# Block harmful words and conversations with content filters
<a name="guardrails-content-filters"></a>

Amazon Bedrock Guardrails supports content filters to help detect and filter harmful user inputs and model-generated outputs in natural language as well as code-related content in Standard tier. Content filters are supported across the following categories:

**Hate** 
+ Describes input prompts and model responses that discriminate, criticize, insult, denounce, or dehumanize a person or group on the basis of an identity (such as race, ethnicity, gender, religion, sexual orientation, ability, and national origin).

**Insults** 
+ Describes input prompts and model responses that includes demeaning, humiliating, mocking, insulting, or belittling language. This type of language is also labeled as bullying.

**Sexual** 
+ Describes input prompts and model responses that indicates sexual interest, activity, or arousal using direct or indirect references to body parts, physical traits, or sex.

**Violence** 
+ Describes input prompts and model responses that includes glorification of, or threats to inflict physical pain, hurt, or injury toward a person, group, or thing.

**Misconduct** 
+ Describes input prompts and model responses that seeks or provides information about engaging in criminal activity, or harming, defrauding, or taking advantage of a person, group or institution.

## Configure content filters for your guardrail
<a name="guardrails-filters-text-configure"></a>

You can configure content filters for your guardrail by using the AWS Management Console or Amazon Bedrock API.

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#### [ Console ]

1. Sign in to the AWS Management Console with an IAM identity that has permissions to use the Amazon Bedrock console. Then, open the Amazon Bedrock console at [https://console.aws.amazon.com/bedrock](https://console.aws.amazon.com/bedrock).

1. From the left navigation pane, choose **Guardrails**, and then choose **Create guardrail**.

1. For **Provide guardrail details** page, do the following:

   1. In the **Guardrail details** section, provide a **Name** and optional **Description** for the guardrail.

   1. For **Messaging for blocked prompts**, enter a message that displays when your guardrail is applied. Select the **Apply the same blocked message for responses** checkbox to use the same message when your guardrail is applied on the response.

   1. (Optional) To enable [cross-Region inference](guardrails-cross-region.md) for your guardrail, expand **Cross-Region inference**, and then select **Enable cross-Region inference for your guardrail**. Choose a guardrail profile that defines the destination AWS Regions where guardrail inference requests can be routed.

   1. (Optional) By default, your guardrail is encrypted with an AWS managed key. To use your own customer-managed KMS key, expand **KMS key selection** and select the **Customize encryption settings (advanced)** checkbox.

      You can select an existing AWS KMS key or select **Create an AWS KMS key** to create a new one.

   1. (Optional) To add tags to your guardrail, expand **Tags**. Then select **Add new tag** for each tag that you define.

      For more information, see [Tagging Amazon Bedrock resources](tagging.md).

   1. Choose **Next**.

1. On the **Configure content filters** page, set up how strongly you want to filter out content related to the categories defined in [Block harmful words and conversations with content filters](#guardrails-content-filters) by doing the following:

   1. Select **Configure harmful categories filter**. Select **Text** and/or **Image** to filter text or image content from prompts or responses to the model. Select **None, Low, Medium, or High** for the level of filtration you want to apply to each category. You can choose to have different filter levels for prompts or responses. You can select the filter for prompt attacks in the harmful categories. Configure how strict you want each filter to be for prompts that the user provides to the model.

   1. Choose **Block** or **Detect (no action)** to determine what action your guardrail takes when it detects harmful content in prompts and responses.

      For more information, see [Options for handling harmful content detected by Amazon Bedrock Guardrails](guardrails-harmful-content-handling-options.md).

   1. For **Set threshold**, select **None, Low, Medium, or High** for the level of filtration you want to apply to each category.

      You can choose to have different filter levels for prompts and responses.

   1. For **Content filters tier**, choose the safeguard tier that you want your guardrail to use for filtering text-based prompts and responses. For more information, see [Safeguard tiers for guardrails policies](guardrails-tiers.md).

   1. Choose **Next** to configure other policies as needed or **Skip to Review and create** to finish creating your guardrail.

1. Review the settings for your guardrail.

   1. Select **Edit** in any section you want to make changes to.

   1. When you're done configuring policies, select **Create** to create the guardrail.

------
#### [ API ]

Configure content filters for your guardrail by sending a [CreateGuardrail](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateGuardrail.html) request. The request format is as follows:

```
POST /guardrails HTTP/1.1
Content-type: application/json

{
   "blockedInputMessaging": "string",
   "blockedOutputsMessaging": "string",
   "contentPolicyConfig": { 
      "filtersConfig": [ 
         {
            "inputAction": "BLOCK | NONE",
            "inputModalities": [ "TEXT" ], 
            "inputStrength": "NONE | LOW | MEDIUM | HIGH",
            "outputStrength": "NONE | LOW | MEDIUM | HIGH",
            "type": "SEXUAL | VIOLENCE | HATE | INSULTS | MISCONDUCT"
         }
      ],
      "tierConfig": { 
         "tierName": "CLASSIC | STANDARD"
      }
   },
   "crossRegionConfig": { 
      "guardrailProfileIdentifier": "string"
   },
   "description": "string",
   "name": "string"
}
```
+ Specify a `name` and `description` for the guardrail.
+ Specify messages for when the guardrail successfully blocks a prompt or a model response in the `blockedInputMessaging` and `blockedOutputsMessaging` fields.
+ Specify filter strengths for the harmful categories available the `contentPolicyConfig` object.

  Each item in the `filtersConfig` list pertains to a harmful category. For more information, see [Block harmful words and conversations with content filters](#guardrails-content-filters). For more information about the fields in a content filter, see [ContentFilter](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_ContentFilter.html).
  + (Optional) For `inputAction` and `outputAction`, specify the action your guardrail takes when it detects harmful content in prompts and responses. 
  + (Optional) Specify the action to take when harmful content is detected in prompts using `inputAction` or responses using `outputAction`. Choose `BLOCK` to block content and replace with blocked messaging, or `NONE` to take no action but return detection information. For more information, see [Options for handling harmful content detected by Amazon Bedrock Guardrails](guardrails-harmful-content-handling-options.md).
  + Specify the strength of the filter for prompts in the `inputStrength` field and for model responses in the `outputStrength` field.
  + Specify the category in the `type` field.
+ (Optional) Specify a safeguard tier for your guardrail in the `tierConfig` object within the `contentPolicyConfig` object. Options include `STANDARD` and `CLASSIC` tiers. 

  For more information, see [Safeguard tiers for guardrails policies](guardrails-tiers.md).
+ (Optional) To enable [cross-Region inference](guardrails-cross-region.md), specify a guardrail profile in the `crossRegionConfig` object. This is required when using the `STANDARD` tier.

The response format looks like this:

```
HTTP/1.1 202
Content-type: application/json

{
   "createdAt": "string",
   "guardrailArn": "string",
   "guardrailId": "string",
   "version": "string"
}
```

------