#!/usr/bin/env elixir

# Load the project dependencies
Mix.install([
  {:jason, "~> 1.4"}
])

# Start the required applications
Application.ensure_all_started(:inets)
Application.ensure_all_started(:ssl)

# Load DSPy modules
Code.eval_file("lib/dspy.ex")

# Unlimited Simple Challenge Generator (Fixed Version)
# Continuously generates problems with increasing difficulty

defmodule UnlimitedSimpleChallenges do
  @moduledoc """
  Unlimited challenge generator that creates increasingly difficult problems
  across 8 reasoning levels and runs indefinitely.
  """

  def start do
    IO.puts("🚀 Starting ADVANCED Unlimited Challenge Generator")
    IO.puts("🧠 Powered by gpt-4.1-mini Model")
    IO.puts("♾️  Generating sophisticated problems with exponential difficulty scaling")
    IO.puts("🎯 Advanced multi-dimensional reasoning across 8 cognitive levels")
    IO.puts("📈 Infinite scalability - press Ctrl+C to stop")
    IO.puts("🔧 Configuring Advanced DSPy Pipeline...\n")
    
    # Configure DSPy
    case configure_dspy() do
      :ok ->
        IO.puts("✅ DSPy configured successfully!\n")
        
        metrics = %{
          total: 0,
          successful: 0,
          errors: 0,
          level_counts: %{1 => 0, 2 => 0, 3 => 0, 4 => 0, 5 => 0, 6 => 0, 7 => 0, 8 => 0},
          level_successes: %{1 => 0, 2 => 0, 3 => 0, 4 => 0, 5 => 0, 6 => 0, 7 => 0, 8 => 0},
          difficulty_multiplier: 1.0,
          start_time: DateTime.utc_now()
        }
        
        run_loop(metrics)
        
      {:error, reason} ->
        IO.puts("❌ Failed to configure DSPy: #{reason}")
        IO.puts("Please set OPENAI_API_KEY environment variable.")
        System.halt(1)
    end
  end
  
  defp configure_dspy do
    # Start DSPy.Settings GenServer if not already started
    case Process.whereis(Dspy.Settings) do
      nil -> Dspy.Settings.start_link()
      _pid -> {:ok, :already_started}
    end
    
    # Get API key
    api_key = System.get_env("OPENAI_API_KEY")
    if api_key do
      # Create flagship GPT-4.1 client for maximum capability
      client = Dspy.LM.OpenAI.new([
        api_key: api_key,
        model: "gpt-4.1-mini",
        timeout: 120_000  # 2 minutes for complex reasoning
      ])
      
      # Configure DSPy settings with advanced parameters
      Dspy.Settings.configure([
        lm: client,
        max_tokens: 4096,        # More tokens for detailed reasoning
        temperature: 0.7,        # Balanced creativity and consistency
        cache: true              # Cache responses for efficiency
      ])
      
      IO.puts("   🧠 Model: gpt-4.1-mini")
      IO.puts("   ⚡ Max Tokens: 4096")
      IO.puts("   🌡️  Temperature: 0.7")
      IO.puts("   ⏱️  Timeout: 120s")
      :ok
    else
      {:error, "OPENAI_API_KEY not set"}
    end
  end

  defp run_loop(metrics) do
    # Select level (progressive unlock)
    level = select_level(metrics.total)
    
    # Generate challenge
    challenge = generate_challenge(level, metrics.difficulty_multiplier)
    
    # Display challenge
    display_challenge(challenge, metrics)
    
    # Execute challenge with appropriate DSPy module
    result = execute_challenge(challenge)
    
    # Display result
    display_result(result, challenge)
    
    # Update metrics
    updated_metrics = update_metrics(metrics, level, result)
    
    # Display progress
    display_progress(updated_metrics)
    
    # Continue
    Process.sleep(3000)
    run_loop(updated_metrics)
  end

  defp select_level(total) do
    cond do
      total < 10 -> Enum.random([1, 2])
      total < 25 -> Enum.random([1, 2, 3])
      total < 50 -> Enum.random([1, 2, 3, 4])
      total < 100 -> Enum.random([1, 2, 3, 4, 5, 6])
      total < 200 -> Enum.random([1, 2, 3, 4, 5, 6, 7])
      true -> Enum.random([1, 2, 3, 4, 5, 6, 7, 8])
    end
  end

  defp generate_challenge(level, difficulty) do
    template = get_template(level)
    problem = generate_problem(template, difficulty)
    
