Building Multi-Agent Conversations with WebRTC & LiveKit

From Simple Bots to Dynamic Conversations We've all seen the basic voice AI demos – ask a question, get an answer. But real-world interactions often involve multiple stages, different roles, or specialized knowledge. How do you build a voice AI system that can gracefully handle introductions, gather information, perform a core task, and then provide a conclusion, potentially using different AI "personalities" or models along the way? Chaining traditional REST API calls for STT, LLM, and TTS already introduces latency and state management headaches for a single agent turn. Trying to orchestrate multiple logical agents or conversational stages this way becomes exponentially more complex, laggy, and brittle. This article explores a powerful solution: building multi-agent voice AI sessions using WebRTC for real-time communication and the LiveKit Agents framework for orchestration. We'll look at a practical Python example of a "storyteller" agent that first gathers user info and then hands off to a specialized story-generating agent, all within a single, low-latency voice call. Why Does the Standard API Approach Fall Short (Especially for Multi-Agent)? The typical STT → LLM → TTS cycle via separate API calls suffers from:

Apr 10, 2025 - 14:16

Building Multi-Agent Conversations with WebRTC & LiveKit

From Simple Bots to Dynamic Conversations

We've all seen the basic voice AI demos – ask a question, get an answer. But real-world interactions often involve multiple stages, different roles, or specialized knowledge. How do you build a voice AI system that can gracefully handle introductions, gather information, perform a core task, and then provide a conclusion, potentially using different AI "personalities" or models along the way?

Chaining traditional REST API calls for STT, LLM, and TTS already introduces latency and state management headaches for a single agent turn. Trying to orchestrate multiple logical agents or conversational stages this way becomes exponentially more complex, laggy, and brittle.

This article explores a powerful solution: building multi-agent voice AI sessions using WebRTC for real-time communication and the LiveKit Agents framework for orchestration. We'll look at a practical Python example of a "storyteller" agent that first gathers user info and then hands off to a specialized story-generating agent, all within a single, low-latency voice call.

Why Does the Standard API Approach Fall Short (Especially for Multi-Agent)?

The typical STT → LLM → TTS cycle via separate API calls suffers from: