openai/openai-realtime-agents — explained in plain English
Analysis updated 2026-06-24
Build a voice AI agent that answers common questions quickly and quietly consults a smarter model only when needed.
Create a multi-agent customer service system where each AI agent handles a specific topic and routes callers onward.
Prototype low-latency voice assistants with streaming spoken responses using the OpenAI Realtime API.
Learn how to implement agent handoffs so one AI passes a conversation seamlessly to a more specialized AI.
| openai/openai-realtime-agents | googleapis/release-please | zsviczian/obsidian-excalidraw-plugin | |
|---|---|---|---|
| Stars | 6,866 | 6,871 | 6,872 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | moderate | easy | easy |
| Complexity | 3/5 | 2/5 | 1/5 |
| Audience | developer | developer | writer |
Figures from each repo's GitHub metadata at analysis time.
Requires a paid OpenAI API key with Realtime API access enabled.
This repository is a demonstration app from OpenAI showing two patterns for building voice-based AI agents using their Realtime API. The Realtime API lets a program have a low-latency, streaming spoken conversation with an AI model rather than sending one text message at a time and waiting for a response. The first pattern, called Chat-Supervisor, uses two models working together. A faster, cheaper model handles the conversational side, greeting the user and collecting information through voice. When a question requires a tool call or more careful reasoning, the fast model quietly consults a smarter text model and then delivers that answer back to the user. The result is a voice agent that responds quickly in conversation while still getting high-quality answers on harder questions. The second pattern is called Sequential Handoff. Here, multiple specialized agents each have their own instructions and tools. When the user's request falls outside what the current agent handles, the agent passes the conversation to a more appropriate one. This mirrors how a customer service phone system routes callers to different departments, but the routing is decided by the model rather than by a rigid menu. The project is a Next.js web application, which is a common framework for building websites with TypeScript. You install dependencies, add an OpenAI API key, and run a local server. Opening a browser then shows the demo interface, where you can switch between the two agent configurations using a dropdown. The README includes diagrams explaining how each pattern works, guidance on adapting the code for your own agent, and notes on trading off cost versus response quality. The full README is longer than what was shown.
A demo app from OpenAI showing two patterns for building voice AI agents, one where a fast model and a smart model collaborate silently, and one where specialized agents hand off conversations to each other.
Mainly TypeScript. The stack also includes TypeScript, Next.js, OpenAI Realtime API.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.