Information
# OpenAI Realtime Console
This is an example application showing how to use the [OpenAI Realtime API](https://platform.openai.com/docs/guides/realtime) with [WebRTC](https://platform.openai.com/docs/guides/realtime-webrtc).
## Installation and usage
Before you begin, you'll need an OpenAI API key - [create one in the dashboard here](https://platform.openai.com/settings/api-keys). Create a \`.env\` file from the example file and set your API key in there:
\`\`\`bash
cp .env.example .env
\`\`\`
Running this application locally requires [Node.js](https://nodejs.org/) to be installed. Install dependencies for the application with:
\`\`\`bash
npm install
\`\`\`
Start the application server with:
\`\`\`bash
npm run dev
\`\`\`
This should start the console application on [http://localhost:3000](http://localhost:3000).
This application is a minimal template that uses [express](https://expressjs.com/) to serve the React frontend contained in the [\`/client\`](./client) folder. The server is configured to use [vite](https://vitejs.dev/) to build the React frontend.
This application shows how to send and receive Realtime API events over the WebRTC data channel and configure client-side function calling. You can also view the JSON payloads for client and server events using the logging panel in the UI.
For a more comprehensive example, see the [OpenAI Realtime Agents](https://github.com/openai/openai-realtime-agents) demo built with Next.js, using an agentic architecture inspired by [OpenAI Swarm](https://github.com/openai/swarm).
## Previous WebSockets version
The previous version of this application that used WebSockets on the client (not recommended in browsers) [can be found here](https://github.com/openai/openai-realtime-console/tree/websockets).
## License
MIT