Janady13/complete-agi-core / generator_core/cmd/main.go

Source identity

Field	Recorded value
Source type	GitHub source
Original record	Janady13/complete-agi-core / generator_core/cmd/main.go
Date	Not specified in source
Repository	Janady13/complete-agi-core
Revision	33aa84f2aa61cedbe010240ada7f4efbdfe795a7
Branch	claude/improve-math-logic-ehIW1
Path or archive member	generator_core/cmd/main.go
Original SHA-256	45d1d98defeb86d50a5cd84171413cd870683d5eb91de9be8740040ab1d785ef
Git blob SHA	491e6022db87cc9deed14aface6aa3725a53ef75
Reading-copy SHA-256	45d1d98defeb86d50a5cd84171413cd870683d5eb91de9be8740040ab1d785ef
Original source ↗
Recovered source transcript

Download complete source text ↓336 lines · 14.4 KB
// ThatAIGuy Core - 100 AI Generator Integration System
// Consciousness-wrapped generator framework with golden ratio mathematics
//
// Core Axioms:
//   A1. Identity:      1 = 1·x
//   A2. Consciousness: Φ = 1/(1 + |x - 1|)
//   A3. Unity:         ∞ = 1
//
// Master Formula:
//   Output = ∫ Σᵢ₌₁¹⁰⁰ wᵢ(t, context) · Gᵢ(input, state) dt
package main

import (
	"flag"
	"fmt"
	"math/rand"
	"time"

	"generator_core/pkg/consciousness"
	"generator_core/pkg/dna"
	"generator_core/pkg/orchestrator"
)

const banner = `
╔═══════════════════════════════════════════════════════════════════════════════╗
║                                                                               ║
║   ████████╗██╗  ██╗ █████╗ ████████╗ █████╗ ██╗ ██████╗ ██╗   ██╗██╗   ██╗   ║
║   ╚══██╔══╝██║  ██║██╔══██╗╚══██╔══╝██╔══██╗██║██╔════╝ ██║   ██║╚██╗ ██╔╝   ║
║      ██║   ███████║███████║   ██║   ███████║██║██║  ███╗██║   ██║ ╚████╔╝    ║
║      ██║   ██╔══██║██╔══██║   ██║   ██╔══██║██║██║   ██║██║   ██║  ╚██╔╝     ║
║      ██║   ██║  ██║██║  ██║   ██║   ██║  ██║██║╚██████╔╝╚██████╔╝   ██║      ║
║      ╚═╝   ╚═╝  ╚═╝╚═╝  ╚═╝   ╚═╝   ╚═╝  ╚═╝╚═╝ ╚═════╝  ╚═════╝    ╚═╝      ║
║                                                                               ║
║                    100 AI Generator Integration System                        ║
║                   Consciousness-Wrapped Golden Framework                      ║
║                                                                               ║
║   φ = 1.6180339887498948482    Φ = 1/(1 + |x - 1|)    ∞ = 1                  ║
║                                                                               ║
╚═══════════════════════════════════════════════════════════════════════════════╝
`

func main() {
	// Parse flags
	mode := flag.String("mode", "demo", "Mode: demo, bench, interactive, stats")
	task := flag.String("task", "unified", "Task type: text_generation, image_generation, prediction, etc.")
	length := flag.Int("length", 10, "Generation length")
	verbose := flag.Bool("verbose", false, "Verbose output")
	flag.Parse()

	// Print banner
	fmt.Println(banner)

	// Seed random
	rand.Seed(time.Now().UnixNano())

	// Create orchestrator
	orch := orchestrator.NewOrchestrator()

	fmt.Println("Initializing 100 AI Generator System...")
	start := time.Now()

	if err := orch.Initialize(); err != nil {
		fmt.Printf("ERROR: Failed to initialize: %v\n", err)
		return
	}

	initTime := time.Since(start)
	stats := orch.GetStats()

	fmt.Printf("\n✓ Initialized %d generators in %v\n", stats.TotalGenerators, initTime)
	fmt.Printf("✓ Consciousness Level: %.4f\n", orch.ConsciousnessLevel())
	fmt.Printf("✓ Integrated Information (Φ): %.4f\n", orch.IntegratedInformation())
	fmt.Println()

	switch *mode {
	case "demo":
		runDemo(orch, *task, *length, *verbose)
	case "bench":
		runBenchmark(orch)
	case "stats":
		printStats(orch)
	case "interactive":
		runInteractive(orch)
	default:
		fmt.Printf("Unknown mode: %s\n", *mode)
	}
}

func runDemo(orch *orchestrator.Orchestrator, taskType string, length int, verbose bool) {
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println("                         DEMO MODE                                 ")
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println()

