> ## Documentation Index
> Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# MLflow

> Use Phoenix evaluators as MLflow scorers for GenAI evaluation workflows.

[MLflow](https://mlflow.org/) includes built-in support for Phoenix evaluators through its third-party scorer interface. This allows Phoenix users to run their existing evaluation metrics within MLflow's `mlflow.genai.evaluate()` pipeline alongside experiment tracking and model management.

## Using Phoenix Evaluators in MLflow

Phoenix evaluators such as `Hallucination`, `QACorrectness`, and `Toxicity` can be used directly as MLflow scorers:

```python theme={null}
from mlflow.genai.scorers.phoenix import Hallucination, QACorrectness

import mlflow

results = mlflow.genai.evaluate(
    data=eval_dataset,
    scorers=[
        Hallucination(model="openai:/gpt-4o"),
        QACorrectness(model="openai:/gpt-4o"),
    ],
)
```

For details on available scorers and configuration, see the [MLflow Phoenix integration docs](https://mlflow.org/docs/latest/genai/eval-monitor/scorers/third-party/phoenix.html).