    %{
      level: level,
      problem: problem,
      difficulty: round(level * 10 * difficulty),
      timestamp: DateTime.utc_now()
    }
  end

  defp get_template(level) do
    templates = %{
      1 => [
        "What is {a} + {b}?",
        "What is the capital of {country}?",
        "How many days in {month}?",
        "What color is {object}?",
        "What year was {invention} invented?"
      ],
      2 => [
        "If {person} has {amount1} apples and buys {amount2} more, then gives away {amount3}, how many are left?",
        "A train travels {distance} km at {speed} km/h. How long does the journey take?",
        "If {workers} people can complete a job in {time} hours, how long for {new_workers} people?",
        "Calculate the area of a rectangle {length}m by {width}m, then add {extra} square meters.",
        "You invest ${principal} at {rate}% interest for {years} years. What's the final amount?"
      ],
      3 => [
        "Solve x² - {a}x + {b} = 0 using multiple methods and verify consistency.",
        "Find the limit of ({numerator})/(x² + {denominator}) as x approaches infinity using different techniques.",
        "Calculate ∫({function}) dx from {start} to {end} using multiple integration methods.",
        "Determine if the series Σ(1/(n^{power} + {constant})) converges using different tests.",
        "Find max/min of f(x,y) = {function} subject to constraint {constraint} = 0."
      ],
      4 => [
        "{company} faces {crisis} with ${budget} budget. Choose between {option1}, {option2}, {option3}. Analyze and recommend.",
        "City planning: Build {project} with ${cost} budget while balancing {interest1}, {interest2}, {interest3}.",
        "{organization} must implement {change} while maintaining {operations}. Create implementation plan.",
        "Healthcare decision: Choose {treatment1} vs {treatment2} considering {factors}. Provide recommendation.",
        "Investment strategy: Allocate ${portfolio} across {sectors} considering {risks} and {opportunities}."
      ],
      5 => [
        "AI facial recognition for missing children vs privacy rights. Address ethical concerns while considering {stakeholder1}, {stakeholder2}, {stakeholder3}.",
        "Autonomous vehicle must choose between {scenario1} and {scenario2} in emergency. Design ethical decision framework.",
        "Social media platform handling {content_issue} across cultures with different values. Balance {principle1} vs {principle2}.",
        "Resource allocation during crisis: distribute {resource} between {need1}, {need2}, {need3} fairly.",
        "AI hiring system showing bias against {group}. Fix while maintaining {requirement1} and {requirement2}."
      ],
      6 => [
        "Analyze relationship between {variable1} and {variable2} in {domain}. Design experiments, collect data, determine {relationship_type}.",
        "Build predictive model for {outcome} using {input1}, {input2}, {input3}. Compare algorithms and validate.",
        "Study {phenomenon} using computational methods. Generate hypotheses, design experiments, analyze results.",
        "Optimize {system} with constraints {constraint1}, {constraint2}. Implement multiple approaches and compare.",
        "Simulate {complex_system} behavior under {condition1}, {condition2}. Study emergent patterns."
      ],
      7 => [
        "Design innovative solution to reduce {waste_type} in {industry} while creating value for all stakeholders.",
        "Invent {technology} that revolutionizes {domain} by combining {approach1}, {approach2}, {novel_element}.",
        "Create {art_form} that teaches {concept} to {audience} using {medium1}, {medium2}, {innovation}.",
        "Design {game} that develops {skill} through {mechanic1}, {mechanic2} while maintaining engagement.",
        "Develop {platform} enabling {activity} between {group1}, {group2}, {group3} with {innovation_factor}."
      ],
      8 => [
        "Design messaging platform for {scale} users with {security}, {performance}, {reliability}. Coordinate {expert1}, {expert2}, {expert3}, {expert4}.",
        "Build {complex_system} for {critical_domain} requiring {domain1}, {domain2}, {domain3} expertise. Address {challenge1}, {challenge2}.",
        "Solve {global_problem} integrating {perspective1}, {perspective2}, {perspective3}, {perspective4} viewpoints.",
        "Create {transformation} strategy requiring {change_type1}, {change_type2}, {change_type3} coordination.",
        "Develop {innovation} combining {field1}, {field2}, {field3} to address {multifaceted_challenge}."
      ]
    }
    