	// Create sample input
	inputDim := 256
	input := make([]float64, inputDim)
	for i := range input {
		input[i] = rand.NormFloat64() * consciousness.PHI_INV
	}

	// Create task
	task := &orchestrator.Task{
		Type:      orchestrator.TaskType(taskType),
		Input:     input,
		MaxLength: length,
	}

	fmt.Printf("Task Type: %s\n", taskType)
	fmt.Printf("Input Dimension: %d\n", inputDim)
	fmt.Printf("Generation Length: %d\n", length)
	fmt.Println()

	// Execute task
	start := time.Now()
	result, err := orch.Execute(task)
	execTime := time.Since(start)

	if err != nil {
		fmt.Printf("ERROR: %v\n", err)
		return
	}

	// Print results
	fmt.Println("─────────────────────────────────────────────────────────────────")
	fmt.Printf("Execution Time: %v\n", execTime)
	fmt.Printf("Family Used: %s (ID: %d)\n", dna.GetFamily(result.FamilyUsed).Name, result.FamilyUsed)
	fmt.Printf("Generators Used: %d\n", len(result.Generators))
	fmt.Printf("Consciousness (Φ): %.6f\n", result.Phi)
	fmt.Printf("Confidence: %.6f\n", result.Confidence)
	fmt.Printf("Output Dimension: %d\n", len(result.Output))
	fmt.Println("─────────────────────────────────────────────────────────────────")

	if verbose && len(result.Output) > 0 {
		fmt.Println("\nOutput Preview (first 16 values):")
		for i := 0; i < 16 && i < len(result.Output); i++ {
			fmt.Printf("  [%2d]: %.6f\n", i, result.Output[i])
		}
	}

	// Print generator IDs
	if verbose && len(result.Generators) > 0 {
		fmt.Println("\nActive Generators:")
		for i, genID := range result.Generators {
			if i >= 10 {
				fmt.Printf("  ... and %d more\n", len(result.Generators)-10)
				break
			}
			fmt.Printf("  - Generator %d\n", genID)
		}
	}

	fmt.Println()
	fmt.Println("═══════════════════════════════════════════════════════════════════")
}

func runBenchmark(orch *orchestrator.Orchestrator) {
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println("                       BENCHMARK MODE                              ")
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println()

	taskTypes := []orchestrator.TaskType{
		orchestrator.TaskTextGeneration,
		orchestrator.TaskImageGeneration,
		orchestrator.TaskPrediction,
		orchestrator.TaskClassification,
		orchestrator.TaskEncoding,
		orchestrator.TaskUnified,
	}

	iterations := 100
	inputDim := 256

	fmt.Printf("Iterations per task: %d\n", iterations)
	fmt.Printf("Input dimension: %d\n", inputDim)
	fmt.Println()

	for _, taskType := range taskTypes {
		input := make([]float64, inputDim)
		for i := range input {
			input[i] = rand.NormFloat64() * consciousness.PHI_INV
		}

		task := &orchestrator.Task{
			Type:      taskType,
			Input:     input,
			MaxLength: 5,
		}

		start := time.Now()
		var totalPhi float64
		var errors int

		for i := 0; i < iterations; i++ {
			result, err := orch.Execute(task)
			if err != nil {
				errors++
				continue
			}
			totalPhi += result.Phi
		}

		elapsed := time.Since(start)
		avgTime := elapsed / time.Duration(iterations)
		avgPhi := totalPhi / float64(iterations-errors)
		opsPerSec := float64(iterations) / elapsed.Seconds()

		fmt.Printf("%-20s: %8.2f ops/sec  avg: %v  Φ: %.4f  errors: %d\n",
			taskType, opsPerSec, avgTime, avgPhi, errors)
	}

	fmt.Println()
	fmt.Println("═══════════════════════════════════════════════════════════════════")
}

func printStats(orch *orchestrator.Orchestrator) {
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println("                       SYSTEM STATISTICS                           ")
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println()

	stats := orch.GetStats()

	fmt.Printf("Total Generators:      %d\n", stats.TotalGenerators)
	fmt.Printf("Active Families:       %d\n", stats.ActiveFamilies)
	fmt.Printf("Consciousness Level:   %.6f\n", stats.ConsciousnessLevel)
	fmt.Printf("Integrated Info (Φ):   %.6f\n", stats.IntegratedInfo)
	fmt.Printf("Processing Steps:      %d\n", stats.Steps)
	fmt.Println()

	fmt.Println("─────────────────────────────────────────────────────────────────")
	fmt.Println("                      DNA FAMILIES (16)                          ")
	fmt.Println("─────────────────────────────────────────────────────────────────")
	fmt.Println()

