ValidateContent

Overview

The ValidateContent block validates text content against various rules like required substrings, forbidden words, length constraints, and regex patterns.

{
  "block": "ValidateContent",
  "input": {
    "from": "response.message",
    "as": "text"
  },
  "config": {
    "contains": ["hello", "world"]
  },
  "output": "validation"
}

Input Parameters

Required

Parameter	Type	Description
`text`	string	The text content to validate

Note: Use the from/as input format to map your data to the text parameter.

Configuration

All config parameters are optional. Use the ones relevant to your validation:

Parameter	Type	Description
`contains`	string/array	Required substring(s) - case insensitive
`notContains`	string/array	Forbidden substring(s) - case insensitive
`minLength`	number	Minimum text length
`maxLength`	number	Maximum text length
`matches`	string	Regex pattern the text must match
`matchFlags`	string	Regex flags (default: `'i'` for case-insensitive)

Output Fields

Field	Type	Description
`passed`	boolean	Whether all validations passed
`failures`	array	List of validation failures
`score`	number	Validation score (0.0 - 1.0)
`checks`	object	Individual check results

Examples

Validate Required Keywords

{
  "block": "ValidateContent",
  "input": {
    "from": "aiResponse.message",
    "as": "text"
  },
  "config": {
    "contains": ["appointment", "time"]
  },
  "output": "validation"
}

Success:

{
  passed: true,
  failures: [],
  score: 1.0,
  checks: {
    contains_appointment: true,
    contains_time: true
  }
}

Failure:

{
  passed: false,
  failures: ["Missing expected content: time"],
  score: 0.5,
  checks: {
    contains_appointment: true,
    contains_time: false
  }
}

Forbid Inappropriate Content

{
  "block": "ValidateContent",
  "input": {
    "from": "userInput.comment",
    "as": "text"
  },
  "config": {
    "notContains": ["spam", "offensive", "inappropriate"]
  },
  "output": "validation"
}

Validate Text Length

{
  "block": "ValidateContent",
  "input": {
    "from": "user.bio",
    "as": "text"
  },
  "config": {
    "minLength": 10,
    "maxLength": 500
  },
  "output": "validation"
}

Regex Pattern Matching

{
  "block": "ValidateContent",
  "input": {
    "from": "user.email",
    "as": "text"
  },
  "config": {
    "matches": "^[\\w.-]+@[\\w.-]+\\.\\w+$"
  },
  "output": "emailValidation"
}

Combined Validations

{
  "block": "ValidateContent",
  "input": {
    "from": "aiResponse.message",
    "as": "text"
  },
  "config": {
    "contains": ["meeting", "time"],
    "notContains": ["error", "failed"],
    "minLength": 20,
    "maxLength": 500,
    "matches": "\\d{1,2}:\\d{2}"
  },
  "output": "validation"
}

Common Patterns

Validate AI Response Quality

{
  "pipeline": [
    {
      "block": "HttpRequest",
      "input": {
        "url": "${AI_API_URL}/chat",
        "method": "POST",
        "body": {
          "message": "What time is the meeting?"
        }
      },
      "output": "response"
    },
    {
      "block": "JsonParser",
      "input": "${response.body}",
      "output": { "parsed": "aiResponse" }
    },
    {
      "block": "ValidateContent",
      "input": {
        "from": "aiResponse.message",
        "as": "text"
      },
      "config": {
        "contains": ["meeting", "time"],
        "minLength": 10
      },
      "output": "validation"
    }
  ],
  "assertions": {
    "validation.passed": true
  }
}

Multi-Field Validation

{
  "pipeline": [
    {
      "block": "MockData",
      "config": {
        "data": {
          "name": "John Doe",
          "email": "john@example.com",
          "bio": "Software engineer"
        }
      },
      "output": "user"
    },
    {
      "id": "validate-name",
      "block": "ValidateContent",
      "input": {
        "from": "user.name",
        "as": "text"
      },
      "config": {
        "minLength": 2,
        "maxLength": 100
      },
      "output": "nameValidation"
    },
    {
      "id": "validate-email",
      "block": "ValidateContent",
      "input": {
        "from": "user.email",
        "as": "text"
      },
      "config": {
        "matches": ".*@.*\\..*"
      },
      "output": "emailValidation"
    },
    {
      "id": "validate-bio",
      "block": "ValidateContent",
      "input": {
        "from": "user.bio",
        "as": "text"
      },
      "config": {
        "minLength": 10
      },
      "output": "bioValidation"
    }
  ],
  "assertions": {
    "nameValidation.passed": true,
    "emailValidation.passed": true,
    "bioValidation.passed": true
  }
}

Content Safety Check

{
  "block": "ValidateContent",
  "input": {
    "from": "userComment.text",
    "as": "text"
  },
  "config": {
    "notContains": [
      "spam",
      "offensive",
      "inappropriate",
      "abuse"
    ],
    "minLength": 5,
    "maxLength": 10000
  },
  "output": "safetyCheck"
}

