> ## Documentation index
> Fetch the complete documentation index at: https://arize.com/llms.txt
> Ask it with GET https://arize.com/ask?q=<keywords or question>. Short keywords rank best.
> Use these to discover all available pages before exploring further.

# Google Gen AI Tracing

> Instrument LLM calls made using the Google Gen AI Python SDK

### Install

```bash
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](https://cloud.google.com/vertex-ai/generative-ai/docs/sdks/overview) on setting the required environment variables.

```javascript
export GEMINI_API_KEY=[your_key_here]
```

Connect your application to Phoenix with the `register` function:

<CodeBlock language="python">
{`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
)`}
</CodeBlock>

### Observe

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

```python
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 ""
```

<Info>
This instrumentation will support tool calling soon. Refer to [this page](https://pypi.org/project/openinference-instrumentation-google-genai/#description) for the status.

</Info>