LiveKit is a free, open source automation project written in Go and released under Apache-2.0. It has 20,973 GitHub stars, 2,347 forks and 189 open issues, and was last pushed 19 hours ago. On this registry it ranks #9 of 54 tracked projects in Automation, with 5 head-to-head comparisons available. It gained 102 stars over the last 6 tracked days.

LiveKit — Full-stack platform for voice, video, and physical AI agents

What is LiveKit?

What it is

LiveKit is an open-source realtime infrastructure project for voice, video, and physical AI agents, and it lives in the WebRTC, media-server, and voice-AI ecosystem. The repository contains the LiveKit server, a scalable distributed WebRTC SFU written in Go and built on Pion WebRTC. It moves realtime audio, video, and data between people, devices, and AI models, while SDKs, agent frameworks, and companion services are provided separately.

The concrete problem it solves is connecting humans and AI inside the same realtime communication session. A team building voice or video agents needs transport for media and data, participant rooms, routing for AI agents, authentication, and SDKs. LiveKit provides the server layer for those sessions, and the linked LiveKit Agents framework adds code-first voice-agent workflows with speech recognition, language models, speech synthesis, turn detection, tool usage, and telephony.

Key capabilities

  • The server operates as a distributed WebRTC SFU that forwards realtime audio, video, and data between participants.
  • It lets people, devices, and AI agents join the same room, with agent dispatch to route agents automatically or on demand.
  • It provides SDKs for web, mobile, desktop, embedded, and server environments.
  • It supports JWT authentication for production use.
  • The Agents framework bundles STT, LLM, TTS, turn detection, expressive speech, keyterm accuracy, tool usage, and telephony.
  • The Agents framework offers Python and Node.js bindings.
  • LiveKit Inference supplies models without per-provider API keys, and LiveKit Cloud provides deployment and observability.

Who uses it and how

  • Production teams use it for realtime voice and video calls at large scale; the README names Salesforce, Nvidia, Oracle, SAP, Spotify, Tinder, Coursera, Headspace, Skydio, Retell, Decagon, Cresta, and HeyGen.
  • Voice AI developers use LiveKit Agents to connect speech recognition, language models, text-to-speech, turn detection, tools, and telephony in code-first Python or Node.js applications.
  • Product teams use the same room model so human users, devices, and AI agents can participate together, with agent dispatch placing AI participants into sessions.
  • Teams evaluating hosted operation can use LiveKit Cloud for deployment and observability, while the open-source server remains the core WebRTC media layer.

Getting started

The README points to the Go-based LiveKit server for the SFU, to LiveKit Agents in Python or Node.js for voice AI workflows, and to LiveKit Cloud for deployment and observability.

When to use it — and when not to

Use LiveKit when a team needs open-source WebRTC infrastructure for realtime audio, video, data, and AI participants in shared rooms. Do not treat this repository as a complete application, because the SDKs, the Agents framework, and companion services are separate and must be assembled around the server. The project is also new, with zero contributors listed, 189 open issues, and a repository age of zero years.

project readme (upstream, from github) — read inline

LiveKit: Realtime infrastructure for voice, video, and AI agents

LiveKit is an open source platform for building voice, video, and physical AI agents. This repository is the LiveKit server: a scalable, distributed WebRTC SFU that moves realtime audio, video, and data between people, devices, and AI models. The SDKs, agents frameworks, and companion services are linked in the table at the bottom of this page.

LiveKit's server is written in Go, using the awesome Pion WebRTC implementation.

GitHub stars Slack community Twitter Follow Ask DeepWiki GitHub release (latest SemVer) GitHub Workflow Status License

[!IMPORTANT] If you're building Voice AI, LiveKit Agents is the SDK for code-first realtime voice agents. STT, LLM, TTS, turn detection, expressive speech, keyterm accuracy, tool usage, and telephony all come bundled in the framework. It's available in both Python and Node.js.

# agent.py
from livekit import agents
from livekit.agents import Agent, AgentServer, AgentSession, STTContextOptions, TurnHandlingOptions, inference

server = AgentServer()


@server.rtc_session(agent_name="my-agent")
async def my_agent(ctx: agents.JobContext):
    session = AgentSession(
        stt=inference.STT(model="deepgram/nova-3", language="multi"),
        llm=inference.LLM(model="google/gemma-4-31b-it"),
        tts=inference.TTS(model="inworld/inworld-tts-2", voice="Ashley"),
        turn_handling=TurnHandlingOptions(turn_detection=inference.TurnDetector()),
        stt_context_options=STTContextOptions(keyterms=["LiveKit", "Acme Corp"]),
        expressive=True,
    )
    await session.start(room=ctx.room, agent=Agent(instructi))
    await session.generate_reply(instructi)


if __name__ == "__main__":
    agents.cli.run_app(server)

Models come from LiveKit Inference with no per-provider API keys, and LiveKit Cloud handles deployment and observability. Visit the docs for more info at docs.livekit.io/agents.

Used in production by

LiveKit carries billions of calls a year for companies including Salesforce, Nvidia, Oracle, SAP, Deutsche Telekom, Spotify, Tinder, Coursera, Headspace, Skydio, Retell, Decagon, Cresta, and HeyGen. Read how Assort Health, Playback, and Polymath Robotics use it, or see more customers.

Features

Documentation & Guides

https://docs.livekit.io

Working with a coding agent? Give it the LiveKit Docs MCP server, or start with the coding agents guide.

Live Demos

Install

[!TIP] We recommend installing LiveKit CLI along with the server. It lets you access server APIs, create tokens, generate test traffic, and scaffold and deploy agents.

The following will install LiveKit's media server:

MacOS

brew install livekit

Linux

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

Windows

Download the latest release here

Getting Started

Starting LiveKit

Start LiveKit in development mode by running livekit-server --dev. It'll use a placeholder API key/secret pair.

API Key: devkey
API Secret: secret

To customize your setup for production, refer to our deployment docs

Creating access token

A user connecting to a LiveKit room requires an access token. Access tokens (JWT) encode the user's identity and the room permissions they've been granted. You can generate a token with our CLI:

lk token create \
    --api-key devkey --api-secret secret \
    --join --room my-first-room --identity user1 \
    --valid-for 24h

Test with example app

Head over to our example app and enter a generated token to connect to your LiveKit server.

Once connected, your video and audio are now being published to your new LiveKit instance!

Simulating a test publisher

lk room join \
    --url ws://localhost:7880 \
    --api-key devkey --api-secret secret \
    --identity bot-user1 \
    --publish-demo \
    my-first-room

This command publishes a looped demo video to a room. Due to how the video clip was encoded (keyframes every 3s), there's a slight delay before the browser has sufficient data to begin rendering frames. This is an artifact of the simulation.

Adding an agent

Agents join rooms as participants, the same way a browser or a phone does. Follow the Voice AI quickstart to build one. An agent connects to a self-hosted server the same way it connects to LiveKit Cloud; when running without Cloud, use model plugins in place of LiveKit Inference.

Deployment

Use LiveKit Cloud

LiveKit Cloud is the fastest and most reliable way to run LiveKit. It runs in 19+ regions with 99.99% uptime and adds agent hosting, model inference, telephony, and observability on top of the server. The Build plan is free, with no credit card required.

readme truncated — read the full docs on github

Frequently asked questions

Is LiveKit free to use?

LiveKit is open source under the Apache-2.0 licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does LiveKit do?

Full-stack platform for voice, video, and physical AI agents

What is LiveKit written in?

LiveKit is primarily written in Go. Its source is publicly available at https://github.com/livekit/livekit, and it has 20,973 GitHub stars.