Output Parameters

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.

Output Parameter Types

Basic Types

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

Structured Types

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

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

Media Types

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

Web Types

URL      # Web URLs
EMAIL    # Email addresses

Special Types

TABLE    # Tabular data
DOCUMENT # Document files

Configuration Examples

1. Basic Type Configuration

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

2. Array Type Configuration

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

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"
}

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
}

Task-Specific Examples

AI Task Output

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

App Task Output

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

Coder Task Output

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

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
}

Data Source Configuration

Memory Storage

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

Data Lake Storage

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

Validation Rules

Type-Specific Validation

Basic Types
- BOOLEAN: true/false
- INTEGER: whole numbers
- FLOAT: decimal numbers
- STRING: text values
- DATETIME: valid date/time format
Array Validation
- Must have defined item type
- Items must match specified type
- Valid for nested arrays
Object Validation
- Properties must be defined
- Property types must be valid
- Required properties present

Best Practices

1. Naming Conventions

✅ Do:

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

❌ Don’t:

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

2. Type Selection

Use simplest type possible
Consider downstream requirements
Document format requirements

3. Documentation

Clear descriptions
Format examples
Usage notes

Common Issues and Solutions

Issue 1: Type Mismatch

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

Issue 2: Missing Properties

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

Issue 3: Visibility Issues

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

Examples by Use Case

1. Data Processing Result

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

2. File Generation

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

3. API Integration

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

Agent

Tasks

Tools

Parameters

Knowledge

Guides

Examples

​Output Parameters

​Overview

​Output Parameter Types

​Basic Types

​Structured Types

​File Types

​Media Types

​Web Types

​Special Types

​Configuration Examples

​1. Basic Type Configuration

​2. Array Type Configuration

​3. Object Type Configuration

​4. File Output Configuration

​Task-Specific Examples

​AI Task Output

​App Task Output

​Coder Task Output

​Visibility and Editability

​Data Source Configuration

​Memory Storage

​Data Lake Storage

​Validation Rules

​Type-Specific Validation

​Best Practices

​1. Naming Conventions

​2. Type Selection

​3. Documentation

​Common Issues and Solutions

​Issue 1: Type Mismatch

​Issue 2: Missing Properties

​Issue 3: Visibility Issues

​Examples by Use Case

​1. Data Processing Result

​2. File Generation

​3. API Integration