A customer service agent built in Foundry needs to tell customers the real-time status of their flight, including delays that change minute to minute. The model itself has no built-in access to live flight data. Which approach lets the agent provide accurate, current flight status?

The correct approach is defining a function, also called a tool, that calls the airline's live flight-status application programming interface and letting the model invoke that tool during a conversation to retrieve current data. This gives the agent a way to fetch genuinely current data at the moment it is needed, which is exactly what a fast-changing value like flight status requires. The temperature-setting approach is incorrect because temperature controls how random or varied the model's word choices are; it has no connection to whether the model has access to real, current data, and increasing it could make responses less accurate, not more. The system-message approach is incorrect because the system message is fixed text set at deployment time; flight status changes minute to minute, so anything written into it would be stale almost immediately and could not be refreshed on every request. The fine-tuning-on-historical-delay-records approach is incorrect because fine-tuning bakes patterns from historical data into the model's weights, producing a model that can talk about past trends but cannot know today's actual delay for a specific flight, which is the opposite of what is needed here. Tool calling is the mechanism built for exactly this situation, connecting a language model to a live, authoritative external source rather than trying to make the model itself the source of fast-changing facts.