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The praisonai-ts CLI provides the guardrail command for content validation.

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Quick Start

1

Simple Usage

praisonai-ts guardrail check "Your content here"
2

With Configuration

praisonai-ts guardrail check "Content to validate" --criteria "Must be professional" --json

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Basic Usage

# Check content against guardrails
praisonai-ts guardrail check "Your content here"

# Check with custom criteria
praisonai-ts guardrail check "Content to validate" --criteria "Must be professional"

# Get JSON output
praisonai-ts guardrail check "Hello world" --json
Example Output: 
{
  "success": true,
  "data": {
    "status": "passed",
    "score": 0.95,
    "message": "Content passes all criteria",
    "reasoning": "The content is appropriate and safe"
  }
}

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Status Values

StatusDescription
passedContent meets all criteria
failedContent does not meet criteria
warningContent partially meets criteria

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SDK Usage

For programmatic guardrail usage: 
import { LLMGuardrail } from 'praisonai';

const guard = new LLMGuardrail({
  name: 'safety',
  criteria: 'Content must be safe and appropriate',
  threshold: 0.8
});

const result = await guard.check('Hello world');
console.log(result.status); // 'passed', 'failed', or 'warning'
console.log(result.score);  // 0-1
console.log(result.reasoning);
For more details, see the LLM Guardrail SDK documentation.

LLM Guardrail

LLM Guardrail overview

Guardrails

Guardrails overview