LLM Tracekit - Google ADK

OpenTelemetry instrumentation for Google ADK (Agent Development Kit), designed to simplify LLM application development and production tracing and debugging.

Installation

pip install "llm-tracekit-google-adk"

Usage

This section describes how to set up instrumentation for Google ADK.

Setting up tracing

You can use the setup_export_to_coralogix function to setup tracing and export traces to Coralogix

from llm_tracekit.google_adk import setup_export_to_coralogix

setup_export_to_coralogix(
    service_name="ai-service",
    application_name="ai-application",
    subsystem_name="ai-subsystem",
    capture_content=True,
)

Alternatively, you can set up tracing manually:

from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.resources import SERVICE_NAME, Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

tracer_provider = TracerProvider(
    resource=Resource.create({SERVICE_NAME: "ai-service"}),
)
exporter = OTLPSpanExporter()
span_processor = SimpleSpanProcessor(exporter)
tracer_provider.add_span_processor(span_processor)
trace.set_tracer_provider(tracer_provider)

Activation

To instrument all clients, call the instrument method

from llm_tracekit.google_adk import GoogleADKInstrumentor

GoogleADKInstrumentor().instrument()

Enabling message content

Message content such as the contents of the prompt, completion, function arguments and return values are not captured by default. To capture message content as span attributes, do one of the following:

• Pass capture_content=True when calling setup_export_to_coralogix
• Set the environment variable OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT to true

Most Coralogix AI evaluations will not work without message contents, so it is highly recommended to enable capturing.

Uninstrument

To uninstrument clients, call the uninstrument method:

GoogleADKInstrumentor().uninstrument()

Full Example

import asyncio
from google.adk import Agent, Runner
from google.adk.sessions import InMemorySessionService
from google.genai import types
from llm_tracekit.google_adk import GoogleADKInstrumentor, setup_export_to_coralogix

# Optional: Configure sending spans to Coralogix
# Reads Coralogix connection details from the following environment variables:
# - CX_TOKEN
# - CX_ENDPOINT
setup_export_to_coralogix(
    service_name="ai-service",
    application_name="ai-application",
    subsystem_name="ai-subsystem",
    capture_content=True,
)

# Activate instrumentation
GoogleADKInstrumentor().instrument()


async def main():
    agent = Agent(
        name="MyAgent",
        model="gemini-2.0-flash",
        instruction="You are a helpful assistant.",
    )

    session_service = InMemorySessionService()
    runner = Runner(agent=agent, app_name="my_app", session_service=session_service)

    session = await session_service.create_session(app_name="my_app", user_id="user_1")

    async for event in runner.run_async(
        user_id="user_1",
        session_id=session.id,
        new_message=types.Content(role="user", parts=[types.Part(text="Hello!")]),
    ):
        # print any streamed text chunks
        if event.content and event.content.parts:
            for part in event.content.parts:
                if part.text:
                    print(part.text, end="")


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

Semantic Conventions