LiveKit: an open source tool for building real-time audio and video applications

General Introduction

LiveKit is an open source project focused on helping developers build real-time audio and video applications. It is based on WebRTC technology , provides a complete solution , including media servers and a variety of client SDK. LiveKit is the core of a scalable SFU (Selective Forwarding Unit) server , written in the Go language , combined with the Pion WebRTC implementation. It is designed to be simple and straightforward, supporting a wide range of scenarios from small applications to large-scale conferences. Developers can use it to quickly set up video conferencing, interactive live streaming, or voice assistants, etc. LiveKit offers both cloud-hosted and self-hosted options for flexibility. Official documentation and community support also make it easy to get started.

Function List

• Real-time audio and video communications: Supports low-latency audio and video calls for multiple people at the same time.
• SFU Media Server: Optimize bandwidth with selective forwarding technology to improve performance for large-scale applications.
• Multi-platform SDK: Provide JavaScript, iOS, Android and other client SDKs to facilitate cross-platform development.
• Server-side support: Contains tools for generating access tokens, calling APIs, and receiving webhooks.
• data channel: Supports real-time transmission of text or customized data, suitable for interactive applications.
• Cloud services vs. self-hosted: Optional LiveKit Cloud or deploy your own server.
• AI Integration: Support for combining with voice and video AI models, suitable for intelligent assistant development.

Using Help

There are two ways to use LiveKit: one is to use LiveKit Cloud directly, and the other is to deploy your own server. Here are the detailed steps.

Installation and Deployment

If you choose to self-host, you need to install the LiveKit server first. Here are the basic steps:

1. Preparing the environment: Make sure your system supports Docker and can run Linux or macOS.
2. Installing the LiveKit CLI: This is the command line tool to help you manage the server and test features. Run the following command:

curl -sSL https://get.livekit.io | bash

After the installation is complete, enter livekit-cli --version Check for success.
3. Start the server: Start the LiveKit server in development mode by running the following command in a terminal:

livekit-server --dev

This will start a local server, which by default listens on the 7880 Ports.
4. Generating access tokens: The server requires token authentication. Generated with the CLI:

livekit-cli create-token --api-key devkey --api-secret secret --identity user1 --room my-room

The output will contain a JWT token for connecting to the room.

If you use LiveKit Cloud, register an account directly at cloud.livekit.io, create a project and get the API key and key pair, no need to deploy it yourself.

Connecting Rooms

Connecting rooms is the core operation of LiveKit. The following is an example of the JavaScript SDK:

1. Installing the SDK: Runs in the project:

npm install @livekit/client

2. Join the room: Connect with the following code:

import { Room, connect } from '@livekit/client';
const room = new Room();
const token = '你的令牌'; // 从 CLI 或云服务获取
await connect(room, token, { url: 'ws://localhost:7880' });
console.log('已连接到房间');

3. Publishing Audio and Video: After connecting, publish the local camera and microphone:

   const localParticipant = room.localParticipant;
   await localParticipant.enableCameraAndMicrophone();
   console.log('开始发布音视频');
   

Featured Function Operation

• Real-time data transmission: In addition to audio and video, LiveKit supports data channels. The code to send a message is as follows:

  localParticipant.publishData('Hello, everyone!', 'text');
  

  The receiver listens:

  room.on('dataReceived', (payload, participant) => {
  console.log(`收到消息：${payload}，来自 ${participant.identity}`);
  });
  

• AI IntegrationLiveKit supports interfacing with AI models. For example, using Python SDK to realize speech to text:

  from livekit import Room
  room = Room()
  await room.connect('ws://localhost:7880', token)
  # 监听音频并处理
  

  Real-time transcription can be achieved by combining it with a speech recognition API such as Google STT.

• Mass Live Streaming: Push streams from OBS with LiveKit Ingress:
  1. Create an Ingress in the cloud console to get the RTMP URL and stream key.
  2. Fill in the URL and key in the OBS settings to start pushing the stream.
  3. Viewers watch with low latency over WebRTC.

workflow

1. Determine the need: is it a small call or a large live broadcast?
2. Choose your deployment method: cloud services save you money, self-hosting is more flexible.
3. Configure the environment: install the tools and get the key.
4. Develop apps: Connect rooms with the SDK and add functionality.
5. Test run: Simulate traffic with the CLI and check the effect.

The LiveKit documentation is available at docs.livekit.io, and you can join the Slack community to ask for help if you have questions.

application scenario

1. videoconferencing
   The company's team uses LiveKit to build an internal meeting system that supports real-time discussions among multiple people.
2. live interactive broadcast
   The host pushes the stream through OBS, and the audience can interact with it in real time using WebRTC, with a latency of less than 100 milliseconds.
3. AI voice assistant
   Developers combine AI models to create intelligent customer service that can listen and speak.
4. distance learning
   Teachers and students conduct online classes through LiveKit, which supports screen sharing and real-time Q&A.

QA

1. How many simultaneous users does LiveKit support?
   It can support concurrency from a few to thousands of people, depending on server configuration and bandwidth.
2. What hardware do I need for self-hosting?
   A 4-core server with 8GB of RAM can run small applications; large scale requires higher configurations.
3. Is LiveKit Cloud free?
   Offers a free credit, beyond which you are charged per traffic, see livekit.io/pricing.