Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This is a simple demonstration of more advanced, agentic patterns built on top of the Realtime API.
| Date | Stars |
|---|---|
| 2026-07-31 | 6945 |
| 2026-08-02 | 6945 |
| 2026-08-05 | 6949 |
| 2026-08-06 | 6949 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Realtime API Agents Demo
This is a demonstration of more advanced patterns for voice agents, using the OpenAI Realtime API and the OpenAI Agents SDK.
## About the OpenAI Agents SDK
This project uses the [OpenAI Agents SDK](https://github.com/openai/openai-agents-js), a toolkit for building, managing, and deploying advanced AI agents. The SDK provides:
- A unified interface for defining agent behaviors and tool integrations.
- Built-in support for agent orchestration, state management, and event handling.
- Easy integration with the OpenAI Realtime API for low-latency, streaming interactions.
- Extensible patterns for multi-agent collaboration, handoffs, tool use, and guardrails.
For full documentation, guides, and API references, see the official [OpenAI Agents SDK Documentation](https://github.com/openai/openai-agents-js#readme).
**NOTE:** For a version that does not use the OpenAI Agents SDK, see the [branch without-agents-sdk](https://github.com/openai/openai-realtime-agents/tree/without-agents-sdk).
There are two main patterns demonstrated:
1. **Chat-Supervisor:** A realtime-based chat agent interacts with the user and handles basic tasks, while a more intelligent, text-based supervisor model (e.g., `gpt-4.1`) is used extensively for tool calls and more complex responses. This approach provides an easy onramp and high-quality answers, with a small increase in latency.
2. **Sequential Handoff:** Specialized agents (powered by realtime api) transfer the user between them to handle specific user intents. This is great for customer service, where user intents can be handled sequentially by specialist models that excel in a specific domains. This helps avoid the model having all instructions and tools in a single agent, which can degrade performance.
## Setup
- This is a Next.js typescript app. Install dependencies with `npm i`.
- Add your `OPENAI_API_KEY` to your env. Either add it to your `.bash_profile` or equivalent, or copy `.env.sample` to `.env` and add it there.
- Start the server with `npm run dev`
- Open your browser to [http://localhost:3000](http://localhost:3000). It should default to the `chatSupervisor` Agent Config.
- You can change examples via the "Scenario" dropdown in the top right.
# Agentic Pattern 1: Chat-Supervisor
This is demonstrated in the [chatSupervisor](src/app/agentConfigs/chatSupervisor/index.ts) Agent Config. The chat agent uses the realtime model to converse with the user and handle basic tasks, like greeting the user, casual conversation, and collecting information, and a more intelligent, text-based supervisor model (e.g. `gpt-4.1`) is used extensively to handle tool calls and more challenging responses. You can control the decision boundary by "opting in" specific tasks to the chat agent as desired.
Video walkthrough: [https://x.com/noahmacca/status/1927014156152058075](https://x.com/noahmacca/status/1927014156152058075)
## Example
*In this exchange, note the immediate response to collect the phone number, and the deferral to the supervisor agent to handle the tool call and formulate the response. There ~2s between the end of "give me a moment to check on that." being spoken aloud and the start of the "Thanks for waiting. Your last bill...".*
## Schematic
```mermaid
sequenceDiagram
participant User
participant ChatAgent as Chat Agent<br/>(gpt-4o-realtime-mini)
participant Supervisor as Supervisor Agent<br/>(gpt-4.1)
participant Tool as Tool
alt Basic chat or info collection
User->>ChatAgent: User message
ChatAgent->>User: Responds directly
else Requires higher intelligence and/or tool call
User->>ChatAgent: User message
ChatAgent->>User: "Let me think"
ChatAgent->>Supervisor: Forwards message/context
alt Tool call needed
Supervisor->>Tool: Calls tool
Tool->>Supervisor: Returns result
end
Excerpt of 15,347 characters
Read on GitHub
29
Brian Fioca
3
3
3
Dominik Kundel
2
2
Kazuhiro Sera · OpenAI · Japan
1
1
1
Danial Mirza
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b13681b69c0fcc26, desc:agentic