Validation Score

The score field represents how well the content passed validation:

1.0 - All validations passed
0.5 - Some validations failed
< 0.5 - Multiple validations failed

The score is calculated based on:

Missing required content
Forbidden content found
Length violations
Pattern mismatches

Use the score for assertions:

{
  "assertions": {
    "validation.score": { "gt": 0.8 }
  }
}

Error Messages

Common failure messages:

Message	Cause
`Missing expected content: word`	Required substring not found
`Found forbidden content: word`	Forbidden substring found
`Text too short: 5 < 10`	Below minLength
`Text too long: 600 > 500`	Above maxLength
`Text doesn't match pattern: regex`	Regex pattern didn’t match

Full Example

{
  "name": "Content Validation Test",
  "context": {
    "AI_API_URL": "${env.AI_API_URL}"
  },
  "tests": [{
    "id": "validate-ai-response",
    "pipeline": [
      {
        "id": "call-ai",
        "block": "HttpRequest",
        "input": {
          "url": "${AI_API_URL}/chat",
          "method": "POST",
          "headers": {
            "Authorization": "Bearer ${env.API_KEY}"
          },
          "body": {
            "messages": [{
              "role": "user",
              "content": "Schedule a meeting for tomorrow at 2pm"
            }]
          }
        },
        "output": "response"
      },
      {
        "id": "parse",
        "block": "JsonParser",
        "input": "${response.body}",
        "output": {
          "parsed": "aiResponse"
        }
      },
      {
        "id": "validate-response",
        "block": "ValidateContent",
        "input": {
          "from": "aiResponse.message",
          "as": "text"
        },
        "config": {
          "contains": ["meeting", "tomorrow", "2pm"],
          "notContains": ["error", "sorry", "cannot"],
          "minLength": 20,
          "maxLength": 500
        },
        "output": "validation"
      }
    ],
    "assertions": {
      "response.status": 200,
      "validation.passed": true,
      "validation.score": { "gt": 0.9 }
    }
  }]
}

Tips

Use from/as Input Format

ValidateContent expects a text parameter. Use the from/as format:

{
  "input": {
    "from": "response.message",
    "as": "text"
  }
}

Case-Insensitive by Default

The contains and notContains checks are case-insensitive:

{
  "config": {
    "contains": "hello"
  }
}
// Matches: "Hello", "HELLO", "hello"

Combine with LLMJudge

Use ValidateContent for structural checks, LLMJudge for semantic validation:

{
  "pipeline": [
    {
      "block": "ValidateContent",
      "input": { "from": "response.text", "as": "text" },
      "config": { "minLength": 10, "contains": "meeting" },
      "output": "structureCheck"
    },
    {
      "block": "LLMJudge",
      "input": {
        "text": "${response.text}",
        "expected": { "expectedBehavior": "Professional tone" }
      },
      "output": "semanticCheck"
    }
  ]
}

Use Regex for Complex Patterns

Regex patterns are powerful for complex validation:

{
  "config": {
    "matches": "^Meeting at \\d{1,2}(am|pm)$"
  }
}

When to Use

Use ValidateContent when:

Checking for required keywords
Filtering inappropriate content
Validating text length
Pattern matching (emails, URLs, etc.)
Structural content validation

Use LLMJudge instead when:

Checking semantic meaning
Evaluating tone or style
Comparing similarity to expected content
Complex reasoning about content

Next Steps

LLMJudge

Semantic content validation

ValidateTools

Validate AI tool calls

Get Started

Core Concepts

Blocks

Testing AI Systems

Advanced

Overview

Input Parameters

Required

Configuration

Output Fields

Examples

Validate Required Keywords

Forbid Inappropriate Content

Validate Text Length

Regex Pattern Matching

Combined Validations

Common Patterns

Validate AI Response Quality

Multi-Field Validation

Content Safety Check

Validation Score

Error Messages

Full Example

Tips

When to Use

Next Steps

LLMJudge

ValidateTools

Get Started

Core Concepts

Blocks

Testing AI Systems

Advanced

​Overview

​Input Parameters

​Required

​Configuration

​Output Fields

​Examples

​Validate Required Keywords

​Forbid Inappropriate Content

​Validate Text Length

​Regex Pattern Matching

​Combined Validations

​Common Patterns

​Validate AI Response Quality

​Multi-Field Validation

​Content Safety Check

​Validation Score

​Error Messages

​Full Example

​Tips

​When to Use

​Next Steps

LLMJudge

ValidateTools

Overview

Input Parameters

Required

Configuration

Output Fields

Examples

Validate Required Keywords

Forbid Inappropriate Content

Validate Text Length

Regex Pattern Matching

Combined Validations

Common Patterns

Validate AI Response Quality

Multi-Field Validation

Content Safety Check

Validation Score

Error Messages

Full Example

Tips

When to Use

Next Steps