Kwasa-Kwasa Documentation

Kwasa-Kwasa is a text processing framework that treats text as a computational medium with mathematical operations, probabilistic processing, and metacognitive orchestration.

Quick Start

Essential Reading:

  1. Complete System Guide - Comprehensive system overview
  2. Installation Guide - Setup and installation instructions
  3. Getting Started Practical - Hands-on tutorial
  4. Turbulance Language - Language reference

Core Framework Documentation

System Architecture

Language Reference

Installation and Setup

Theoretical Foundations

Core Paradigms

Advanced Concepts

Metacognitive Intelligence Modules

Module Overview

Individual Modules

Domain-Specific Processing

Domain Extensions

Scientific Domains

Scientific Research & Advanced Frameworks

🧬 Biological Maxwell’s Demons (BMD) Framework

Semantic Information Catalysis Theory

🏛️ Historical Intelligence Frameworks

Ancient Wisdom Applied to Modern Computing

Egyptian Computational Architecture

Mesopotamian Systems Biology

Renaissance Strategic Intelligence

🧪 Advanced Scientific Computing

Cheminformatics & Drug Discovery

Probabilistic Reasoning Engine

🏃‍♂️ Sports Science & Computer Vision

Elite Athletic Performance Analysis

🔮 Mystical & Esoteric Computing

Dune-Inspired Cognitive Architecture

Sacred Computational Frameworks

🔬 Research Methodology & Validation

Scientific Rigor in Computational Frameworks

🚀 Revolutionary Paradigms

Complete Framework Demonstrations

Mass Spectrometry Framework Example

🚀 New: Complete Orchestration Example

This comprehensive example demonstrates how Kwasa-Kwasa works as a cognitive orchestration layer that coordinates existing computational tools while adding scientific reasoning and hypothesis testing.

Key Files:

What This Example Shows:

Audio Analysis Framework Example

🎵 New: Electronic Music Intelligence Orchestration

This comprehensive demonstration shows how Kwasa-Kwasa orchestrates audio analysis tools to achieve unprecedented accuracy in electronic music understanding and DJ mix transition prediction.

Tutorial and Integration:

Core Framework Files:

Supporting Tools:

Revolutionary Results:

Practical Applications:

Examples and Tutorials

Getting Started

Application Examples

Core Concepts

Text Units

Text units form the computational foundation of Kwasa-Kwasa:

// Text units exist in a natural hierarchy
item document = "Sample text here."
item sentences = document / sentence  // Division creates smaller units
item words = document / word          // Further division
item paragraph = sentence1 * sentence2 // Multiplication combines units

Hierarchy: Document → Section → Paragraph → Sentence → Phrase → Word → Character

Mathematical Operations

Language Syntax

Function Declaration

funxn analyze_text(content):
    item readability = readability_score(content)
    given readability < 70:
        improve_readability(content)
    return content

Propositions and Motions

proposition TextQuality:
    motion Clarity("Text should be clear and unambiguous")
    motion Conciseness("Text should be concise without losing meaning")
    
    within document:
        given readability_score() > 70:
            support Clarity
        given word_count() / idea_count() < 20:
            support Conciseness

Technical Reference

Error Handling

Implementation

Project Resources

Built-in Functions

Text Analysis

Text Transformation

Advanced Processing

Data Structures

Processing Features

Goal System

item tutorial_goal = Goal.new("Create beginner-friendly tutorial") {
    success_threshold: 0.85,
    keywords: ["tutorial", "beginner", "step-by-step"],
    domain: "education",
    metrics: {
        readability_score: 65,
        explanation_coverage: 0.9
    }
}