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¶
Web Types¶
Special Types¶
Configuration Examples¶
1. Basic Type Configuration¶
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¶
Data Lake Storage¶
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:
❌ Don't:
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
}