Part 2: Setting Up APIs for Function Calling

For our Gemini agent to perform actions in the real world (like checking a calendar), it needs a set of well-defined tools. These tools are our backend APIs. We will use Spring Boot to create a simple, secure, and scalable backend.

Defining the Tool Specification

The core of function calling is providing the AI model with a clear "schema" of the functions it can invoke. This includes the function name, a description of what it does, and the parameters it accepts.

We will create two main endpoints:

• GET /api/appointments/available-slots: Checks for open appointment times on a given date.
• POST /api/appointments/book: Books an appointment for a specific date and time slot.

Spring Boot Implementation Example

Here is a simplified example of what the controller for available slots might look like:

@RestController
@RequestMapping("/api/appointments")
public class AppointmentController {

    @GetMapping("/available-slots")
    public ResponseEntity<List<String>> getAvailableSlots(@RequestParam String date) {
        // In a real application, you would query a database.
        // For this example, we return a mock list.
        System.out.println("Checking availability for: " + date);
        List<String> slots = List.of("10:00 AM", "2:00 PM", "4:00 PM");
        return ResponseEntity.ok(slots);
    }
}