Architecting Full-Duplex Multimodal Voice Agents with Gemini Live
How to design ultra-low latency bi-directional audio streams, client-side tool execution, and interruption handling using WebSockets and AudioWorklet.
Real-time voice AI requires moving away from traditional turn-based Request/Response cycles. When building with Google Gemini Live API, we encounter three core engineering challenges:
1. Zero-Copy Audio Streaming with AudioWorklet
Running audio sampling on the browser’s main JavaScript thread leads to dropped frames and choppy audio whenever UI layouts recalculate. By shifting the raw PCM 16-bit / 24kHz buffer capturing to a dedicated AudioWorkletNode, audio ingestion remains uninterrupted.
2. Managing BidiStream Asynchrony
Gemini Live uses WebSocket binary framing. Audio input packets stream continuously to the model, while the model emits response chunks as they become available. Interruption detection allows the user to speak mid-sentence, causing the client to immediately flush its playback buffer and instruct the server to truncate its output.
3. Dynamic Tool Calling without Audio Jitter
When the model decides to invoke a tool, we intercept the function declaration payload, execute the query against local cache or APIs, and reply with the function response payload in under 200ms.
Intergenerational Peer Dialogue (3)
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