> ## Documentation Index
> Fetch the complete documentation index at: https://docs.aevyra.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# EvalResults

> API reference for EvalResults and ModelResult.

## EvalResults

Returned by `EvalRunner.run()`. Contains per-model results and aggregate comparisons.

```python theme={null}
results = runner.run(dataset)
```

### `.compare(metric_name=None)`

Return a formatted comparison table as a string. Uses the first metric if none specified.

```python theme={null}
print(results.compare())
print(results.compare("rouge_rougeL"))
print(results.compare("llm_judge"))
```

### `.summary()`

Return a dict of per-model aggregate stats (mean score, stdev, latency, token usage).

```python theme={null}
summary = results.summary()
# {
#   "openai/gpt-5.4-nano": {
#     "provider": "openai",
#     "model": "gpt-5.4-nano",
#     "success_rate": 1.0,
#     "mean_latency_ms": 312.4,
#     "total_tokens": 4821,
#     "rouge_rougeL_mean": 0.782,
#     "rouge_rougeL_stdev": 0.134,
#   },
#   ...
# }
```

### `.to_dataframe()`

Convert the summary to a pandas DataFrame for further analysis.

```python theme={null}
df = results.to_dataframe()
print(df.sort_values("rouge_rougeL_mean", ascending=False))
```

### `.to_json(path=None)`

Export full results (summary + per-sample data) as JSON. Returns the JSON string.

```python theme={null}
results.to_json("results.json")
json_str = results.to_json()
```

### Properties

| Property                | Description                            |
| ----------------------- | -------------------------------------- |
| `results.models`        | List of model labels.                  |
| `results.metric_names`  | List of metric names used in this run. |
| `results.model_results` | Dict mapping label → `ModelResult`.    |

***

## ModelResult

Per-model results accessible via `results.model_results["label"]`.

| Method                       | Description                                 |
| ---------------------------- | ------------------------------------------- |
| `.mean_score(metric_name)`   | Mean score for a metric across all samples. |
| `.median_score(metric_name)` | Median score.                               |
| `.stdev_score(metric_name)`  | Standard deviation.                         |
| `.mean_latency_ms()`         | Mean API latency in milliseconds.           |
| `.total_tokens()`            | Total tokens used across all completions.   |

| Property        | Description                                                  |
| --------------- | ------------------------------------------------------------ |
| `.num_samples`  | Total samples evaluated.                                     |
| `.num_errors`   | Samples that failed after all retries.                       |
| `.success_rate` | Fraction of samples that completed without error.            |
| `.completions`  | List of `CompletionResult` objects (one per sample).         |
| `.scores`       | List of `{metric_name: ScoreResult}` dicts (one per sample). |
| `.errors`       | List of error strings or `None` (one per sample).            |