The best open source frameworks for building realtime voice and video AI agents

LiveKit Agents and Pipecat are presented as the leading open-source frameworks for production voice and video AI agents, both supporting standard speech-to-text, language-model, and text-to-speech workflows while differing primarily in abstraction level and infrastructure assumptions. LiveKit Agents is tightly integrated with LiveKit’s open-source WebRTC and SIP stack, providing prewired sessions, turn handling, scaling, telephony, observability, multi-platform SDKs, and managed cloud options, making it suited to teams prioritizing rapid deployment, enterprise compliance, and global production operations. Pipecat is a Python-only, transport-agnostic framework that exposes an explicit, customizable pipeline, giving developers greater flexibility to add, reorder, fork, or build non-conversational audio and video processing flows, but requiring them to manage more media, transport, pipeline, and provider complexity. The comparison notes that both projects are actively maintained and have meaningful adoption, while alternatives such as TEN Framework, Dograh, Vision Agents, and Vocode serve narrower roles or face licensing, platform-dependency, or maintenance limitations. The recommended choice depends on whether teams need a managed, opinionated agent platform with integrated infrastructure, where LiveKit is generally favored, or a highly configurable pipeline architecture for research, unusual media workflows, direct carrier audio handling, or parallel processing, where Pipecat may be more appropriate.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.