    Enum.random(templates[level])
  end

  defp generate_problem(template, difficulty) do
    # Extract variables and substitute
    variables = Regex.scan(~r/\{(\w+)\}/, template, capture: :all_but_first)
                |> List.flatten()
                |> Enum.uniq()
    
    substitutions = Enum.map(variables, fn var ->
      {var, generate_value(var, difficulty)}
    end)
    
    Enum.reduce(substitutions, template, fn {var, value}, text ->
      String.replace(text, "{#{var}}", to_string(value))
    end)
  end

  defp generate_value(var, difficulty) do
    multiplier = max(1, round(difficulty))
    
    cond do
      var in ["a", "b", "amount1", "amount2", "amount3", "numerator", "denominator", "power", "constant", "start", "end", "extra"] ->
        Enum.random(1..20) * multiplier
      
      var == "country" ->
        Enum.random(["Japan", "Brazil", "Germany", "Australia", "Canada", "India"])
      
      var == "month" ->
        Enum.random(["January", "February", "March", "April", "May", "June"])
      
      var == "object" ->
        Enum.random(["sky", "grass", "sun", "ocean", "rose", "snow"])
      
      var == "invention" ->
        Enum.random(["telephone", "computer", "airplane", "television", "internet"])
      
      var == "person" ->
        Enum.random(["Alice", "Bob", "Charlie", "Diana", "Eve", "Frank"])
      
      var in ["distance", "length", "width"] ->
        Enum.random(10..100) * multiplier
      
      var in ["speed", "rate"] ->
        Enum.random(20..80)
      
      var in ["time", "years"] ->
        Enum.random(2..10)
      
      var in ["workers", "new_workers"] ->
        Enum.random(2..12)
      
      var in ["principal", "budget", "cost", "portfolio"] ->
        amounts = [10000, 50000, 100000, 500000, 1000000]
        Enum.random(amounts) * multiplier
      
      var == "company" ->
        Enum.random(["TechCorp", "GlobalSoft", "InnovateCo", "FutureTech"])
      
      var == "crisis" ->
        Enum.random(["declining profits", "market disruption", "regulatory changes", "supply shortage"])
      
      String.contains?(var, "option") ->
        Enum.random(["cost reduction", "market expansion", "product innovation", "strategic partnership"])
      
      var == "organization" ->
        Enum.random(["university", "hospital", "government agency", "corporation"])
      
      var == "change" ->
        Enum.random(["digital transformation", "process automation", "cultural shift", "system upgrade"])
      
      var == "operations" ->
        Enum.random(["quality standards", "customer service", "regulatory compliance", "budget constraints"])
      
      String.contains?(var, "treatment") ->
        Enum.random(["surgical intervention", "medication therapy", "lifestyle changes", "monitoring protocol"])
      
      var == "factors" ->
        "patient age, medical history, treatment costs, success rates"
      
      String.contains?(var, "stakeholder") ->
        Enum.random(["parents", "privacy advocates", "law enforcement", "technology companies", "civil rights groups"])
      
      String.contains?(var, "scenario") ->
        Enum.random(["pedestrian safety", "passenger protection", "property damage", "traffic flow"])
      
      var == "content_issue" ->
        Enum.random(["hate speech", "misinformation", "political content", "cultural sensitivity"])
      
