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Task Examples

Overview

This guide provides practical examples of task configurations for common use cases. Each example includes complete configuration and explanation.

Content Review Workflow

1. Generate Content (AI Task)

{
    "type": "TASK",
    "block": {
        "name": "Generate Blog Post",
        "instructions": "Generate a blog post about the provided topic following brand guidelines",
        "input_parameters": [
            {
                "name": "topic",
                "type": "STRING",
                "description": "Blog post topic",
                "required": true,
                "source": "task_config"
            },
            {
                "name": "tone",
                "type": "STRING",
                "description": "Writing tone",
                "required": true,
                "source": "task_config"
            },
            {
                "name": "word_count",
                "type": "INTEGER",
                "description": "Target word count",
                "required": true,
                "source": "task_config"
            }
        ],
        "expected_output": [
            {
                "name": "content",
                "type": "STRING",
                "description": "Generated blog post content"
            }
        ]
    }
}

2. Review Content (Human Task)

{
    "type": "HUMAN_TASK",
    "block": {
        "name": "Review Blog Post",
        "instructions": "Review the generated blog post for quality, accuracy, and brand alignment",
        "dependencies": ["Generate Blog Post"]
    }
}

3. Format Document (App Task)

{
    "type": "APP_TASK",
    "block": {
        "name": "Create PDF",
        "provider": "pdf",
        "tool_name": "writer",
        "tool_id": 12,
        "input_parameters": [
            {
                "name": "content",
                "type": "STRING",
                "description": "Blog post content",
                "required": true,
                "source": "task_config"
            },
            {
                "name": "template",
                "type": "STRING",
                "description": "PDF template",
                "required": true,
                "source": "task_config"
            }
        ],
        "expected_output": [
            {
                "name": "pdf_url",
                "type": "STRING",
                "description": "URL of the generated PDF"
            }
        ],
        "dependencies": ["Review Blog Post"]
    }
}

Data Processing Workflow

1. Process Data (Coder Task)

{
    "type": "CODER",
    "block": {
        "name": "Process CSV Data",
        "code_artifact_id": 123,
        "input_parameters": [
            {
                "name": "csv_data",
                "type": "ARRAY",
                "description": "Raw CSV data",
                "required": true,
                "source": "task_config"
            },
            {
                "name": "processing_rules",
                "type": "OBJECT",
                "description": "Data processing rules",
                "required": true,
                "properties": [
                    {
                        "name": "columns",
                        "type": "ARRAY",
                        "description": "Columns to process"
                    },
                    {
                        "name": "aggregation",
                        "type": "STRING",
                        "description": "Aggregation method"
                    }
                ]
            }
        ],
        "expected_output": [
            {
                "name": "processed_data",
                "type": "ARRAY",
                "description": "Processed data"
            }
        ]
    }
}

2. Validate Results (AI Task)

{
    "type": "TASK",
    "block": {
        "name": "Validate Data",
        "instructions": "Analyze the processed data for anomalies and validation issues",
        "input_parameters": [
            {
                "name": "data",
                "type": "ARRAY",
                "description": "Processed data to validate",
                "required": true
            }
        ],
        "expected_output": [
            {
                "name": "validation_result",
                "type": "OBJECT",
                "properties": {
                    "is_valid": "BOOLEAN",
                    "issues": "ARRAY",
                    "recommendations": "ARRAY"
                }
            }
        ],
        "dependencies": ["Process CSV Data"]
    }
}

3. Review Results (Human Task)

{
    "type": "HUMAN_TASK",
    "block": {
        "name": "Review Results",
        "instructions": "Review the processed data and validation results. Approve if accurate or reject for reprocessing.",
        "dependencies": ["Validate Data"]
    }
}

Document Generation Workflow

1. Gather Data (App Task)

{
    "type": "APP_TASK",
    "block": {
        "name": "Fetch Data",
        "provider": "database",
        "tool_name": "query_executor",
        "tool_id": 34,
        "input_parameters": [
            {
                "name": "query_params",
                "type": "OBJECT",
                "description": "Query parameters",
                "required": true
            }
        ],
        "expected_output": [
            {
                "name": "query_results",
                "type": "ARRAY",
                "description": "Query results"
            }
        ]
    }
}

2. Generate Report (Coder Task)

{
    "type": "CODER",
    "block": {
        "name": "Generate Report",
        "code_artifact_id": 456,
        "input_parameters": [
            {
                "name": "data",
                "type": "ARRAY",
                "description": "Report data",
                "required": true
            },
            {
                "name": "template",
                "type": "STRING",
                "description": "Report template",
                "required": true
            }
        ],
        "expected_output": [
            {
                "name": "report",
                "type": "OBJECT",
                "properties": {
                    "content": "STRING",
                    "metadata": "OBJECT"
                }
            }
        ],
        "dependencies": ["Fetch Data"]
    }
}

Task Combinations

AI + Human Review

graph TD
    A[AI Analysis] --> B[Human Review]
    B -- Approved --> C[Next Task]
    B -- Rejected --> A

App + Coder Processing

graph TD
    A[App Data Fetch] --> B[Coder Processing]
    B --> C[Result Storage]

Best Practices

  1. Task Dependencies

    • Keep chains simple
    • Validate data flow
    • Handle all outcomes

  2. Error Handling

    • Define recovery paths
    • Set retry policies
    • Log errors properly

  3. Performance

    • Optimize data transfer
    • Set appropriate timeouts
    • Monitor execution time