Build an OpenAI GPT Live voice agent with Next.js

Use Agora's TypeScript SDK to run an OpenAI GPT Live voice agent from Next.js server routes. GPT Live handles speech input, reasoning, and speech output as one MLLM stage. The browser publishes microphone audio and displays transcripts, agent state, and latency metrics.

Prerequisites

• Node.js 22 or newer
• pnpm
• Agora CLI
• An Agora project with an App ID and App Certificate
• An OpenAI API key with GPT Live access

Run the recipe

Clone the repository, install dependencies, and create the environment file:

git clone git@github.com:AgoraIO-Community/OpenAI-Agora-Voice-Agents-NextJS.git
cd OpenAI-Agora-Voice-Agents-NextJS
pnpm install
cp env.local.example .env.local

Use the Agora CLI to select a project and write its credentials to .env.local:

agora login
agora project use <your-project-name-or-id>
agora project env write .env.local --template nextjs

Add your OpenAI key to .env.local:

NEXT_OPENAI_API_KEY=your_openai_api_key

Start the app:

pnpm run dev

Open http://localhost:3000, allow microphone access, and select Start conversation.

Configure GPT Live

The server route creates the MLLM and starts a session with the browser's channel and UID:

import { AgoraClient, Agent, Area, ExpiresIn, OpenAIGPTLive } from 'agora-agents';

async function startAgent(channel: string, agentUid: string, userUid: string) {
  const client = new AgoraClient({
    area: Area.US,
    appId: process.env.NEXT_PUBLIC_AGORA_APP_ID!,
    appCertificate: process.env.NEXT_AGORA_APP_CERTIFICATE!,
  });

  const agent = new Agent({
    client,
    advancedFeatures: { enable_rtm: true, enable_tools: false },
    parameters: {
      audio_scenario: 'chorus',
      data_channel: 'rtm',
      enable_error_message: true,
      enable_metrics: true,
    },
  }).withMllm(
    new OpenAIGPTLive({
      apiKey: process.env.NEXT_OPENAI_API_KEY!,
      model: 'gpt-live-1',
      voice: 'cedar',
      prompt: 'You are a concise and helpful voice assistant.',
      greeting: 'Hello! How can I help?',
      messages: [
        { role: 'user', content: 'My name is Arlene.' },
        { role: 'assistant', content: 'Nice to meet you, Arlene.' },
      ],
    }),
  );

  const session = agent.createSession({
    channel,
    agentUid,
    remoteUids: [userUid],
    idleTimeout: 30,
    expiresIn: ExpiresIn.hours(1),
  });
  const agentId = await session.start();
  return { agentId, session };
}

The complete sample generates an RTC+RTM token before starting the agent. The browser and agent join the same channel with different UIDs, and remoteUids identifies the browser user whose audio the agent should process.

Customize the conversation

Use prompt for system behavior and messages to continue an earlier conversation. Keep the App Certificate, OpenAI key, and conversation history in server code.

Stop the agent

Retain the session returned by startAgent and stop it when the call ends:

await session.stop();

For a multi-instance deployment, store lifecycle ownership in shared state or route start and stop requests to the same instance.

Verify the project

pnpm run verify

See the project README for architecture, deployment, configuration options, and troubleshooting.