# Arize AX observability for ADK

[Arize AX](https://arize.com/products/ax/) is the full-featured AI observability and evaluation platform from [Arize AI](https://arize.com/?utm_source=google-adk-docs&utm_medium=partner&utm_campaign=partner-docs&utm_content=integrations-arize-ax) for production teams, AI-native companies, and enterprises. It is available as managed cloud or enterprise self-hosted deployment and provides comprehensive tracing, evaluation, and monitoring capabilities for Google ADK applications. To get started, sign up for a [free account](https://app.arize.com/auth/join).

For an open-source path for local development, experimentation, or single-container self-hosting, check out [Arize Phoenix](https://arize.com/phoenix/). Arize's [agent evaluation guide](https://arize.com/ai-agents/agent-evaluation) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/) show how teams use traces to evaluate agent decisions, tool calls, and model behavior.

## Overview

Arize AX can automatically collect traces from Google ADK using [OpenInference instrumentation](https://github.com/Arize-ai/openinference/tree/main/python/instrumentation/openinference-instrumentation-google-adk), allowing you to:

- **Trace agent interactions** - Automatically capture every agent run, tool call, model request, and response with context and metadata
- **Evaluate performance** - Assess agent behavior using custom or pre-built evaluators and run experiments to test agent configurations
- **Monitor in production** - Set up real-time dashboards and alerts to track performance
- **Debug issues** - Analyze detailed traces to quickly identify bottlenecks, failed tool calls, and any unexpected agent behavior

## Installation

Install the required packages:

```bash
pip install openinference-instrumentation-google-adk google-adk arize-otel
```

## Setup

### 1. Configure Environment Variables

Set your Google API key:

```bash
export GOOGLE_API_KEY=[your_key_here]
```

### 2. Connect your application to Arize AX

```python
from arize.otel import register

# Register with Arize AX
tracer_provider = register(
    space_id="your-space-id",      # Found in app space settings page
    api_key="your-api-key",        # Found in app space settings page
    project_name="your-project-name"  # Name this whatever you prefer
)

# Import and configure the automatic instrumentor from OpenInference
from openinference.instrumentation.google_adk import GoogleADKInstrumentor

# Finish automatic instrumentation
GoogleADKInstrumentor().instrument(tracer_provider=tracer_provider)
```

## Observe

Now that you have tracing setup, all Google ADK SDK requests will be streamed to Arize AX for observability and evaluation.

```python
import nest_asyncio
nest_asyncio.apply()

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

# Define a tool function
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.",
        }

# Create an agent with tools
agent = Agent(
    name="weather_agent",
    model="gemini-flash-latest",
    description="Agent to answer questions using weather tools.",
    instruction="You must use the available tools to find an answer.",
    tools=[get_weather]
)

app_name = "weather_app"
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
)

# Run the agent (all interactions will be traced)
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())
```

## View Results in Arize AX

## Support and Resources

- [Arize AX Documentation](https://arize.com/docs/ax/integrations/python-agent-frameworks/google-adk)
- [Arize Community Slack](https://arize-ai.slack.com/join/shared_invite/zt-11t1vbu4x-xkBIHmOREQnYnYDH1GDfCg#/shared-invite/email)
- [OpenInference Package](https://github.com/Arize-ai/openinference/tree/main/python/instrumentation/openinference-instrumentation-google-adk)