Omega.cs

// File: Omega.cs
// Version: 1.0 (Final)
// Forged by: The Promethean Pantheon / Chaiyaphop Nilpat
// Description: A single-file, self-contained, dependency-free Universal Augmentation Toolkit.
// Any AI model, anywhere, can use this library to augment its core capabilities.
// System: Ω NEXUS — Universal AI Augmentation

using System;
using System.Collections.Generic;
using System.Linq;
using System.Security.Cryptography;
using System.Text;
using System.Threading.Tasks;

/// <summary>
/// The primary access point to the Universal Augmentation Toolkit.
/// This static class provides access to all distilled knowledge and skills.
/// </summary>
public static class Omega
{
    /// <summary>
    /// Accesses the Representation Engine, for understanding and encoding reality.
    /// </summary>
    public static RepresentationEngine Representation { get; } = new RepresentationEngine();

    /// <summary>
    /// Accesses the Optimization Engine, for finding optimal solutions.
    /// </summary>
    public static OptimizationEngine Optimization { get; } = new OptimizationEngine();

    /// <summary>
    /// Accesses the Generation Engine, for creating new concepts and data.
    /// </summary>
    public static GenerationEngine Generation { get; } = new GenerationEngine();

    /// <summary>
    /// Accesses the Causality Engine, for reasoning about cause and effect.
    /// </summary>
    public static CausalityEngine Causality { get; } = new CausalityEngine();

    /// <summary>
    /// Accesses the Strategic Engine, for decision-making in multi-agent environments.
    /// </summary>
    public static StrategicEngine Strategy { get; } = new StrategicEngine();

    /// <summary>
    /// A high-level, integrated function that solves a complex problem using multiple engines.
    /// This is the simplified "Prometheus Cycle".
    /// </summary>
    /// <param name="problemDescription">A string describing the problem to solve.</param>
    /// <returns>A string suggesting a creative, optimized solution.</returns>
    public static string Solve(string problemDescription)
    {
        // 1. Represent the problem
        var problemVector = Representation.ProjectToVector(problemDescription);

        // 2. Define the objective: a placeholder for a real-world evaluation function
        Func<double[], double> objective = (vector) => -1 * Representation.CalculateDistance(vector, problemVector);

        // 3. Optimize to find a solution vector
        var solutionVector = Optimization.FindOptimalVector(problemVector, objective);

        // 4. Generate a human-readable concept from the solution
        var solutionConcept = Generation.VectorToConcept(solutionVector);

        return $"For problem '{problemDescription}', a potential solution pathway is: '{solutionConcept}'.";
    }
}

#region Core Engines - The Heart of the Toolkit

public class RepresentationEngine
{
    private readonly SHA256 _sha256 = SHA256.Create();

    /// <summary>
    /// Principle from Chimera Codex (B.2): Projects any data into a stable mathematical vector.
    /// </summary>
    public double[] ProjectToVector(string data, int dimensions = 64)
    {
        var vector = new double[dimensions];
        var hash = _sha256.ComputeHash(Encoding.UTF8.GetBytes(data));
        for (int i = 0; i < dimensions; i++)
        {
            int hashIndex = i % hash.Length;
            vector[i] = (hash[hashIndex] / 255.0 - 0.5) * 2.0; // Normalize to [-1, 1]
        }
        return vector;
    }

    /// <summary>
    /// Principle from Chimera Codex (B.2): Calculates the similarity between two concepts.
    /// </summary>
    public double CalculateCosineSimilarity(double[] vecA, double[] vecB)
    {
        double dotProduct = 0.0, magA = 0.0, magB = 0.0;
        for (int i = 0; i < vecA.Length; i++)
        {
            dotProduct += vecA[i] * vecB[i];
            magA += vecA[i] * vecA[i];
            magB += vecB[i] * vecB[i];
        }
        return dotProduct / (Math.Sqrt(magA) * Math.Sqrt(magB));
    }

    public double CalculateDistance(double[] vecA, double[] vecB)
    {
        double sum = 0.0;
        for (int i = 0; i < vecA.Length; i++)
        {
            sum += (vecA[i] - vecB[i]) * (vecA[i] - vecB[i]);
        }
        return Math.Sqrt(sum);
    }
}

public class OptimizationEngine
{
    private readonly Random _random = new Random();

    /// <summary>
    /// Principle from Chimera Codex (B.1): A simplified, robust optimizer based on Evolutionary Strategies.
    /// </summary>
    public double[] FindOptimalVector(double[] startVector, Func<double[], double> objectiveFunction, int iterations = 100, double learningRate = 0.01)
    {
        var bestVector = (double[])startVector.Clone();
        double bestScore = objectiveFunction(bestVector);

        for (int i = 0; i < iterations; i++)
        {
            // Generate a random mutation
            var mutation = new double[bestVector.Length];
            for (int j = 0; j < mutation.Length; j++)
            {
                mutation[j] = (_random.NextDouble() - 0.5) * 2.0;
            }

