/guardrails/apply_guardrail

Use this endpoint to directly call a guardrail configured on your LiteLLM instance. This is useful when you have services that need to directly call a guardrail.

Supported Guardrail Types

This endpoint supports various guardrail types including:

• Presidio - PII detection and masking
• Bedrock - AWS Bedrock guardrails for content moderation
• Lakera - AI safety guardrails
• PANW Prisma AIRS - Threat detection, DLP, and policy enforcement
• Custom guardrails - User-defined guardrails

Configuration

Bedrock Guardrail Configuration

To use Bedrock guardrails with the apply_guardrail endpoint, configure your guardrail in your LiteLLM config.yaml:

guardrails:
  - guardrail_name: "bedrock-content-guard"
    litellm_params:
      guardrail: bedrock
      mode: "pre_call"
      guardrailIdentifier: "your-guardrail-id"  # Your actual Bedrock guardrail ID
      guardrailVersion: "DRAFT"  # or your version number
      aws_region_name: "us-east-1"  # Your AWS region
      aws_role_name: "your-role-arn"  # Your AWS role with Bedrock permissions
      default_on: true

Required AWS Setup:

1. Create a Bedrock guardrail in AWS Console
2. Get the guardrail ID and version
3. Ensure your AWS credentials have Bedrock permissions
4. Configure the guardrail in your LiteLLM config

Usage

---

In this example mask_pii is a Presidio guardrail configured on LiteLLM.

curl -X POST 'http://localhost:4000/guardrails/apply_guardrail' \\
-H 'Content-Type: application/json' \\
-H 'Authorization: Bearer your-api-key' \\
-d '{
    "guardrail_name": "mask_pii",
    "text": "My name is John Doe and my email is john@example.com",
    "language": "en",
    "entities": ["NAME", "EMAIL"]
}'

In this example bedrock-content-guard is a Bedrock guardrail configured on LiteLLM.

curl -X POST 'http://localhost:4000/guardrails/apply_guardrail' \\
-H 'Content-Type: application/json' \\
-H 'Authorization: Bearer your-api-key' \\
-d '{
    "guardrail_name": "bedrock-content-guard",
    "text": "This is potentially harmful content that should be blocked",
    "language": "en"
}'

Note: For Bedrock guardrails, the entities parameter is not used as Bedrock handles content moderation based on its own policies.

Request Format

---

The request body should follow the ApplyGuardrailRequest format.

Example Request Body

{
    "guardrail_name": "mask_pii",
    "text": "My name is John Doe and my email is john@example.com",
    "language": "en",
    "entities": ["NAME", "EMAIL"]
}

Required Fields

• guardrail_name (string):
  The identifier for the guardrail to apply (e.g., "mask_pii").
• text (string):
  The input text to process through the guardrail.

Optional Fields

• language (string):
  The language of the input text (e.g., "en" for English).
• entities (array of strings):
  Specific entities to process or filter (e.g., ["NAME", "EMAIL"]).

Response Format

---

The response will contain the processed text after applying the guardrail.

Example Response

{
    "response_text": "My name is [REDACTED] and my email is [REDACTED]"
}

{
    "response_text": "This is potentially harmful content that should be blocked"
}

Note: If Bedrock guardrail blocks the content, the endpoint will return an error with the blocking reason.

Response Fields

• response_text (string):
  The text after applying the guardrail.

Error Responses

If a guardrail blocks content (e.g., Bedrock guardrail), the endpoint will return an error:

{
    "detail": "Content blocked by Bedrock guardrail: Content violates policy"
}