLibrary.

System Prompt Generation

For runtime generation (used in the route above), call library.prompt(). For a static file:

npx @openuidev/cli generate ./src/lib/library.ts --out src/generated/system-prompt.txt

Validation Checklist

• OPENAI_API_KEY is set in .env.local
• CSS import present in root layout
• API route returns response.toReadableStream() with application/x-ndjson content type
• Frontend uses streamProtocol={openAIReadableStreamAdapter()} and openAIMessageFormat
• componentLibrary={openuiChatLibrary} prop passed to FullScreen
• React >= 18.3.1 installed (peer accepts ^18.3.1 || ^19.0.0)

Error Patterns

Error	Cause	Fix
401 from OpenAI	Missing or invalid API key	Set OPENAI_API_KEY in .env.local
Stream hangs	Missing toReadableStream() call	Ensure stream: true and return response.toReadableStream()
Components render as text	Library not passed to FullScreen	Add componentLibrary={openuiChatLibrary} prop
Blank screen	CSS not imported	Add @openuidev/react-ui/components.css to root layout
Nothing renders, no error	Wrong prop name (adapter is silently ignored)	Rename to streamProtocol and call the adapter as a function: streamProtocol={openAIReadableStreamAdapter()}
Partial render then stop	Model finished mid-output	Check token limits, increase max_tokens if needed