OpenAI Customer Service AI Agent

A While back OpenAI dropped a GitHub repo with a slick demo of an AI-powered Customer Service Agent interface.

In Short

This GitHub repo showcases an airline customer service AI Agent built on OpenAI’s Agents SDK.

It features five AI Agents collaborating, led by a Triage Agent that delegates tasks to four specialised sub-agents.

Built-in guardrails prevent off-topic chats and jailbreaks.

Handles conversation context and memory for seamless interactions.

What is OpenAI’s goal? A blueprint for devs to build robust AI apps with their SDK.

The Agent view has a pane with with the agents which are available, the guardrails and the context which is being managed. At the bottom is the conversational logs. Obviously on the right of the screen is the conversational UI, or the customer view. So think of left as the organisational view, and the right as the customer facing portion.

Introduction

OpenAI’s repo is a hands-on showcase of how AI Agents can revolutionise customer service — starting with airlines.

In this post, I’ll break down the demo’s setup, standout features and why it’s a must-see for anyone eyeing agentic AI in service sectors.

What’s in the Repo?

This OpenAI-built demo simulates real-world airline support, tackling everything from seat swaps to flight cancellations. It’s split into two clean components…

Python Backend

Powers the agent orchestration using the Agents SDK’s customer service blueprint.

Next.js Frontend

Delivers a visual chat UI to track agent flows in real-time.

It’s a prime example of agentic AI in action — autonomous systems that collaborate to solve user queries efficiently.

Here the conversation has unfolded as you can see on the right, and the runner output or logs are on the left.

Key Features

At its core, this demo rocks a conversational web UI that’s intuitive and secure.

Guardrails keep things on rails (pun intended), filtering out irrelevant tangents or risky prompts.

The OpenAI Agents SDK — evolved from the Swarm framework — keeps it lightweight, with minimal abstractions for quick prototyping and production scaling.

Triage Agent as Conductor

It analyses user input, routes it to the right sub-agent, for bookings or FAQs etc. and oversees the handoff.

Real-Time Agent Tracking

The UI highlights the active AI Agent under the Available Agents section — super handy for debugging.

Dual Guardrails

One for relevance, another for security — ensuring chats stay helpful and safe.

Context Management ( Memory)

Retains conversation history for natural, ongoing dialogues.

These elements make it reliable for complex workflows, with built-in tracing to log every step for easy monitoring.

A Real-World Walkthrough

Imagine a frustrated flyer wants to switch seats on their early morning flight...

They type their request into the web UI.

1. The Triage Agent kicks in, verifies identity via a mock database tool.

2. It hands off to the Seat Change Agent, which scans availability and confirms the swap.

3. Guardrails double-check, Is this on-topic? Any sensitive data leaks

4. Tracing logs the whole flow, so devs can tweak as needed.

The demo includes pre-built flows for

cancellations,

status checks, and

FAQs — proving how one system can juggle diverse tasks.

It’s scalable too, thanks to seamless agent handoffs, aligning perfectly with the all the interest around AI in customer ops.

Getting It Running

I fired this up on macOS Terminal — straightforward.

Here’s the step-by-step…

Set Up a Virtual Environment

python3 -m venv agent
 source agent/bin/activate

Clone the Repo

git clone https://github.com/openai/openai-cs-agents-demo

Backend Dependencies

cd python-backend
 pip install -r requirements.txt

Frontend Setup

cd ../ui
 npm install 

API Key Config (in both tabs):

export OPENAI_API_KEY=your_api_key_here
echo $OPENAI_API_KEY # Verify it echoes back

Open two Terminal tabs — one for backend, one for frontend.

Spin Up the Backend From python-backend/:

python -m uvicorn api:app --reload --port 8000

Backend lives at http://localhost:8000*

Launch the Frontend

From ui/`:

npm run dev

Frontend awaits at

http://localhost:3000

This demo isn’t just a code project— it’s a roadmap for AI-driven service.

As AI Agent tech matures, expect more industries to adopt these multi-agent setups for smarter, faster support. Fork it, tweak it, and build your own.

Chief Evangelist @ Kore.ai | I’m passionate about exploring the intersection of AI and language. Language Models, AI Agents, Agentic Apps, Dev Frameworks & Data-Driven Tools shaping tomorrow.

GitHub - openai/openai-cs-agents-demo: Demo of a customer service use case implemented with the…
Demo of a customer service use case implemented with the OpenAI Agents SDK - openai/openai-cs-agents-demogithub.com

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COBUS GREYLING
Where AI Meets Language | Language Models, AI Agents, Agentic Applications, Development Frameworks & Data-Centric…www.cobusgreyling.com

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