This repository contains a reference client aka sample library for connecting to OpenAI's Realtime API. This library is in beta and should not be treated as a final implementation. You can use it to easily prototype conversational apps.
The easiest way to get playing with the API right away is to use the Realtime Console, it uses the reference client to deliver a fully-functional API inspector with examples of voice visualization and more.
This library is built to be used both server-side (Node.js) and in browser (React, Vue),
in both JavaScript and TypeScript codebases. While in beta, to install the library you will
need to npm install directly from the GitHub repository.
$ npm i openai/openai-realtime-api-beta --saveimport { RealtimeClient } from '@openai/realtime-api-beta';
const client = new RealtimeClient({ apiKey: process.env.OPENAI_API_KEY });
// Can set parameters ahead of connecting, either separately or all at once
client.updateSession({ instructions: 'You are a great, upbeat friend.' });
client.updateSession({ voice: 'alloy' });
client.updateSession({
turn_detection: { type: 'none' }, // or 'server_vad'
input_audio_transcription: { model: 'whisper-1' },
});
// Set up event handling
client.on('conversation.updated', (event) => {
const { item, delta } = event;
const items = client.conversation.getItems();
/**
* item is the current item being updated
* delta can be null or populated
* you can fetch a full list of items at any time
*/
});
// Connect to Realtime API
await client.connect();
// Send a item and triggers a generation
client.sendUserMessageContent([{ type: 'input_text', text: `How are you?` }]);You can use this client directly from the browser in e.g. React or Vue apps. We do not recommend this, your API keys are at risk if you connect to OpenAI directly from the browser. In order to instantiate the client in a browser environment, use:
import { RealtimeClient } from '@openai/realtime-api-beta';
const client = new RealtimeClient({
apiKey: process.env.OPENAI_API_KEY,
dangerouslyAllowAPIKeyInBrowser: true,
});If you are running your own relay server, e.g. with the Realtime Console, you can instead connect to the relay server URL like so:
const client = new RealtimeClient({ url: RELAY_SERVER_URL });In this library, there are three primitives for interfacing with the Realtime API.
We recommend starting with the RealtimeClient, but more advanced users may be
more comfortable working closer to the metal.
RealtimeClient
conversation.updated, conversation.item.appended, conversation.item.completed, conversation.interrupted and realtime.event eventsRealtimeAPI
client.realtimeserver.{event_name} and client.{event_name}, respectivelyRealtimeConversation
client.conversationThe client comes packaged with some basic utilities that make it easy to build realtime apps quickly.
Sending messages to the server from the user is easy.
client.sendUserMessageContent([{ type: 'input_text', text: `How are you?` }]);
// or (empty audio)
client.sendUserMessageContent([
{ type: 'input_audio', audio: new Int16Array(0) },
]);To send streaming audio, use the .appendInputAudio() method. If you're in turn_detection: 'disabled' mode,
then you need to use .createResponse() to tell the model to respond.
// Send user audio, must be Int16Array or ArrayBuffer
// Default audio format is pcm16 with sample rate of 24,000 Hz
// This populates 1s of noise in 0.1s chunks
for (let i = 0; i < 10; i++) {
const data = new Int16Array(2400);
for (let n = 0; n < 2400; n++) {
const value = Math.floor((Math.random() * 2 - 1) * 0x8000);
data[n] = value;
}
client.appendInputAudio(data);
}
// Pending audio is committed and model is asked to generate
client.createResponse();Working with tools is easy. Just call .addTool() and set a callback as the second parameter.
The callback will be executed with the parameters for the tool, and the result will be automatically
sent back to the model.
// We can add tools as well, with callbacks specified
client.addTool(
{
name: 'get_weather',
description:
'Retrieves the weather for a given lat, lng coordinate pair. Specify a label for the location.',
parameters: {
type: 'object',
properties: {
lat: {
type: 'number',
description: 'Latitude',
},
lng: {
type: 'number',
description: 'Longitude',
},
location: {
type: 'string',
description: 'Name of the location',
},
},
required: ['lat', 'lng', 'location'],
},
},
async ({ lat, lng, location }) => {
const result = await fetch(
`https://api.open-meteo.com/v1/forecast?latitude=${lat}&longitude=${lng}¤t=temperature_2m,wind_speed_10m`,
);
const json = await result.json();
return json;
},
);The .addTool() method automatically runs a tool handler and triggers a response
on handler completion. Sometimes you may not want that, for example: using tools
to generate a schema that you use for other purposes.
