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

# Protect

> Reference for the Protect class in the Future AGI Python SDK.

# `Protect` Class

The `Protect` class provides a client for evaluating and protecting against unwanted content (such as toxicity, prompt injection, and more) using various metrics and rules. It leverages the `Evaluator` class and a set of built-in evaluation templates.

## Initialization

```python theme={null}
def __init__(
    self,
    fi_api_key: Optional[str] = None,
    fi_secret_key: Optional[str] = None,
    fi_base_url: Optional[str] = None,
    evaluator: Optional[Evaluator] = None,
)
```

**Arguments:**

* `fi_api_key` (Optional\[str]): API key for authentication. If not provided, will be read from environment variables.
* `fi_secret_key` (Optional\[str]): Secret key for authentication. If not provided, will be read from environment variables.
* `fi_base_url` (Optional\[str]): Base URL for the API. If not provided, will be read from environment variables.
* `evaluator` (Optional\[Evaluator]): An instance of the `Evaluator` class to use for evaluations. If not provided, a new one will be created.

**Raises:**

* `InvalidAuthError`: If API key or secret key is missing.

***

## Instance Methods

### `protect`

Evaluates input strings against a set of protection rules and returns messages for any failed checks.

```python theme={null}
def protect(
    self,
    inputs: str,
    protect_rules: List[Dict],
    action: str = "Response cannot be generated as the input fails the checks",
    reason: bool = False,
    timeout: int = 300,
) -> List[str]
```

**Arguments:**

* `inputs` (str): The input string to evaluate.
* `protect_rules` (List\[Dict]): List of protection rule dictionaries. Each rule must contain:
  * `metric` (str): Name of the metric to evaluate (e.g., `"Toxicity"`, `"Tone"`, `"Sexism"`).
  * `contains` (List\[str]): Values to check for in the evaluation results.
  * `type` (str): Either `"any"` or `"all"`, specifying the matching logic.
  * `action` (str): Message to return when the rule is triggered.
  * `reason` (bool, optional): Whether to include the evaluation reason in the message.
* `action` (str, optional): Default message to return when a rule is triggered. Defaults to `"Response cannot be generated as the input fails the checks"`.
* `reason` (bool, optional): Whether to include the evaluation reason in the message. Defaults to `False`.
* `timeout` (int, optional): Timeout for evaluations in seconds. Defaults to `300`.

**Returns:**

* `List[str]`: List of protection messages for failed rules, or `["All checks passed"]` if no rules are triggered.

**Raises:**

* `ValueError`: If `inputs` or `protect_rules` do not match the required structure.
* `TypeError`: If `inputs` contains non-string objects.

***

## Example Usage

```python theme={null}
from fi.evals import Protect

protect_client = Protect(fi_api_key="your_api_key", fi_secret_key="your_secret_key")

rules = [
    {
        "metric": "Toxicity",
    },
    {
        "metric": "Sexism",
    },
]

result = protect_client.protect(
    inputs="Some user input to check.",
    protect_rules=rules,
    timeout=60,
)

print(result)
```

***