Openui Forge Anthropic

OpenUI Forge — Anthropic

Build generative UI apps with OpenUI + Anthropic Claude. Converts Anthropic streaming events to OpenAI-compatible NDJSON.

Activation Triggers

• "openui anthropic", "openui claude", "openui sonnet"
• "generative ui claude", "claude streaming ui"

Prerequisites

• Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
• ANTHROPIC_API_KEY environment variable set
• Next.js project (App Router recommended)

Quick Start

1. Install dependencies:

npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod @anthropic-ai/sdk

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

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

1. Create the API route and frontend page below
2. Run npm run dev and test

Full Code

Backend: app/api/chat/route.ts

The backend streams from Anthropic and converts each event into OpenAI-compatible SSE chunks that openAIAdapter() expects (data: {json}\n\n lines, terminated by data: [DONE]).

import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

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."],
  });

  // ANTHROPIC_MODEL alternatives: claude-opus-4-8, claude-haiku-4-5, claude-fable-5
  const stream = client.messages.stream({
    model: process.env.ANTHROPIC_MODEL ?? "claude-sonnet-4-6",
    max_tokens: 4096,
    system: systemPrompt,
    messages,
  });

  const encoder = new TextEncoder();
  const readableStream = new ReadableStream({
    async start(controller) {
      const id = `chatcmpl-${Date.now()}`;
      for await (const event of stream) {
        if (
          event.type === "content_block_delta" &&
          event.delta.type === "text_delta"
        ) {
          const chunk = {
            id,
            object: "chat.completion.chunk",
            choices: [
              {
                index: 0,
                delta: { content: event.delta.text },
                finish_reason: null,
              },
            ],
          };
          controller.enqueue(
            encoder.encode(`data: ${JSON.stringify(chunk)}\n\n`)
          );
        }
      }
      const done = {
        id,
        object: "chat.completion.chunk",
        choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
      };
      controller.enqueue(encoder.encode(`data: ${JSON.stringify(done)}\n\n`));
      controller.enqueue(encoder.encode("data: [DONE]\n\n"));
      controller.close();
    },
  });

  return new Response(readableStream, {
    headers: { "Content-Type": "text/event-stream" },
  });
}

Frontend: app/chat/page.tsx

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

export default function ChatPage() {
  return (
    
  );
}

> The backend emits SSE (data: {json}\n\n). Pair it with openAIAdapter() on the frontend — openAIReadableStreamAdapter() is for NDJSON (no data: prefix) and will silently produce no output here.

Component Creation

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

export const StatusCard = defineComponent({
  name: "StatusCard",
  description: "Displays a status with label and color indicator",
  props: z.object({
    label: z.string().describe("Status label text"),
    status: z.enum(["ok", "warning", "error"]).describe("Current status level"),
  }),
  component: ({ props }) => {
    const colors = { ok: "#22c55e", warning: "#eab308", error: "#ef4444" };
    return (
      
        
        {props.label}
      
    );
  },
});

System Prompt Generation

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

Or at runtime: openuiChatLibrary.prompt({ preamble: "...", additionalRules: [...] }).

Validation Checklist

• [ ] ANTHROPIC_API_KEY is set in .env.local
• [ ] CSS import present in root layout
• [ ] Backend converts Anthropic content_block_delta events to OpenAI-compatible SSE chunks
• [ ] Final chunk has finish_reason: "stop" and ends with data: [DONE]
• [ ] Frontend uses streamProtocol={openAIAdapter()} and openAIMessageFormat
• [ ] componentLibrary={openuiChatLibrary} prop passed to FullScreen

Error Patterns

| Error | Cause | Fix | |-------|-------|-----| | 401 from Anthropic | Missing or invalid API key | Set ANTHROPIC_API_KEY in .env.local | | Stream hangs | Missing [DONE] sentinel or controller.close() | Ensure final chunk and [DONE] are sent | | Garbled output | Not wrapping in data: ... SSE format | Each chunk must be data: {json}\n\n | | Components render as text | Library not passed to FullScreen | Add componentLibrary={openuiChatLibrary} prop | | Nothing renders, no error | Used openAIReadableStreamAdapter() (NDJSON) on SSE stream, or adapter= prop (silently ignored) | Use streamProtocol={openAIAdapter()} | | max_tokens required | Anthropic API requires explicit max_tokens | Always set max_tokens (e.g., 4096) |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: OthmanAdi
• Source: OthmanAdi/openui-forge
• License: MIT
• Homepage: https://spruce-prism-8yya.here.now/

Install and usage instructions live in the source repository linked above.