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Basic Information

Repository provides official Python SDKs for LiveKit, enabling developers to add realtime video, audio and data features to Python applications. It includes two packages: livekit for participant-side realtime SDK functionality and livekit-api for server-side APIs and access token generation. The SDKs support connecting to LiveKit Cloud or a self-hosted server and are intended to help build applications such as multi-modal AI, live streaming, and video calls. The README includes pip installation instructions, code snippets for generating access tokens and creating rooms, and demonstrates using an asyncio-based RoomService. It documents how to access services via a LiveKitAPI client and points to example scripts and ecosystem resources for further integration.

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App URL
https://github.com/livekit/python-sdks
Github Repository
https://github.com/livekit/python-sdks/blob/main/README.md

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App Details

Features
Provides a realtime participant SDK to connect to LiveKit rooms, subscribe to tracks, and receive video frames via a VideoStream abstraction. Includes a server API package for access token generation and server-side operations such as creating and listing rooms. Uses asyncio and aiohttp for asynchronous API calls. Exposes services through a LiveKitAPI object including room, egress, ingress, sip, and agent_dispatch. Supports RPC between participants with examples for registering RPC handlers, performing RPC calls, configuring response timeouts, and RpcError handling. Ships example programs like basic_room, face_landmark using mediapipe, publish_hue, and publish_wave. Installation is available via pip for both packages and the README shows event-driven callbacks for participant and track events.
Use Cases
Helps Python developers integrate realtime communications quickly by providing ready-made client and server libraries with clear examples. The server API simplifies token creation and room lifecycle management so backends can provision rooms and grants programmatically. The realtime SDK offers event hooks for participant and track events and an async programming model suitable for scalable applications. VideoStream and track subscriptions let developers process frames or forward media to other services. RPC support enables custom method calls between participants, useful for agent integrations or forwarding LLM function calls. Example scripts accelerate prototyping for common flows such as face landmark detection and synthetic track publishing, and the README links to community channels for support and contribution.

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