In this case, we can use the tools item with updateSession. In this case you
must specify type: 'function', which is not required for .addTool().
Note: Tools added with .addTool() will not be overridden when updating
sessions manually like this, but every updateSession() change will override previous
updateSession() changes. Tools added via .addTool() are persisted and appended
to anything set manually here.
client.updateSession({
tools: [
{
type: 'function',
name: 'get_weather',
description:
'Retrieves the weather for a given lat, lng coordinate pair. Specify a label for the location.',
parameters: {
type: 'object',
properties: {
lat: {
type: 'number',
description: 'Latitude',
},
lng: {
type: 'number',
description: 'Longitude',
},
location: {
type: 'string',
description: 'Name of the location',
},
},
required: ['lat', 'lng', 'location'],
},
},
],
});Then, to handle function calls...
client.on('conversation.updated', ({ item, delta }) => {
if (item.type === 'function_call') {
// do something
if (delta.arguments) {
// populating the arguments
}
}
});
client.on('conversation.item.completed', ({ item }) => {
if (item.type === 'function_call') {
// your function call is complete, execute some custom code
}
});You may want to manually interrupt the model, especially in turn_detection: 'disabled' mode.
To do this, we can use:
// id is the id of the item currently being generated
// sampleCount is the number of audio samples that have been heard by the listener
client.cancelResponse(id, sampleCount);This method will cause the model to immediately cease generation, but also truncate the
item being played by removing all audio after sampleCount and clearing the text
response. By using this method you can interrupt the model and prevent it from "remembering"
anything it has generated that is ahead of where the user's state is.
If you need more manual control and want to send custom client events according
to the Realtime Client Events API Reference,
you can use client.realtime.send() like so:
// manually send a function call output
client.realtime.send('conversation.item.create', {
item: {
type: 'function_call_output',
call_id: 'my-call-id',
output: '{function_succeeded:true}',
},
});
client.realtime.send('response.create');With RealtimeClient we have reduced the event overhead from server events to five
main events that are most critical for your application control flow. These events
are not part of the API specification itself, but wrap logic to make application
development easier.
// errors like connection failures
client.on('error', (event) => {
// do thing
});
// in VAD mode, the user starts speaking
// we can use this to stop audio playback of a previous response if necessary
client.on('conversation.interrupted', () => {
/* do something */
});
// includes all changes to conversations
// delta may be populated
client.on('conversation.updated', ({ item, delta }) => {
// get all items, e.g. if you need to update a chat window
const items = client.conversation.getItems();
switch (item.type) {
case 'message':
// system, user, or assistant message (item.role)
break;
case 'function_call':
// always a function call from the model
break;
case 'function_call_output':
// always a response from the user / application
break;
}
if (delta) {
// Only one of the following will be populated for any given event
// delta.audio = Int16Array, audio added
// delta.transcript = string, transcript added
// delta.arguments = string, function arguments added
}
});
// only triggered after item added to conversation
client.on('conversation.item.appended', ({ item }) => {
/* item status can be 'in_progress' or 'completed' */
});
// only triggered after item completed in conversation
// will always be triggered after conversation.item.appended
client.on('conversation.item.completed', ({ item }) => {
/* item status will always be 'completed' */
});If you want more control over your application development, you can use the
realtime.event event and choose only to respond to server events.
The full documentation for these events are available on
the Realtime Server Events API Reference.
// all events, can use for logging, debugging, or manual event handling
client.on('realtime.event', ({ time, source, event }) => {
// time is an ISO timestamp
// source is 'client' or 'server'
// event is the raw event payload (json)
if (source === 'server') {
doSomething(event);
}
});You will need to make sure you have a .env file with OPENAI_API_KEY= set in order
to run tests. From there, running the test suite is easy.
$ npm testTo run tests with debug logs (will log events sent to and received from WebSocket), use:
$ npm test -- --debugThank you for checking out the Realtime API. Would love to hear from you. Special thanks to the Realtime API team for making this all possible.