The Tool Desk
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Choose speech-to-speech or a chained pipeline
The architecture determines how much of the voice interaction your application controls. OpenAI describes both a speech-to-speech approach and a chained voice pipeline; neither is a universal best choice. OpenAI’s voice-agent guide explains the options.
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| Architecture | Best fit | Tradeoff |
|---|---|---|
| Realtime speech-to-speech | Natural spoken turns, interruptions, and real-time tool use are priorities. | Less stage-by-stage control than a chained pipeline. |
| Chained voice pipeline | You need separate control over recognition text, agent output, or speech generation. | Your application orchestrates speech-to-text, the agent workflow, and text-to-speech as distinct stages. |
In a speech-to-speech design, audio understanding and spoken responses happen within a Realtime session. A chained design exposes intermediate text and lets you change or inspect stages independently. Those differences can guide your choice; they do not establish a guaranteed latency, accuracy, or support outcome.
How do I build a speech-to-speech voice agent in a browser?
For a browser-based agent, OpenAI’s Realtime API setup uses an application server to create an ephemeral client secret. The browser connects with that temporary credential over WebRTC or WebSocket. Do not put a long-lived API credential in browser code. See Getting started with the Realtime API for the connection setup.
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Choose the browser transport
| Transport | What it offers | What your team must consider |
|---|---|---|
| WebRTC | The Agents SDK describes it as the simpler browser route, with audio handling managed for you. | Decide carefully which tools and data are available in the browser session. |
| WebSocket | More direct control over the connection and events. | Your application is responsible for audio capture and playback. |
The Agents SDK notes that tools run where the RealtimeSession runs. If the session runs in the browser, its function tools also run there. Keep sensitive business logic and access to customer records behind an appropriate server boundary; do not assume that choosing a transport automatically secures those operations. The SDK’s voice-agent building guide describes the transport options and session behavior.
How do I connect a phone number to the Realtime API?
Telephone support needs a telephony connection, not just a browser audio session. OpenAI’s Telephony and SIP guide describes connecting a phone number to the Realtime API through SIP trunking and names Twilio as an example provider.
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A separate route uses Twilio Media Streams to send call audio to a WebSocket server. The OpenAI Agents SDK’s Twilio voice-agent extension guide describes this integration and marks its adapter beta. Treat that status as specific to the cited guide, and verify the current documentation and SDK status before depending on it for a launch.
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Evaluate the agent on real support scenarios
Use scripted, repeatable conversations that reflect the tasks your support team actually handles. OpenAI’s official evaluation guidance calls out task completion, audible response latency, interruptions, and unwanted silence; it does not set universal acceptance thresholds. Define thresholds for your own workflows rather than adopting an unsupported latency or success target. See the voice-agent guide.
- Routine requests: Check whether the agent completes representative support tasks.
- Interruptions: Speak over the agent and observe whether the interaction recovers appropriately.
- Changes of mind: Revise a request mid-conversation and check whether the agent follows the new direction.
- Human handoff: Include cases that should reach a human and verify the expected support path.
- Silence and response timing: Record audible response latency and unwanted pauses across repeated runs.
Run the same scenarios consistently and compare results across iterations. Keep browser and phone evaluations distinct, because their transport and timing behavior differ.
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