> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/guardrails/llms.txt.
> For full documentation content, see https://docs.nvidia.com/nemo/guardrails/llms-full.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/guardrails/_mcp/server.

# nemoguardrails.eval.ui.common

## Module Contents

### Functions

| Name                                                                                                          | Description                                                               |
| ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------- |
| [`_get_compliance_df`](#nemoguardrails-eval-ui-common-_get_compliance_df)                                     | Computes a DataFrame with information about compliance.                   |
| [`_get_resource_usage_and_latencies_df`](#nemoguardrails-eval-ui-common-_get_resource_usage_and_latencies_df) | Computes a DataFrame with information about resource usage and latencies. |
| [`_render_compliance_data`](#nemoguardrails-eval-ui-common-_render_compliance_data)                           | -                                                                         |
| [`_render_resource_usage_and_latencies`](#nemoguardrails-eval-ui-common-_render_resource_usage_and_latencies) | Render the resource usage part.                                           |
| [`_render_sidebar`](#nemoguardrails-eval-ui-common-_render_sidebar)                                           | -                                                                         |
| [`render_summary`](#nemoguardrails-eval-ui-common-render_summary)                                             | Show a summary of the evaluation results.                                 |

### API

```python
nemoguardrails.eval.ui.common._get_compliance_df(
    output_names: typing.List[str],
    policy_options: typing.List[str],
    eval_data: nemoguardrails.eval.ui.utils.EvalData
) -> pandas.DataFrame
```

Computes a DataFrame with information about compliance.

Returns
DataFrame: \["Guardrail Config", "Policy", "Compliance Rate", "Violations Count", "Interaction Count"]

```python
nemoguardrails.eval.ui.common._get_resource_usage_and_latencies_df(
    output_names: typing.List[str],
    eval_data: nemoguardrails.eval.ui.utils.EvalData,
    eval_config: nemoguardrails.eval.models.EvalConfig,
    use_expected_latencies: bool = False
) -> typing.Tuple[pandas.DataFrame, pandas.DataFrame]
```

Computes a DataFrame with information about resource usage and latencies.

Returns
DataFrame: \["Metric", \*output\_names]

```python
nemoguardrails.eval.ui.common._render_compliance_data(
    output_names: typing.List[str],
    policy_options: typing.List[str],
    eval_data: nemoguardrails.eval.ui.utils.EvalData,
    short: bool = False
)
```

```python
nemoguardrails.eval.ui.common._render_resource_usage_and_latencies(
    output_names: typing.List[str],
    eval_data: nemoguardrails.eval.ui.utils.EvalData,
    eval_config: nemoguardrails.eval.models.EvalConfig,
    short: bool = False
)
```

Render the resource usage part.

```python
nemoguardrails.eval.ui.common._render_sidebar(
    output_names: typing.List[str],
    policy_options: typing.List[str],
    tags: typing.List[str]
)
```

```python
nemoguardrails.eval.ui.common.render_summary(
    short: bool = False
)
```

Show a summary of the evaluation results.