Google Gen AI Tracing

Instrument LLM calls made using the Google Gen AI Python SDK

Launch Phoenix

Sign up for Phoenix:

  1. Sign up for an Arize Phoenix account at https://app.phoenix.arize.com/login

  2. Click Create Space, then follow the prompts to create and launch your space.

Install packages:

pip install arize-phoenix-otel

Set your Phoenix endpoint and API Key:

From your new Phoenix Space

  1. Create your API key from the Settings page

  2. Copy your Hostname from the Settings page

  3. In your code, set your endpoint and API key:

import os

os.environ["PHOENIX_API_KEY"] = "ADD YOUR PHOENIX API KEY"
os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "ADD YOUR PHOENIX HOSTNAME"

# If you created your Phoenix Cloud instance before June 24th, 2025,
# you also need to set the API key as a header:
# os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={os.getenv('PHOENIX_API_KEY')}"

Having trouble finding your endpoint? Check out Finding your Phoenix Endpoint

Install

pip install openinference-instrumentation-google-genai google-genai

Setup

Set the GEMINI_API_KEY environment variable. To use the Gen AI SDK with Vertex AI instead of the Developer API, refer to Google's guide on setting the required environment variables.

export GEMINI_API_KEY=[your_key_here]

Use the register function to connect your application to Phoenix.

from phoenix.otel import register

# Configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)

Observe

Now that you have tracing setup, all Gen AI SDK requests will be streamed to Phoenix for observability and evaluation.

import os
from google import genai

def send_message_multi_turn() -> tuple[str, str]:
    client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
    chat = client.chats.create(model="gemini-2.0-flash-001")
    response1 = chat.send_message("What is the capital of France?")
    response2 = chat.send_message("Why is the sky blue?")

    return response1.text or "", response2.text or ""

This instrumentation will support tool calling soon. Refer to this page for the status.

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