## List

`agents.evaluation_metrics.list()  -> EvaluationMetricListResponse`

**get** `/v2/gen-ai/evaluation_metrics`

To list all evaluation metrics, send a GET request to `/v2/gen-ai/evaluation_metrics`.

### Returns

- `class EvaluationMetricListResponse`

  - **metrics:** `Optional[List[APIEvaluationMetric]]`

    - **description:** `Optional[str]`

    - **inverted:** `Optional[bool]`

      If true, the metric is inverted, meaning that a lower value is better.

    - **metric\_name:** `Optional[str]`

    - **metric\_type:** `Optional[Literal["METRIC_TYPE_UNSPECIFIED", "METRIC_TYPE_GENERAL_QUALITY", "METRIC_TYPE_RAG_AND_TOOL"]]`

      - `"METRIC_TYPE_UNSPECIFIED"`

      - `"METRIC_TYPE_GENERAL_QUALITY"`

      - `"METRIC_TYPE_RAG_AND_TOOL"`

    - **metric\_uuid:** `Optional[str]`

    - **metric\_value\_type:** `Optional[Literal["METRIC_VALUE_TYPE_UNSPECIFIED", "METRIC_VALUE_TYPE_NUMBER", "METRIC_VALUE_TYPE_STRING", "METRIC_VALUE_TYPE_PERCENTAGE"]]`

      - `"METRIC_VALUE_TYPE_UNSPECIFIED"`

      - `"METRIC_VALUE_TYPE_NUMBER"`

      - `"METRIC_VALUE_TYPE_STRING"`

      - `"METRIC_VALUE_TYPE_PERCENTAGE"`

    - **range\_max:** `Optional[float]`

      The maximum value for the metric.

    - **range\_min:** `Optional[float]`

      The minimum value for the metric.

### Example

```python
from do_gradientai import GradientAI

client = GradientAI()
evaluation_metrics = client.agents.evaluation_metrics.list()
print(evaluation_metrics.metrics)
```