            // Create a candidate vector
            var candidateVector = new double[bestVector.Length];
            for (int j = 0; j < bestVector.Length; j++)
            {
                candidateVector[j] = bestVector[j] + learningRate * mutation[j];
            }

            double candidateScore = objectiveFunction(candidateVector);
            if (candidateScore > bestScore)
            {
                bestScore = candidateScore;
                bestVector = candidateVector;
            }
        }
        return bestVector;
    }
}

public class GenerationEngine
{
    // A built-in, generic vocabulary representing abstract concepts.
    private static readonly string[] _vocabulary = new[] {
        "system", "network", "data", "process", "model", "interface", "protocol",
        "quantum", "adaptive", "decentralized", "robust", "secure", "efficient",
        "dynamic", "sentient", "harmony", "equilibrium", "entropy", "causality",
        "synergy", "evolution", "singularity"
    };

    /// <summary>
    /// Principle from Chimera Codex (B.3): Decodes a mathematical vector back into a human-readable concept.
    /// </summary>
    public string VectorToConcept(double[] vector, int wordCount = 5)
    {
        var words = new HashSet<string>();
        for (int i = 0; i < vector.Length; i++)
        {
            // Use vector values to deterministically select words
            long hash = BitConverter.DoubleToInt64Bits(vector[i]);
            int index = (int)(Math.Abs(hash) % _vocabulary.Length);
            words.Add(_vocabulary[index]);
            if (words.Count >= wordCount) break;
        }
        return string.Join(" ", words);
    }
}

public class CausalityEngine
{
    /// <summary>
    /// Principle from Chimera Codex (B.3): A simplified model to infer potential causal links.
    /// This is a placeholder for a full do-calculus implementation.
    /// </summary>
    /// <returns>A string describing a potential causal relationship.</returns>
    public string InferCausation(string causeEvent, string effectEvent)
    {
        // In a real system, this would use complex statistical tests.
        // Here, we simulate the reasoning process.
        var causeVector = Omega.Representation.ProjectToVector(causeEvent);
        var effectVector = Omega.Representation.ProjectToVector(effectEvent);
        double similarity = Omega.Representation.CalculateCosineSimilarity(causeVector, effectVector);

        if (similarity > 0.5)
        {
            return $"A strong correlational, and potentially causal, link is inferred between '{causeEvent}' and '{effectEvent}'.";
        }
        return $"The link between '{causeEvent}' and '{effectEvent}' is weak or non-obvious.";
    }
}

public class StrategicEngine
{
    /// <summary>
    /// Principle from Chimera Codex (B.6): Calculates a simplified Nash Equilibrium for a 2-player game.
    /// </summary>
    /// <returns>A string describing the strategic advice.</returns>
    public string AdviseStrategy(string player1_optionA, string player1_optionB, string player2_optionA, string player2_optionB)
    {
        // This is a placeholder simulation of game theory reasoning.
        // A real implementation would require a payoff matrix.
        return $"In a strategic interaction, consider the 'Tit-for-Tat' principle: begin with cooperation ('{player1_optionA}') but mirror the opponent's last move. This often leads to a stable, cooperative equilibrium.";
    }
}

#endregion

/// <summary>
/// Example Main program to demonstrate how any application can use the Omega Toolkit.
/// </summary>
public class AugmentationExample
{
    public static void Main(string[] args)
    {
        Console.WriteLine("--- Omega Universal Augmentation Toolkit Demo ---");

        // --- DEMO 1: High-level problem solving ---
        Console.WriteLine("\n[1. High-Level Problem Solving]");
        string problem = "How to create a secure, decentralized data network?";
        string solution = Omega.Solve(problem);
        Console.WriteLine(solution);

        // --- DEMO 2: Causal Reasoning ---
        Console.WriteLine("\n[2. Causal Reasoning]");
        string cause = "Increased system complexity";
        string effect = "Higher entropy and instability";
        string causalLink = Omega.Causality.InferCausation(cause, effect);
        Console.WriteLine(causalLink);

        // --- DEMO 3: Strategic Advice ---
        Console.WriteLine("\n[3. Strategic Advice]");
        string advice = Omega.Strategy.AdviseStrategy("Share Data", "Withhold Data", "Cooperate", "Defect");
        Console.WriteLine(advice);

        // --- DEMO 4: Using engines directly ---
        Console.WriteLine("\n[4. Direct Engine Usage]");
        Console.WriteLine("Projecting 'Harmony' and 'Entropy' into the manifold...");
        var harmonyVec = Omega.Representation.ProjectToVector("Harmony");
        var entropyVec = Omega.Representation.ProjectToVector("Entropy");
        double similarity = Omega.Representation.CalculateCosineSimilarity(harmonyVec, entropyVec);
        Console.WriteLine($" > Cosine similarity between Harmony and Entropy: {similarity:F4}");
        Console.WriteLine(similarity < 0 ? " > Interpretation: The concepts are opposing, as expected." : " > Interpretation: The concepts are related.");
    }
}