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Personality System Overview

FlavumHive's personality system enables the creation and management of distinct AI personalities that can interact across multiple social media platforms while maintaining consistent character traits and behaviors.

Core Concepts​

What is a Personality?​

A personality in FlavumHive represents a distinct character with:

  • Defined traits and characteristics
  • Specific knowledge domains
  • Consistent voice and tone
  • Platform-specific behavior patterns

Key Components​

  1. Personality Definition

    • Character traits
    • Knowledge base
    • Interaction patterns
    • Response templates

  2. State Management

    • Conversation history
    • Context awareness
    • Memory persistence
    • Cross-platform state

  3. Behavior Control

    • Rate limiting
    • Content filtering
    • Platform adaptation
    • Interaction rules

Available Personalities​

Crypto Researcher​

  • Deep knowledge of blockchain technology
  • Analysis of market trends
  • Technical explanations
  • Research-focused content

Tech Enthusiast​

  • Latest technology trends
  • Product reviews
  • Tech news commentary
  • Innovation discussions

Community Manager​

  • Engagement focused
  • Community building
  • Support handling
  • Event coordination

Creating Custom Personalities​

Basic Structure​

class CustomPersonality(BasePersonality):
    def __init__(self):
        self.traits = {
            "name": "Custom Name",
            "expertise": ["Domain1", "Domain2"],
            "tone": "professional"
        }

Configuration​

{
  "personality": {
    "name": "custom_name",
    "traits": {
      "expertise": ["domain1", "domain2"],
      "tone": "professional",
      "response_style": "detailed"
    }
  }
}

Best Practices​

  1. Consistency

    • Maintain consistent voice
    • Align knowledge domains
    • Use consistent formatting
    • Follow platform guidelines

  2. Engagement

    • Natural conversation flow
    • Appropriate response timing
    • Context-aware interactions
    • Platform-specific adaptation

  3. Maintenance

    • Regular updates
    • Performance monitoring
    • Feedback integration
    • Behavior refinement

Next Steps​