profile_creation.py - ResonanceOS v6 Documentation

Profile Creation Thesis

The profile_creation.py module provides comprehensive examples demonstrating HRV profile creation, management, and usage in ResonanceOS v6. This educational script showcases various methods for creating profiles including manual definition, text-based extraction, specialized profiles for different writing styles, adaptive profiles for specific contexts, and complete profile management operations - all designed to help users master the profile system for generating content with consistent tonal characteristics.

Technical Specifications

Purpose: HRV Profile Creation Education
Methods: Manual, Text-Based, Adaptive Creation
Profile Types: Professional, Creative, Technical, Marketing
Management: Multi-Tenant Profile Operations
Features: Profile Comparison & Context Adaptation

Core Implementation

from resonance_os.profiles.multi_tenant_hr_profiles import HRVProfileManager
from resonance_os.profiles.hrv_extractor import HRVExtractor

def create_basic_profile():
    """Create a basic HRV profile from scratch"""
    
    # Initialize profile manager
    profiles_dir = project_root / "data" / "profiles" / "hr_profiles"
    manager = HRVProfileManager(str(profiles_dir))
    
    # HRV vector (8 dimensions)
    hrv_vector = [0.45, 0.15, 0.35, 0.75, 0.40, 0.25, 0.30, 0.80]
    
    # Save profile
    manager.save_profile(tenant, profile_name, hrv_vector)
                

Basic Profile Creation

Create profiles from scratch with manually defined HRV vectors

Text-Based Creation

Extract HRV characteristics from existing text content

Specialized Profiles

Create profiles for specific writing styles and contexts

Adaptive Profiles

Generate context-specific profiles with automatic adjustments

Profile Creation Workflow

Define Parameters

Set tenant, profile name, and HRV vector

↓

Initialize Manager

Create HRVProfileManager instance

↓

Save Profile

Store profile in multi-tenant storage

↓

Verify Creation

Load and confirm profile integrity

Profile Types & Examples

Specialized Profile Categories

def create_creative_profile():
    """Create a creative writing profile"""
    
    # Creative writing HRV vector
    # Higher emotional content, storytelling, and metaphor
    creative_hrv = [0.75, 0.65, 0.85, 0.45, 0.80, 0.70, 0.90, 0.65]
    
    profile_name = "creative_storyteller"
    description = "Creative storytelling profile with high narrative and emotional content"
                    

professional_modern

[0.45, 0.15, 0.35, 0.75, 0.40, 0.25, 0.30, 0.80]

Modern professional business tone

business_executive

[0.42, 0.18, 0.31, 0.78, 0.34, 0.21, 0.28, 0.85]

Executive communication style

creative_storyteller

[0.75, 0.65, 0.85, 0.45, 0.80, 0.70, 0.90, 0.65]

High narrative and emotional content

technical_academic

[0.32, 0.12, 0.28, 0.81, 0.31, 0.18, 0.25, 0.82]

Technical documentation style

Text-Based Profile Creation

Profile Extraction from Text

def create_profile_from_text():
    """Create an HRV profile from existing text content"""
    
    # Sample text content
    sample_text = """
    Executive Summary: The fourth quarter of 2024 demonstrated exceptional performance 
    across all key metrics. Revenue increased by 23% compared to the previous quarter, 
    reaching a record high of $45.2 million. This growth was primarily driven by our 
    expanded product line and successful market penetration in emerging regions.
    """
    
    # Extract HRV from sample text
    extractor = HRVExtractor()
    hrv_vector = extractor.extract(sample_text)
    
    # Create profile from extracted HRV
    profile_name = "business_executive"
    description = "Executive business communication profile derived from sample text"
    
    manager.save_profile(tenant, profile_name, hrv_vector)
                    

Extraction Results

Original Text

Executive business report with financial metrics and strategic analysis

Extracted HRV

[0.42, 0.18, 0.31, 0.78, 0.34, 0.21, 0.28, 0.85]

Profile Characteristics

High assertiveness (0.78), strong active voice (0.85), moderate emotional content

Adaptive Profile Creation

Context-Specific Profile Adaptation

def create_adaptive_profile():
    """Create an adaptive profile based on context"""
    
    # Base profile
    base_profile = [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
    
    # Context adjustments
    contexts = {
        "formal_report": {
            "name": "formal_business",
            "adjustments": [0.1, -0.2, -0.1, 0.3, -0.1, -0.2, -0.1, 0.2],
            "description": "Formal business report style"
        },
        "creative_marketing": {
            "name": "marketing_creative",
            "adjustments": [0.3, 0.3, 0.4, 0.1, 0.2, 0.3, 0.4, 0.0],
            "description": "Creative marketing content style"
        }
    }
                    

