traceAI-google-adk 0.1.0

OpenTelemetry instrumentation for Anthropic

TraceAI Google ADK Instrumentation

Python auto-instrumentation library for Google ADK.

Quickstart

In this example we will instrument a small program that uses Gemini and observe the traces in Future AGI Dashboard

Install packages.

pip install traceai-google-adk

In a python file, set up the GoogleADKInstrumentor and configure the tracer to send traces to Observe.

import asyncio

from google.adk.agents import Agent
from google.adk.runners import InMemoryRunner
from google.genai import types

from traceai_google_adk import GoogleADKInstrumentor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType

tracer_provider = register(
    project_name="test_project",
    project_type=ProjectType.OBSERVE,
)



GoogleADKInstrumentor().instrument(tracer_provider=tracer_provider)

def get_weather(city: str) -> dict:
    """Retrieves the current weather report for a specified city.

    Args:
        city (str): The name of the city for which to retrieve the weather report.

    Returns:
        dict: status and result or error msg.
    """
    if city.lower() == "new york":
        return {
            "status": "success",
            "report": (
                "The weather in New York is sunny with a temperature of 25 degrees"
                " Celsius (77 degrees Fahrenheit)."
            ),
        }
    else:
        return {
            "status": "error",
            "error_message": f"Weather information for '{city}' is not available.",
        }

agent = Agent(
   name="test_agent",
   model="gemini-2.5-flash-preview-05-20",
   description="Agent to answer questions using tools.",
   instruction="You must use the available tools to find an answer.",
   tools=[get_weather]
)

async def main():
    app_name = "test_instrumentation"
    user_id = "test_user"
    session_id = "test_session"
    runner = InMemoryRunner(agent=agent, app_name=app_name)
    session_service = runner.session_service
    await session_service.create_session(
        app_name=app_name,
        user_id=user_id,
        session_id=session_id
    )
    async for event in runner.run_async(
        user_id=user_id,
        session_id=session_id,
        new_message=types.Content(role="user", parts=[
            types.Part(text="What is the weather in New York?")]
        )
    ):
        if event.is_final_response():
            print(event.content.parts[0].text.strip())

if __name__ == "__main__":
    asyncio.run(main())

Since we are using Gemini, we must set the GOOGLE_API_KEY environment variable to authenticate with the Gemini API.

export GOOGLE_API_KEY=your-api-key

Run the python file to send the traces to Future AGI Platform.

python your_file.py