Building low-latency audio pipelines with the OpenAI Realtime API lets developers launch human-like conversational voice agents in production. Traditionally, building a voice interface meant chaining three separate model layers: automatic speech recognition (ASR), a text-based LLM logic layer, and text-to-speech (TTS) synthesis. That multi-step pipeline introduced significant round-trip network delays, making natural conversation impossible. Native audio processing over a persistent WebSocket connection changes this, reducing network latency below 300 milliseconds. This guide explains how to establish connection states, stream raw audio buffers, and optimise session configurations.
API Security Warning: Never expose your OpenAI API key directly inside client-side browser scripts. Always proxy the WebSocket connection through a secure edge middleware (such as a Cloudflare Worker) that appends authorisation headers before forwarding packets to OpenAI.
Key Takeaways:
WebSocket Connection: Connect directly to OpenAI's realtime WebSocket gateway using edge proxies.
Native Modalities: Specify both text and audio in your initial session update config payload.
