What is Seat Booking Agent

The seat-booking-agent is an experimental implementation designed to facilitate self-service airline seat reservations using OpenAI Agents SDK, Autogen memory, and MCP tools support.

Use cases

Use cases include self-service airline seat reservation kiosks, enhancing customer support in flight booking processes, and providing assistance with inquiries related to flights, planes, and onboarding.

How to use

To use the seat-booking-agent, set up a Python virtual environment, install the required dependencies, and run the application using Chainlit with the command ‘chainlit run app.py’.

Key features

Key features include a triage agent for handling general inquiries, routing questions to specialized agents, retrieving user preferences, utilizing MCP server for web content fetching, and a web chat interface for user self-service.

Where to use

The seat-booking-agent is primarily used in the airline industry, specifically in self-service kiosks for seat reservations and customer support.

Experimental Seat Booking Agent

Experimental seat booking agent implementation combines OpenAI Agents SDK, Autogen extensions, and MCP tools support.

Use Case

The self-service airline seat reservation kiosk, also known as a flight seat booking service agent or passenger service agent, is designed to provide comprehensive customer support and assistance. This kiosk ensures a smooth and positive travel experience by handling various tasks, including reservations, through its call center interface.

Key Features:

• Triage agent answer user general inquiry with tools
• Triage agent should route customer question to specialized agents
• Triage agent retrieve user preferences on seating, airlines and food
• Triage agent use agents as tools on question routing
• Triage agent use MCP server as tools to perform web fetch content and read files system
• QA agent has knownledge to handling questions about Plane, Flight and Onboarding
• Seat booking agent specifilized on plane seat reservation tasks
• Web Chat interface for user self-service

Lab Technical Stack

• Linux
• OpenAI Agents SDK
• Autogen 0.4 + extensions (MCP Tools,OpenAI, Ollama)
• Chainlit (UI)
• Ollama (local Qwen2,5)

Environment

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Running

chainlit run app.py

Todos

• save seat history at the end of the booking
• improve FAQ agent to use RAG on actual documents
• improve memory storage
• add MCP tools to invoke actual booking service api
• more to came…

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

Important: Please keep your pull requests small and focused. This will make it easier to review and merge.

Feature Requests

If you have a feature request, please open an issue and make sure it is tagged with enhancement.

License

This project is licensed under the MIT License - see the LICENSE file for details.