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Output Parameters

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Overview

Output parameters define the expected output format and structure from tasks in your workflow. This guide covers all available output parameter types and their configurations.

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Output Parameter Types

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Basic Types

BOOLEAN  # True/False values
INTEGER  # Whole numbers
FLOAT    # Decimal numbers
STRING   # Text values
DATETIME # Date and time values

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Structured Types

ENTITY   # Entity references
JSON     # JSON formatted data
ARRAY    # List of items
OBJECT   # Complex objects
ENUM     # Enumerated values

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File Types

TEXT     # Plain text files
MARKDOWN # Markdown formatted text
HTML     # HTML content
CODE     # Source code
PDF      # PDF documents
CSV      # CSV data
XML      # XML data
FILE     # Generic files
PPT      # PowerPoint presentations

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Media Types

IMAGE    # Image files
VIDEO    # Video files
AUDIO    # Audio files
GIF      # GIF animations

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Web Types

URL      # Web URLs
EMAIL    # Email addresses

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Special Types

TABLE    # Tabular data
DOCUMENT # Document files

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Configuration Examples

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1. Basic Type Configuration

{
    "name": "is_valid",
    "type": "BOOLEAN",
    "description": "Indicates if the process was successful"
}

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2. Array Type Configuration

{
    "name": "results",
    "type": "ARRAY",
    "items": {
        "type": "STRING"
    },
    "description": "List of processed items"
}

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3. Object Type Configuration

{
    "name": "user_data",
    "type": "OBJECT",
    "properties": {
        "id": {
            "type": "INTEGER",
            "description": "User ID"
        },
        "email": {
            "type": "STRING",
            "description": "User email"
        }
    },
    "description": "User information object"
}

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4. File Output Configuration

{
    "name": "report",
    "type": "PDF",
    "description": "Generated report file",
    "content": null,
    "gaife_internal_is_data_visible": true,
    "gaife_internal_is_data_editable": false
}

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Task-Specific Examples

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AI Task Output

{
    "name": "sentiment_analysis",
    "type": "OBJECT",
    "properties": {
        "sentiment": {
            "type": "STRING",
            "description": "Detected sentiment"
        },
        "confidence": {
            "type": "FLOAT",
            "description": "Confidence score"
        }
    }
}

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App Task Output

{
    "name": "api_response",
    "type": "JSON",
    "description": "API response data",
    "gaife_internal_is_data_visible": true
}

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Coder Task Output

{
    "name": "calculation_result",
    "type": "OBJECT",
    "properties": {
        "result": {
            "type": "FLOAT",
            "description": "Calculated value"
        },
        "metadata": {
            "type": "OBJECT",
            "description": "Additional information"
        }
    }
}

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Visibility and Editability

Control output parameter visibility and editability:

{
    "name": "sensitive_data",
    "type": "OBJECT",
    "gaife_internal_is_data_visible": false,
    "gaife_internal_is_data_editable": false
}

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Data Source Configuration

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Memory Storage

{
    "name": "result",
    "type": "OBJECT",
    "data_source": "MEMORY"
}

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Data Lake Storage

{
    "name": "large_dataset",
    "type": "ARRAY",
    "data_source": "DATA_LAKE",
    "data_lake_id": "12345"
}

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Validation Rules

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Type-Specific Validation

  1. Basic Types

    • BOOLEAN: true/false
    • INTEGER: whole numbers
    • FLOAT: decimal numbers
    • STRING: text values
    • DATETIME: valid date/time format

  2. Array Validation

    • Must have defined item type
    • Items must match specified type
    • Valid for nested arrays

  3. Object Validation

    • Properties must be defined
    • Property types must be valid
    • Required properties present

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Best Practices

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1. Naming Conventions

✅ Do:

{
    "name": "userProfileData",
    "description": "Complete user profile information"
}

❌ Don’t:

{
    "name": "data1",
    "description": "some data"
}

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2. Type Selection

  • Use simplest type possible
  • Consider downstream requirements
  • Document format requirements

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3. Documentation

  • Clear descriptions
  • Format examples
  • Usage notes

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Common Issues and Solutions

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Issue 1: Type Mismatch

  • Problem: Output type doesn’t match connected input
  • Solution: Verify type compatibility between connected tasks

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Issue 2: Missing Properties

  • Problem: Required object properties not defined
  • Solution: Define all required properties in object type

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Issue 3: Visibility Issues

  • Problem: Data not visible in UI
  • Solution: Check gaife_internal_is_data_visible setting

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Examples by Use Case

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1. Data Processing Result

{
    "name": "processing_result",
    "type": "OBJECT",
    "properties": {
        "status": "STRING",
        "processed_items": "INTEGER",
        "errors": "ARRAY"
    }
}

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2. File Generation

{
    "name": "generated_file",
    "type": "PDF",
    "description": "Generated report",
    "gaife_internal_is_data_visible": true
}

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3. API Integration

{
    "name": "api_result",
    "type": "JSON",
    "description": "API response data"
}