Build a production voice agent with LiveKit and AssemblyAI

A technical tutorial explains how to build and deploy a browser-ready, real-time AI voice agent by combining LiveKit for WebRTC transport and agent orchestration with AssemblyAI for streaming speech recognition, LLM access, and text-to-speech through a single API key. It presents a roughly 100-line Python implementation that supports turn detection, interruption handling, tool calling, multi-user LiveKit rooms, conversational context, and an order-lookup example, while outlining local console testing and deployment to LiveKit Cloud or self-hosted infrastructure. The guide details configuration of Universal-3.6 Pro Realtime for transcription, the OpenAI-compatible LLM Gateway, and assemblyai-tts-1 for streamed speech, including options for voice selection, multilingual output, domain-specific terms, noisy environments, latency-versus-accuracy tradeoffs, and EU data residency. It also discusses scaling workers across concurrent rooms, handling multiple participants, common setup problems, integrations with external LLMs, pricing, and the broader design rationale of separating real-time media transport from AI model services.

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