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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" }
Required Parameter Type Description textstring 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 containsstring/array Required substring(s) - case insensitive notContainsstring/array Forbidden substring(s) - case insensitive minLengthnumber Minimum text length maxLengthnumber Maximum text length matchesstring Regex pattern the text must match matchFlagsstring Regex flags (default: 'i' for case-insensitive)
Output Fields Field Type Description passedboolean Whether all validations passed failuresarray List of validation failures scorenumber Validation score (0.0 - 1.0) checksobject 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 passed0.5 - 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: wordRequired substring not found Found forbidden content: wordForbidden substring found Text too short: 5 < 10Below minLength Text too long: 600 > 500Above maxLength Text doesn't match pattern: regexRegex 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
Case-Insensitive by Default
The contains and notContains checks are case-insensitive: { "config" : { "contains" : "hello" } } // Matches: "Hello", "HELLO", "hello"
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
