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

# Camel.models.reward.evaluator

<a id="camel.models.reward.evaluator" />

<a id="camel.models.reward.evaluator.Evaluator" />

## Evaluator

```python theme={"system"}
class Evaluator:
```

Evaluator class to evaluate messages using a reward model and filter
data based on the scores.

**Parameters:**

* **reward\_model** (BaseRewardModel): A reward model to evaluate messages.

<a id="camel.models.reward.evaluator.Evaluator.__init__" />

### **init**

```python theme={"system"}
def __init__(self, reward_model: BaseRewardModel):
```

<a id="camel.models.reward.evaluator.Evaluator.evaluate" />

### evaluate

```python theme={"system"}
def evaluate(self, messages: List[Dict[str, str]]):
```

Evaluate the messages using the reward model.

**Parameters:**

* **messages** (List\[Dict\[str, str]]): A list of messages where each message is a dictionary with 'role' and 'content'.

**Returns:**

Dict\[str, float]: A dictionary mapping score types to their values.

<a id="camel.models.reward.evaluator.Evaluator.filter_data" />

### filter\_data

```python theme={"system"}
def filter_data(
    self,
    messages: List[Dict[str, str]],
    thresholds: Dict[str, float]
):
```

Filter messages based on the scores.

**Parameters:**

* **messages** (List\[Dict\[str, str]]): A list of messages where each message is a dictionary with 'role' and 'content'.
* **thresholds** (Dict\[str, float]): A dictionary mapping score types to their values.

**Returns:**

bool: A boolean indicating whether the messages pass the filter.