      String.contains?(var, "principle") ->
        Enum.random(["free speech", "user safety", "cultural respect", "platform integrity"])
      
      var == "resource" ->
        Enum.random(["medical supplies", "funding", "personnel", "equipment", "food aid"])
      
      String.contains?(var, "need") ->
        Enum.random(["emergency response", "long-term recovery", "prevention", "research", "infrastructure"])
      
      var == "group" ->
        Enum.random(["women", "minorities", "older workers", "recent graduates", "international candidates"])
      
      String.contains?(var, "requirement") ->
        Enum.random(["job relevance", "legal compliance", "efficiency", "fairness", "accuracy"])
      
      String.contains?(var, "variable") ->
        Enum.random(["temperature", "pressure", "concentration", "time", "frequency", "voltage"])
      
      var == "domain" ->
        Enum.random(["climate science", "neuroscience", "economics", "biology", "physics", "chemistry"])
      
      String.contains?(var, "input") ->
        Enum.random(["sensor data", "user behavior", "market conditions", "environmental factors"])
      
      var == "outcome" ->
        Enum.random(["system performance", "user satisfaction", "energy consumption", "success rate"])
      
      var == "relationship_type" ->
        Enum.random(["linear", "exponential", "logarithmic", "polynomial", "inverse"])
      
      var == "phenomenon" ->
        Enum.random(["neural plasticity", "market volatility", "ecosystem dynamics", "social behavior"])
      
      var == "system" ->
        Enum.random(["traffic network", "power grid", "supply chain", "communication system"])
      
      String.contains?(var, "constraint") ->
        Enum.random(["budget limit", "time deadline", "resource availability", "regulatory requirement"])
      
      var == "complex_system" ->
        Enum.random(["urban ecosystem", "financial market", "social network", "biological system"])
      
      String.contains?(var, "condition") ->
        Enum.random(["high stress", "resource scarcity", "rapid change", "external pressure"])
      
      var == "waste_type" ->
        Enum.random(["food waste", "plastic waste", "energy waste", "water waste", "electronic waste"])
      
      var == "industry" ->
        Enum.random(["restaurant", "manufacturing", "healthcare", "education", "technology"])
      
      var == "technology" ->
        Enum.random(["AI assistant", "renewable energy", "transportation", "communication", "medical device"])
      
      String.contains?(var, "approach") ->
        Enum.random(["biomimetic design", "circular economy", "collaborative platform", "adaptive system"])
      
      var == "novel_element" ->
        Enum.random(["quantum computing", "blockchain", "nanotechnology", "biotechnology"])
      
      var == "art_form" ->
        Enum.random(["interactive installation", "virtual reality", "augmented reality", "multimedia performance"])
      
      var == "concept" ->
        Enum.random(["sustainability", "empathy", "critical thinking", "collaboration", "innovation"])
      
      var == "audience" ->
        Enum.random(["children", "teenagers", "adults", "seniors", "professionals"])
      
      String.contains?(var, "medium") ->
        Enum.random(["visual", "auditory", "tactile", "digital", "physical"])
      
      var == "innovation" ->
        Enum.random(["gamification", "personalization", "social learning", "adaptive feedback"])
      
      var == "game" ->
        Enum.random(["puzzle game", "strategy game", "simulation", "role-playing", "cooperative game"])
      
      var == "skill" ->
        Enum.random(["problem-solving", "leadership", "communication", "creativity", "teamwork"])
      
      String.contains?(var, "mechanic") ->
        Enum.random(["progression system", "collaboration tools", "feedback loops", "challenge scaling"])
      
      var == "platform" ->
        Enum.random(["collaboration hub", "learning environment", "creative workspace", "innovation lab"])
      
      var == "activity" ->
        Enum.random(["knowledge sharing", "project collaboration", "skill development", "creative work"])
      