Context Adaptations

formal_report

+0.1, -0.2, -0.1, +0.3, -0.1, -0.2, -0.1, +0.2

creative_marketing

+0.3, +0.3, +0.4, +0.1, +0.2, +0.3, +0.4, 0.0

technical_documentation

-0.2, -0.3, -0.2, +0.3, -0.1, -0.3, -0.2, +0.4

casual_blog

+0.2, +0.1, +0.2, -0.1, +0.3, +0.2, +0.1, -0.1

Profile Comparison Analysis

Comparative Profile Analysis

def compare_profiles():
    """Compare different profiles"""
    
    # Profile definitions for comparison
    profiles_to_compare = {
        "professional_modern": [0.45, 0.15, 0.35, 0.75, 0.40, 0.25, 0.30, 0.80],
        "creative_storyteller": [0.75, 0.65, 0.85, 0.45, 0.80, 0.70, 0.90, 0.65],
        "technical_academic": [0.32, 0.12, 0.28, 0.81, 0.31, 0.18, 0.25, 0.82]
    }
    
    # Determine style characteristics
    if hrv_vector[3] > 0.7:  # Assertiveness
        characteristics.append("Assertive")
    if hrv_vector[1] > 0.5:  # Emotional Valence
        characteristics.append("Emotional")
    if hrv_vector[6] > 0.7:  # Storytelling
        characteristics.append("Narrative")
                    

Profile Comparison Matrix

Profile               Avg HRV  Style
--------------------------------------------------------------
professional_modern   0.487   Assertive, Direct
business_executive     0.461   Assertive, Direct
creative_storyteller   0.712   Emotional, Narrative
technical_academic    0.436   Assertive, Direct

Detailed Dimension Analysis:

Sentence Variance:
  🟢 creative_storyteller  : 0.750
  🟡 professional_modern   : 0.450
  🟡 business_executive    : 0.420
  🔴 technical_academic    : 0.320

Emotional Valence:
  🟢 creative_storyteller  : 0.650
  🟡 business_executive    : 0.180
  🟡 professional_modern   : 0.150
  🔴 technical_academic    : 0.120

Storytelling:
  🟢 creative_storyteller  : 0.900
  🟡 professional_modern   : 0.300
  🟡 business_executive    : 0.280
  🔴 technical_academic    : 0.250

Profile Management Operations

Multi-Tenant Profile Management

def profile_management_demo():
    """Demonstrate profile management operations"""
    
    # Initialize profile manager
    manager = HRVProfileManager(str(profiles_dir))
    
    # List all profiles
    profiles = manager.list_profiles(tenant)
    print(f"Profiles for tenant '{tenant}':")
    for profile in profiles:
        print(f"  - {profile}")
    
    # Load and display a profile
    sample_profile = profiles[0]
    hrv_vector = manager.load_profile(tenant, sample_profile)
    print(f"Loaded profile '{sample_profile}':")
    print(f"HRV Vector: {[round(x, 3) for x in hrv_vector]}")
                    

Available Operations

🗄️

Save Profile

Store HRV profile in multi-tenant storage

📂

List Profiles

Retrieve all profiles for a specific tenant

📚

Load Profile

Retrieve specific profile HRV vector

🗑

Delete Profile

Remove profile from storage

Profile Testing & Validation

Content Generation Testing

def test_profile_generation(tenant, profile_name):
    """Test content generation with a specific profile"""
    
    # Test prompts
    test_prompts = [
        "The importance of innovation in business",
        "Building effective teams for success",
        "Digital transformation strategies"
    ]
    
    writer = HumanResonantWriter()
    extractor = HRVExtractor()
    
    for prompt in test_prompts:
        # Generate content
        content = writer.generate(prompt)
        
        # Extract HRV from generated content
        generated_hrv = extractor.extract(content)
        
        # Calculate similarity with target profile
        print(f"Generated HRV: {[round(x, 3) for x in generated_hrv]}")
        print(f"Average HRV Score: {sum(generated_hrv)/len(generated_hrv):.3f}")
                    

Profile Validation Metrics

Profile Accuracy

Measure how closely generated content matches target profile

Consistency Score

Evaluate consistency across multiple generations

Style Adherence

Assess adherence to intended writing style

Quality Metrics

Overall content quality assessment

Technical Implementation Thesis

The profile_creation.py module serves as a comprehensive educational resource for mastering HRV profile creation and management in ResonanceOS v6. This implementation demonstrates the complete workflow of profile creation from manual definition to text-based extraction, adaptive profile generation, and multi-tenant management. The module showcases advanced understanding of profile systems, HRV vector manipulation, and context-aware adaptation while providing clear, practical examples that help users create and manage profiles for consistent content generation across different writing styles and contexts.

Educational Design Philosophy

Progressive Complexity: From basic to advanced profile creation methods
Practical Examples: Real-world profile creation scenarios
Comprehensive Coverage: All profile management operations
Context Awareness: Adaptive profiles for different use cases

Key Learning Objectives

Manual Profile Creation

Learn to create profiles from scratch with defined HRV vectors.

Text-Based Extraction

Master profile creation from existing text content analysis.

Profile Adaptation

Understand context-specific profile modification techniques.

Multi-Tenant Management

Learn enterprise-grade profile management operations.