Use this SDK to add realtime video, audio and data features to your Python app. By connecting to LiveKit Cloud or a self-hosted server, you can quickly build applications such as multi-modal AI, live streaming, or video calls with just a few lines of code.
This repo contains two packages
- livekit: Real-time SDK for connecting to LiveKit as a participant
- livekit-api: Access token generation and server APIs
$ pip install livekit-api
from livekit import api
import os
# will automatically use the LIVEKIT_API_KEY and LIVEKIT_API_SECRET env vars
token = api.AccessToken() \
.with_identity("python-bot") \
.with_name("Python Bot") \
.with_grants(api.VideoGrants(
room_join=True,
room="my-room",
)).to_jwt()
RoomService uses asyncio and aiohttp to make API calls. It needs to be used with an event loop.
from livekit import api
import asyncio
async def main():
lkapi = api.LiveKitAPI(
'http://localhost:7880',
)
room_info = await lkapi.room.create_room(
api.CreateRoomRequest(name="my-room"),
)
print(room_info)
results = await lkapi.room.list_rooms(api.ListRoomsRequest())
print(results)
await lkapi.aclose()
asyncio.get_event_loop().run_until_complete(main())
$ pip install livekit
from livekit import rtc
async def main():
room = rtc.Room()
@room.on("participant_connected")
def on_participant_connected(participant: rtc.RemoteParticipant):
logging.info(
"participant connected: %s %s", participant.sid, participant.identity)
async def receive_frames(stream: rtc.VideoStream):
async for frame in video_stream:
# received a video frame from the track, process it here
pass
# track_subscribed is emitted whenever the local participant is subscribed to a new track
@room.on("track_subscribed")
def on_track_subscribed(track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant):
logging.info("track subscribed: %s", publication.sid)
if track.kind == rtc.TrackKind.KIND_VIDEO:
video_stream = rtc.VideoStream(track)
asyncio.ensure_future(receive_frames(video_stream))
# By default, autosubscribe is enabled. The participant will be subscribed to
# all published tracks in the room
await room.connect(URL, TOKEN)
logging.info("connected to room %s", room.name)
# participants and tracks that are already available in the room
# participant_connected and track_published events will *not* be emitted for them
for participant in room.participants.items():
for publication in participant.track_publications.items():
print("track publication: %s", publication.sid)
room = rtc.Room()
...
chat = rtc.ChatManager(room)
# receiving chat
@chat.on("message_received")
def on_message_received(msg: rtc.ChatMessage):
print(f"message received: {msg.participant.identity}: {msg.message}")
# sending chat
await chat.send_message("hello world")
- Facelandmark: Use mediapipe to detect face landmarks (eyes, nose ...)
- Basic room: Connect to a room
- Publish hue: Publish a rainbow video track
- Publish wave: Publish a sine wave
Please join us on Slack to get help from our devs / community members. We welcome your contributions(PRs) and details can be discussed there.
LiveKit Ecosystem | |
---|---|
Realtime SDKs | React Components · Browser · Swift Components · iOS/macOS/visionOS · Android · Flutter · React Native · Rust · Node.js · Python · Unity (web) · Unity (beta) |
Server APIs | Node.js · Golang · Ruby · Java/Kotlin · Python · Rust · PHP (community) |
Agents Frameworks | Python · Playground |
Services | LiveKit server · Egress · Ingress · SIP |
Resources | Docs · Example apps · Cloud · Self-hosting · CLI |