By name: livekit
description: Build voice AI agents with LiveKit. Use when developing realtime voice applications, voice agent pipelines (STT-LLM-TTS), WebRTC communication, or deploying conversational AI. Covers LiveKit Agents SDK, provider selection (Deepgram, OpenAI, ElevenLabs, Cartesia), cloud vs self-hosted deployment.
LiveKit Voice AI Skill
Build production voice agents with LiveKit's open-source platform.
Quick Start
# Install SDK
pip install livekit-agents livekit-plugins-openai livekit-plugins-deepgram livekit-plugins-cartesia
# Or Node.js
npm install @livekit/agents @livekit/agents-plugin-openai
Minimal Agent (Python)
from livekit.agents import AgentSession, JobContext, WorkerOptions, cli
from livekit.plugins import deepgram, openai, cartesia
async def entrypoint(ctx: JobContext):
await ctx.connect()
session = AgentSession(
stt=deepgram.STT(),
llm=openai.LLM(model="gpt-4.1-mini"),
tts=cartesia.TTS(),
)
session.start(ctx.room)
await session.say("Hello! How can I help?")
if __name__ == "__main__":
cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
Provider Selection
| Component | Budget | Quality | Low Latency |
|-----------|--------|---------|-------------|
| STT | Deepgram Nova-3 | AssemblyAI | Deepgram Keychain |
| LLM | GPT-4.1 mini | Claude Sonnet | GPT-4.1 mini |
| TTS | Cartesia Sonic-3 | ElevenLabs | Cartesia Sonic-3 |
Voice Pipeline vs Realtime
STT-LLM-TTS Pipeline:
More control, mix providers
Generally cheaper
Easier to debug
OpenAI Realtime API:
Speech-to-speech, more expressive
Higher cost (~$0.10/min)
Less control
Environment Variables
LIVEKIT_URL=wss://your-app.livekit.cloud
LIVEKIT_API_KEY=your-api-key
LIVEKIT_API_SECRET=your-api-secret
# Provider keys (if not using LiveKit Inference)
OPENAI_API_KEY=
DEEPGRAM_API_KEY=
CARTESIA_API_KEY=
ELEVENLABS_API_KEY=
Tool Use
from livekit.agents import function_tool
@function_tool()
async def get_weather(location: str) -> str:
"""Get current weather for a location."""
# Your implementation
return f"Weather in {location}: 72°F, sunny"
session = AgentSession(
stt=deepgram.STT(),
llm=openai.LLM(),
tts=cartesia.TTS(),
tools=[get_weather],
)
Telephony (SIP)
from livekit import api
# Outbound call
await lk_api.sip.create_sip_participant(
api.CreateSIPParticipantRequest(
sip_trunk_id="trunk-id",
sip_call_to="+15551234567",
room_name="my-room",
)
)
Deployment
LiveKit Cloud: livekit-server-cli deploy --project my-project
Self-hosted:
docker run -d \
-p 7880:7880 -p 7881:7881 -p 7882:7882/udp \
-e LIVEKIT_KEYS="api-key: api-secret" \
livekit/livekit-server
Cost Estimates
| Scenario | Monthly Cost |
|----------|--------------|
| Dev/testing | Free tier |
| 100 hrs/mo voice | ~$150-250 |
| Production B2B | ~$300-500 |
| High volume | Self-host |
Common Patterns
Turn Detection
session = AgentSession(
turn_detection=openai.TurnDetection(
threshold=0.5,
silence_duration_ms=500,
),
...
)
Interruption Handling
@session.on("user_speech_started")
async def handle_interruption():
session.stop_speaking()
Multi-Agent Handoff
await session.transfer_to(specialist_agent)
References
Examples: https://github.com/livekit/agents/tree/main/examples
Playground: https://agents-playground.livekit.io