org.llm4s.agent.guardrails

Combines multiple guardrails with configurable validation mode.

Supports three modes:

All: All guardrails must pass (strictest)
Any: At least one guardrail must pass (OR logic)
First: First result wins (performance optimization)

Type parameters

A: The type of value to validate

Value parameters

guardrails: The guardrails to combine
mode: How to combine validation results

Attributes

Companion: object
Supertypes: trait Guardrail[A]

class Object

trait Matchable

class Any

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: CompositeGuardrail.type

Base trait for all guardrails.

A guardrail is a pure function that validates a value of type A. Guardrails are used to validate inputs before agent processing and outputs before returning results to users.

Type parameters

A: The type of value to validate

Attributes

Supertypes: class Object

trait Matchable

class Any
Known subtypes: class CompositeGuardrail[A]

trait InputGuardrail

class LengthCheck

class PIIDetector

class PIIMasker

class ProfanityFilter

class PromptInjectionDetector

class RegexValidator

class TopicBoundaryGuardrail

trait OutputGuardrail

class JSONValidator

class ToneValidator

trait RAGGuardrail

class ContextRelevanceGuardrail

class GroundingGuardrail

class SourceAttributionGuardrail

trait LLMGuardrail

class LLMFactualityGuardrail

class LLMQualityGuardrail

class LLMSafetyGuardrail

class LLMToneGuardrail
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Actions to take when a guardrail detects a violation.

Guardrails can be configured to respond to violations in different ways depending on the use case and severity of the detected issue.

Example usage:

// Block on prompt injection (security critical)
val injectionGuard = PromptInjectionDetector(onFail = GuardrailAction.Block)

// Fix PII by masking (privacy preserving)
val piiGuard = PIIDetector(onFail = GuardrailAction.Fix)

// Warn on low-severity issues (monitoring)
val lengthGuard = LengthCheck(1, 10000, onFail = GuardrailAction.Warn)

Attributes

Companion: object
Supertypes: class Object

trait Matchable

class Any
Known subtypes: object Block

object Fix

object Warn

Attributes

Companion: trait
Supertypes: trait Sum

trait Mirror

class Object

trait Matchable

class Any
Self type: GuardrailAction.type

Result of a guardrail check with action handling.

Extends the basic Result type with information about what action was taken and any warnings that were logged.

Attributes

Companion: object
Supertypes: class Object

trait Matchable

class Any
Known subtypes: class Blocked

class Fixed[A]

class Passed[A]

class Warned[A]

Attributes

Companion: trait
Supertypes: trait Sum

trait Mirror

class Object

trait Matchable

class Any
Self type: GuardrailResult.type

Validates user input before agent processing.

Input guardrails run BEFORE the LLM is called, validating:

User queries
System prompts
Tool arguments

Attributes

Supertypes: trait Guardrail[String]

class Object

trait Matchable

class Any
Known subtypes: class LengthCheck

class PIIDetector

class PIIMasker

class ProfanityFilter

class PromptInjectionDetector

class RegexValidator

class TopicBoundaryGuardrail
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Base trait for LLM-based guardrails (LLM-as-Judge pattern).

LLM guardrails use a language model to evaluate content against natural language criteria. This enables validation of subjective qualities like tone, factual accuracy, and safety that cannot be easily validated with deterministic rules.

Unlike function-based guardrails, LLM guardrails:

Use natural language evaluation prompts
Return a score between 0.0 and 1.0
Pass if score >= threshold
Can use a separate model for judging (to avoid self-evaluation bias)

Attributes

Note

LLM guardrails have higher latency than function-based guardrails due to the LLM API call. Consider using them only when deterministic validation is insufficient.

Example

class MyCustomLLMGuardrail(client: LLMClient) extends LLMGuardrail {
 val llmClient = client
 val evaluationPrompt = "Rate if this response is helpful (0-1)"
 val threshold = 0.7
 val name = "HelpfulnessGuardrail"
}

Companion

object

Supertypes

trait OutputGuardrail

trait Guardrail[String]

class Object

trait Matchable

class Any

Known subtypes

class LLMFactualityGuardrail

class LLMQualityGuardrail

class LLMSafetyGuardrail

class LLMToneGuardrail

Attributes

Companion: trait
Supertypes: class Object

trait Matchable

class Any
Self type: LLMGuardrail.type

Validates agent output before returning to user.

Output guardrails run AFTER the LLM responds, validating:

Assistant messages
Tool results
Final responses

Attributes

Supertypes: trait Guardrail[String]

class Object

trait Matchable

class Any
Known subtypes: class JSONValidator

class LengthCheck

class PIIDetector

class PIIMasker

class ProfanityFilter

class RegexValidator

class ToneValidator

trait RAGGuardrail

class ContextRelevanceGuardrail

class GroundingGuardrail

class SourceAttributionGuardrail

trait LLMGuardrail

class LLMFactualityGuardrail

class LLMQualityGuardrail

class LLMSafetyGuardrail

class LLMToneGuardrail
Show all

Mode for combining multiple guardrails.

Determines how validation results are combined when multiple guardrails are applied to the same value.

Attributes

Companion: object
Supertypes: class Object

trait Matchable

class Any
Known subtypes: object All

object Any

object First

Attributes

Companion: trait
Supertypes: trait Sum

trait Mirror

class Object

trait Matchable

class Any
Self type: ValidationMode.type

org.llm4s.agent.guardrails

Members list

Packages

Type members

Classlikes

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