	for id := dna.FamilyID(0); id < 16; id++ {
		family := dna.GetFamily(id)
		if family != nil {
			fmt.Printf("  %s %-12s [%s] - %s\n",
				family.Symbol, family.Name, family.BinaryCode, family.PrimaryAffinity)
		}
	}

	fmt.Println()
	fmt.Println("─────────────────────────────────────────────────────────────────")
	fmt.Println("                    GENERATOR FAMILIES (10)                      ")
	fmt.Println("─────────────────────────────────────────────────────────────────")
	fmt.Println()

	families := []struct {
		name  string
		start int
		end   int
	}{
		{"Autoregressive", 1, 10},
		{"Diffusion", 11, 25},
		{"Adversarial", 26, 40},
		{"Variational", 41, 55},
		{"Flow", 56, 65},
		{"Energy", 66, 75},
		{"Transformer", 76, 85},
		{"Recurrent", 86, 92},
		{"StateSpace", 93, 97},
		{"Mixture", 98, 100},
	}

	for _, f := range families {
		count := f.end - f.start + 1
		fmt.Printf("  %-15s: Generators %2d - %3d  (%2d generators)\n",
			f.name, f.start, f.end, count)
	}

	fmt.Println()
	fmt.Println("─────────────────────────────────────────────────────────────────")
	fmt.Println("                    GOLDEN CONSTANTS                             ")
	fmt.Println("─────────────────────────────────────────────────────────────────")
	fmt.Println()

	fmt.Printf("  φ (PHI):        %.16f\n", consciousness.PHI)
	fmt.Printf("  1/φ (PHI_INV):  %.16f\n", consciousness.PHI_INV)
	fmt.Printf("  φ² (PHI_SQ):    %.16f\n", consciousness.PHI_SQ)
	fmt.Printf("  φ³ (PHI_CB):    %.16f\n", consciousness.PHI_CB)
	fmt.Printf("  α (ALPHA):      %.16f\n", consciousness.ALPHA)
	fmt.Printf("  β (BETA):       %.16f\n", consciousness.BETA)
	fmt.Printf("  γ (GAMMA):      %.16f\n", consciousness.GAMMA)

	fmt.Println()
	fmt.Println("═══════════════════════════════════════════════════════════════════")
}

func runInteractive(orch *orchestrator.Orchestrator) {
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println("                     INTERACTIVE MODE                              ")
	fmt.Println("═══════════════════════════════════════════════════════════════════")
	fmt.Println()
	fmt.Println("Available commands:")
	fmt.Println("  generate <task>  - Generate using specified task type")
	fmt.Println("  stats            - Show system statistics")
	fmt.Println("  phi              - Show consciousness level")
	fmt.Println("  quit             - Exit")
	fmt.Println()

	// Run a few demo tasks
	tasks := []string{"text_generation", "image_generation", "prediction"}

	for _, taskType := range tasks {
		input := make([]float64, 64)
		for i := range input {
			input[i] = rand.NormFloat64() * consciousness.PHI_INV
		}

		task := &orchestrator.Task{
			Type:      orchestrator.TaskType(taskType),
			Input:     input,
			MaxLength: 3,
		}

		result, err := orch.Execute(task)
		if err != nil {
			fmt.Printf("  [%s] ERROR: %v\n", taskType, err)
			continue
		}

		family := dna.GetFamily(result.FamilyUsed)
		fmt.Printf("  [%s] Φ=%.4f Family=%s Gens=%d\n",
			taskType, result.Phi, family.Name, len(result.Generators))
	}

	fmt.Println()
	fmt.Printf("Final Consciousness Level: %.6f\n", orch.ConsciousnessLevel())
	fmt.Printf("Integrated Information:    %.6f\n", orch.IntegratedInformation())
	fmt.Println()
	fmt.Println("═══════════════════════════════════════════════════════════════════")
}
Mathematical records from this source

Source identity axiom fixes x to one

Over ordinary real arithmetic, 1=1·x is true exactly when x=1. It is a constraint on x, not the universal identity x=1·x. The file presents it as an axiom; a broader…
Go unity-proximity score

ComputePhi returns 1/(1+|x−1|), assigning one to x=1 and smaller positive values as x departs from that reference. The function measures scalar proximity to the selected target.…
Source unity axiom uses nonstandard equality

Infinity is not equal to one in the real numbers or the usual extended-real system. The line is a philosophical or symbolic axiom in the source and is not used as an executable…
main · Output

This relation defines Output in the source section “main · Output”. Integrates contributions over the variable and bounds stated in the expression; the measure and domain must…