A new tutorial shows how to create a Multi‑Agent Travel Planning System in Python. The guide walks readers through setting up an OpenAI client via OpenRouter.ai, then defines four specialized agents—Research, Activity, Budget, and Final Assistant—to collaborate on itineraries.

The post details an OOP class for agents, passing role descriptions and user tasks to the gpt-4.1-mini model. Each agent receives a clear prompt: the Research agent gathers local attractions, the Activity agent schedules sights, the Budget agent calculates costs, and the Final Assistant merges outputs into a concise itinerary.

Developers can copy the sample code into PyCharm, install the OpenAI package, and replace the placeholder API key with their own. The example emphasizes modular design, letting teams add new agents or swap models without restructuring the whole system.

By illustrating how multiple AI agents can coordinate in a single project, the tutorial demonstrates a practical path from single‑model scripts to scalable, role‑based AI workflows in Python.