Orchestrating Deterministic Tool Execution

Function Calling empowers Gemini to act as an intelligent orchestrator. The model does not execute foreign code inside its own sandbox; instead, it outputs structured call signatures with typed parameters that your application executes securely.

from google import genai
from google.genai import types

def get_exchange_rate(base_currency: str, target_currency: str) -> dict:
    """Retrieves real-time foreign currency exchange rates."""
    rates = {"USD:GBP": 0.78, "GBP:USD": 1.28, "EUR:GBP": 0.85}
    key = f"{base_currency}:{target_currency}"
    return {"pair": key, "rate": rates.get(key, 1.0)}

client = genai.Client()

# Pass native Python functions directly to tools
response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents="Convert 5,000 GBP to USD at current rates.",
    config=types.GenerateContentConfig(
        tools=[get_exchange_rate],
        tool_config=types.ToolConfig(
            function_calling_config=types.FunctionCallingConfig(
                mode=types.FunctionCallingConfigMode.AUTO
            )
        )
    )
)

# Handle tool call and return response
if response.function_calls:
    call = response.function_calls[0]
    print(f"Invoking {call.name} with args: {call.args}")