Workflow 1: Data Processing

This workflow processes and transforms data using AI-powered analysis.

Overview

The Data Processing workflow ingests raw data, applies AI analysis, and outputs processed results. It's designed for batch processing of structured and unstructured data.

Workflow Steps

Step 1: Data Ingestion

Purpose: Loads data from various sources (database, files, APIs)

Configuration:

{
  "stepId": "data_ingestion",
  "name": "Data Ingestion",
  "type": "data-input",
  "config": {
    "source": "database",
    "table": "raw_data",
    "batchSize": 1000
  }
}

Step 2: Data Validation

Purpose: Validates data structure and quality

Configuration:

{
  "stepId": "data_validation",
  "name": "Data Validation",
  "type": "validation",
  "config": {
    "schema": "data_schema.json",
    "strict": true
  }
}

Step 3: AI Analysis

Purpose: Applies AI models to analyze and process data

Configuration:

{
  "stepId": "ai_analysis",
  "name": "AI Analysis",
  "type": "ai-process",
  "config": {
    "model": "gpt-4",
    "prompt": "Analyze the following data and extract key insights:",
    "temperature": 0.7
  }
}

Step 4: Result Storage

Purpose: Stores processed results

Configuration:

{
  "stepId": "result_storage",
  "name": "Result Storage",
  "type": "data-output",
  "config": {
    "destination": "database",
    "table": "processed_data"
  }
}

Configuration

Basic Configuration

{
  "name": "Data Processing Workflow",
  "description": "Processes and analyzes data using AI",
  "timeout": 60000,
  "retries": 3
}

Usage Examples

Basic Usage

import { AIWorkflow } from 'ai-workflow';

const workflow = new AIWorkflow({
  apiKey: process.env.AI_WORKFLOW_API_KEY
});

// Execute workflow
const result = await workflow.execute('data-processing-workflow', {
  input: {
    source: 'database',
    table: 'raw_data',
    dateRange: '2024-01-01 to 2024-12-31'
  }
});

console.log('Processed records:', result.processedCount);

With Custom Options

const result = await workflow.execute('data-processing-workflow', {
  input: {
    source: 'api',
    endpoint: 'https://api.example.com/data',
    filters: {
      status: 'active',
      category: 'sales'
    }
  },
  options: {
    async: true,
    priority: 'high'
  }
});

Input/Output

Input Schema

{
  "source": "string (database|api|file)",
  "table": "string (if source is database)",
  "endpoint": "string (if source is api)",
  "filters": {
    "status": "string",
    "category": "string",
    "dateRange": "string"
  }
}

Output Schema

{
  "processedCount": "number",
  "results": [
    {
      "id": "string",
      "analysis": "string",
      "insights": "array",
      "processedAt": "timestamp"
    }
  ],
  "metadata": {
    "duration": "number",
    "model": "string",
    "version": "string"
  }
}

Error Handling

Common Errors

Error Code	Description	Solution
DATA_SOURCE_NOT_FOUND	Data source is unavailable	Check source configuration
INVALID_DATA_FORMAT	Data format is invalid	Validate data schema
AI_MODEL_ERROR	AI model processing failed	Check model configuration

Monitoring

Track Execution Progress

workflow.on('step:started', (step) => {
  console.log(`Step ${step.name} started`);
});

workflow.on('step:completed', (step) => {
  console.log(`Step ${step.name} completed`);
});

Performance Tips

1. Use batch processing for large datasets
2. Enable parallel processing when possible
3. Cache intermediate results
4. Monitor memory usage for large data sets

Related Workflows

• Workflow 2: Content Generation - Uses processed data for content creation
• Workflow 3: Report Generation - Generates reports from processed data

Next Steps

• Workflows Overview - Return to workflows overview
• API Reference - Explore the API