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Extract Dynamic Variables

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Overview

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When to use

• Collect user information
• Extract contact details
• Capture preferences
• Identify intent
• Parse structured data

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Configuration

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Variable Types

• Text - String values
• Number - Numeric values
• Email - Email addresses
• Phone - Phone numbers
• Date - Date and time values
• Boolean - True/false values
• Custom - Business-specific formats

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Extraction Methods

• Pattern Matching - Regex patterns
• Entity Recognition - NLP-based extraction
• Context Analysis - Conversation context
• Validation Rules - Format validation

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Implementation

{
  "function": "extract_dynamic_variables",
  "parameters": {
    "variables": {
      "name": {
        "type": "text",
        "required": true,
        "prompt": "What is your name?"
      },
      "email": {
        "type": "email", 
        "required": true,
        "validation": "^[\\w\\.-]+@[\\w\\.-]+\\.[a-zA-Z]{2,}$"
      },
      "phone": {
        "type": "phone",
        "required": false,
        "format": "international"
      },
      "appointment_time": {
        "type": "date",
        "required": true,
        "format": "datetime"
      }
    },
    "extraction_strategy": "context_aware"
  }
}

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Common Use Cases

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Lead Generation

• Name extraction
• Contact information
• Company details
• Interest areas

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Appointment Booking

• Date/time preferences
• Service type
• Contact details
• Special requirements

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Support Requests

• Issue description
• Account information
• Urgency level
• Contact preferences

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Best Practices

• Define clear variable types
• Use appropriate validation
• Handle extraction failures
• Confirm extracted values
• Store securely

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Next Steps

• Agent Transfer