> ## 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 Evals

### Using Google Gen AI with Phoenix Evals

<Note>
Need to install the extra dependency `google-genai>=1.0.0`
</Note>

Use the `LLM` wrapper with `provider="google"` to access Google's Gemini models through the Google GenAI SDK.

**Authentication Options**

**Option 1: Using API Key (Developer API)**

Set the `GOOGLE_API_KEY` or `GEMINI_API_KEY` environment variable:

```bash
export GOOGLE_API_KEY=your_api_key_here
```

```python
from phoenix.evals import LLM

llm = LLM(provider="google", model="gemini-2.5-flash")
```

**Option 2: Using VertexAI**

```python
from phoenix.evals import LLM

llm = LLM(
    provider="google",
    model="gemini-2.5-flash",
    vertexai=True,
    project="your-project-id",
    location="us-central1",
)
```

**Basic Usage**

```python
from phoenix.evals import LLM
from phoenix.evals.metrics import FaithfulnessEvaluator

llm = LLM(provider="google", model="gemini-2.5-flash")

evaluator = FaithfulnessEvaluator(llm=llm)
result = evaluator.evaluate(eval_input={
    "input": "What is the capital of France?",
    "output": "Paris is the capital of France.",
    "context": "Paris is the capital and largest city of France.",
})
result[0].pretty_print()
```

**Supported Models**

The Google provider supports all Gemini models available through the Google GenAI SDK, including:

* `gemini-2.5-flash` (default)
* `gemini-2.5-flash-001`
* `gemini-2.0-flash-001`
* `gemini-1.5-pro`
* `gemini-1.5-flash`

<Note>
We acknowledge [Siddharth Sahu](https://github.com/sahusiddharth) for this valuable contribution and support.
</Note>