# python-sdks
**Repository Path**: mirrors_ANYbotics/python-sdks
## Basic Information
- **Project Name**: python-sdks
- **Description**: LiveKit real-time and server SDKs for Python
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-08-24
- **Last Updated**: 2026-01-24
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
[](https://pypi.org/project/livekit/)
# ๐น๐๏ธ๐ Python SDK for LiveKit
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](https://pypi.org/project/livekit/): Real-time SDK for connecting to LiveKit as a participant
- [livekit-api](https://pypi.org/project/livekit-api/): Access token generation and server APIs
## Using Server API
```shell
$ pip install livekit-api
```
### Generating an access token
```python
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()
```
### Creating a room
RoomService uses asyncio and aiohttp to make API calls. It needs to be used with an event loop.
```python
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.run(main())
```
## Using Real-time SDK
```shell
$ pip install livekit
```
### Connecting to a room
see [room_example](examples/room_example.py) for full example
```python
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 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 identity, participant in room.remote_participants.items():
print(f"identity: {identity}")
print(f"participant: {participant}")
for tid, publication in participant.track_publications.items():
print(f"\ttrack id: {publication}")
```
### Sending and receiving chat
```python
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")
```
### RPC
Perform your own predefined method calls from one participant to another.
This feature is especially powerful when used with [Agents](https://docs.livekit.io/agents), for instance to forward LLM function calls to your client application.
#### Registering an RPC method
The participant who implements the method and will receive its calls must first register support:
```python
@room.local_participant.register_rpc_method("greet")
async def handle_greet(data: RpcInvocationData):
print(f"Received greeting from {data.caller_identity}: {data.payload}")
return f"Hello, {data.caller_identity}!"
```
In addition to the payload, your handler will also receive `response_timeout`, which informs you the maximum time available to return a response. If you are unable to respond in time, the call will result in an error on the caller's side.
#### Performing an RPC request
The caller may then initiate an RPC call like so:
```python
try:
response = await room.local_participant.perform_rpc(
destination_identity='recipient-identity',
method='greet',
payload='Hello from RPC!'
)
print(f"RPC response: {response}")
except Exception as e:
print(f"RPC call failed: {e}")
```
You may find it useful to adjust the `response_timeout` parameter, which indicates the amount of time you will wait for a response. We recommend keeping this value as low as possible while still satisfying the constraints of your application.
#### Errors
LiveKit is a dynamic realtime environment and calls can fail for various reasons.
You may throw errors of the type `RpcError` with a string `message` in an RPC method handler and they will be received on the caller's side with the message intact. Other errors will not be transmitted and will instead arrive to the caller as `1500` ("Application Error"). Other built-in errors are detailed in `RpcError`.
## Examples
- [Facelandmark](https://github.com/livekit/python-sdks/tree/main/examples/face_landmark): Use mediapipe to detect face landmarks (eyes, nose ...)
- [Basic room](https://github.com/livekit/python-sdks/blob/main/examples/basic_room.py): Connect to a room
- [Publish hue](https://github.com/livekit/python-sdks/blob/main/examples/publish_hue.py): Publish a rainbow video track
- [Publish wave](https://github.com/livekit/python-sdks/blob/main/examples/publish_wave.py): Publish a sine wave
## Getting help / Contributing
Please join us on [Slack](https://livekit.io/join-slack) to get help from our devs / community members. We welcome your contributions(PRs) and details can be discussed there.