> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# AccuracyEval

> AccuracyEval parameters, run methods, and AccuracyResult fields.

`AccuracyEval` runs an agent or team against an input, then scores the response against an expected output with an evaluator agent on a 1-10 scale.

```python theme={null}
from agno.eval import AccuracyEval, AccuracyResult
```

## Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| `input` | `Union[str, Callable]` | Required | Input sent to the agent or team. A callable must return the input string. |
| `expected_output` | `Union[str, Callable]` | Required | Expected answer the evaluator scores against. A callable must return the expected string. |
| `agent` | `Optional[Agent]` | `None` | Agent to evaluate. Provide exactly one of `agent` or `team`. |
| `team` | `Optional[Team]` | `None` | Team to evaluate. Provide exactly one of `agent` or `team`. |
| `name` | `Optional[str]` | `None` | Evaluation name. |
| `eval_id` | `str` | Autogenerated UUID | Evaluation ID. |
| `num_iterations` | `int` | `1` | Number of times the input is run and scored. |
| `model` | `Optional[Model]` | `None` | Model for the default evaluator agent. Falls back to OpenAI `o4-mini` when unset. |
| `evaluator_agent` | `Optional[Agent]` | `None` | Custom agent that scores the response. Replaces the default evaluator. |
| `additional_guidelines` | `Optional[Union[str, List[str]]]` | `None` | Guidelines appended to the default evaluator's instructions. |
| `additional_context` | `Optional[str]` | `None` | Context appended to the default evaluator's instructions. |
| `print_summary` | `bool` | `False` | Print the summary table with score statistics after the run. |
| `print_results` | `bool` | `False` | Print the per-iteration results table after the run. |
| `show_spinner` | `bool` | `True` | Render the progress spinner. Set to `False` when the eval runs inside code that must not write to the console. |
| `file_path_to_save_results` | `Optional[str]` | `None` | File path where the result is saved. |
| `debug_mode` | `bool` | `False` | Enable debug logs. Defaults to `True` when the `AGNO_DEBUG` environment variable is `"true"`. |
| `db` | `Optional[Union[BaseDb, AsyncBaseDb]]` | `None` | Database where the eval run is stored. |
| `telemetry` | `bool` | `True` | Log minimal telemetry for the eval run. |
| `result` | `Optional[AccuracyResult]` | `None` | Result of the evaluation. Set after a run completes. |

## Methods

| Method | Return type | Description |
| - | - | - |
| `run(*, print_summary=True, print_results=True)` | `Optional[AccuracyResult]` | Run the agent or team `num_iterations` times and score each response. Raises with an async database; use `arun()` instead. |
| `arun(*, print_summary=True, print_results=True)` | `Optional[AccuracyResult]` | Async version of `run()`. |
| `run_with_output(*, output, print_summary=True, print_results=True)` | `Optional[AccuracyResult]` | Score the given `output` string instead of running the agent or team. |
| `arun_with_output(*, output, print_summary=True, print_results=True)` | `Optional[AccuracyResult]` | Async version of `run_with_output()`. |

## AccuracyResult

| Field | Type | Description |
| - | - | - |
| `results` | `List[AccuracyEvaluation]` | One entry per scored iteration. |
| `avg_score` | `Optional[float]` | Average score across iterations. `None` when there are no results. |
| `mean_score` | `Optional[float]` | Mean score across iterations. Same value as `avg_score`. |
| `min_score` | `Optional[float]` | Lowest score across iterations. |
| `max_score` | `Optional[float]` | Highest score across iterations. |
| `std_dev_score` | `Optional[float]` | Standard deviation of scores. `0` with a single result. |

`AccuracyResult` also exposes `print_summary(console=None)` and `print_results(console=None)` to render the statistics and per-iteration tables.

## AccuracyEvaluation

Each entry in `AccuracyResult.results` is an `AccuracyEvaluation`:

| Field | Type | Description |
| - | - | - |
| `input` | `str` | Input sent to the agent or team. |
| `output` | `str` | Response produced by the agent or team. |
| `expected_output` | `str` | Expected answer the response was scored against. |
| `score` | `int` | Accuracy score from 1 to 10. |
| `reason` | `str` | The evaluator's reasoning for the score. |


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