Google ADK Integration¶

Install the ADK extra and initialize Taimoe before constructing an Agent:

pip install "taimoe-platform[adk]"

from google.adk.agents import LlmAgent
from taimoe.platform import init, taimoe

init(
    platform_url="https://platform.example.com",
    api_key="...",
    runtime_name="support-prod",
    framework="google-adk",
)

handle = taimoe.agent("support")
tool_registry = {"search_orders": search_orders}

agent = LlmAgent(
    name="support",
    model=handle.model,
    instruction=handle.instruction,
    tools=[tool_registry[name] for name in handle.tools],
    before_agent_callback=handle.refresh_callback,
)

Live configuration behavior¶

Field	Behavior
`instruction`	Callable instruction provider; ADK resolves it on every model call.
`model`	Snapshot at construction; the refresh callback updates it later.
`tools`	Names or IDs, not ADK tool objects; resolve them in application code.
`generation_config`	Dictionary of configured values; absent keys mean provider defaults.
`refresh_callback`	Refreshes model, tools, and generation settings before execution.

Hard-coded Agent fields remain owned by application code. Taimoe only governs fields that the application reads from the handle.

Automatic instrumentation¶

init(instrument=None) instruments ADK only when google.adk has already been imported. Pass instrument=True to force patching or False to disable it. Instrumentation routes supported ADK Gemini calls through the Taimoe Gateway and emits model/tool telemetry. Patching is process-wide and idempotent.

Tool resolution boundary¶

The Platform currently synchronizes tool identifiers, not executable Python objects. Keep the identifier-to-object registry in application code. This preserves the deployment’s code and credential boundary while allowing the Platform to select from approved tools.