      String.contains?(var, "group") ->
        Enum.random(["researchers", "students", "professionals", "artists", "entrepreneurs"])
      
      var == "innovation_factor" ->
        Enum.random(["AI assistance", "blockchain verification", "VR collaboration", "real-time analytics"])
      
      var == "scale" ->
        scales = ["100M", "500M", "1B", "5B"]
        scale = Enum.random(scales)
        if multiplier > 1, do: "#{multiplier}#{scale}", else: scale
      
      String.contains?(var, "security") ->
        Enum.random(["end-to-end encryption", "zero-trust architecture", "quantum-safe crypto"])
      
      String.contains?(var, "performance") ->
        Enum.random(["sub-second latency", "99.99% uptime", "infinite scalability"])
      
      String.contains?(var, "reliability") ->
        Enum.random(["fault tolerance", "automatic recovery", "disaster resilience"])
      
      String.contains?(var, "expert") ->
        Enum.random(["system architect", "security specialist", "performance engineer", "reliability expert", "UX designer"])
      
      var == "critical_domain" ->
        Enum.random(["healthcare", "finance", "transportation", "energy", "defense"])
      
      var == "global_problem" ->
        Enum.random(["climate change", "poverty", "disease", "inequality", "conflict"])
      
      String.contains?(var, "perspective") ->
        Enum.random(["scientific", "economic", "social", "political", "technological", "environmental"])
      
      var == "transformation" ->
        Enum.random(["digital transformation", "organizational change", "cultural evolution", "system modernization"])
      
      String.contains?(var, "change_type") ->
        Enum.random(["process redesign", "technology adoption", "skill development", "culture change"])
      
      String.contains?(var, "field") ->
        Enum.random(["artificial intelligence", "biotechnology", "nanotechnology", "quantum computing"])
      
      var == "multifaceted_challenge" ->
        Enum.random(["sustainable development", "aging population", "urbanization", "resource depletion"])
      
      String.contains?(var, "interest") ->
        Enum.random(["economic growth", "environmental protection", "social equity", "public safety"])
      
      var == "project" ->
        Enum.random(["highway", "park", "hospital", "school", "housing complex"])
      
      var == "sectors" ->
        "technology, healthcare, finance, real estate"
      
      var == "risks" ->
        "market volatility, regulatory changes, economic downturns"
      
      var == "opportunities" ->
        "emerging markets, technological innovation, changing demographics"
      
      var == "function" ->
        Enum.random(["x²", "sin(x)", "ln(x)", "e^x", "x³"])
      
      String.contains?(var, "challenge") ->
        Enum.random(["scalability", "integration", "security", "performance", "usability"])
      
      # Default case
      true ->
        "#{var}_#{:rand.uniform(1000)}"
    end
  end

  defp execute_challenge(challenge) do
    IO.puts("🔄 Executing with GPT-4.1 DSPy Pipeline...")
    start_time = System.monotonic_time(:millisecond)
    
    case challenge.level do
      1 ->
        # Enhanced factual reasoning with detailed signature
        signature = Dspy.Signature.new("question -> detailed_analysis, answer, confidence_score")
        predictor = Dspy.Predict.new(signature)
        
        try do
          result = Dspy.Module.forward(predictor, %{question: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Enhanced Dspy.Predict", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Enhanced Dspy.Predict", 0}
        end
        
      2 ->
        # Advanced chain of thought with step-by-step verification
        signature = Dspy.Signature.new("problem -> step_by_step_reasoning, mathematical_work, verification, final_answer, confidence")
        cot = Dspy.ChainOfThought.new(signature)
        
        try do
          result = Dspy.Module.forward(cot, %{problem: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Advanced Dspy.ChainOfThought", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Advanced Dspy.ChainOfThought", 0}
        end
        
      3 ->
        # Enhanced self-consistency with multiple reasoning paths
        signature = Dspy.Signature.new("problem -> methodology, solution_path, mathematical_proof, cross_verification, final_solution")
        self_consistency = Dspy.SelfConsistency.new(signature, num_samples: 5)
        
        try do
          result = Dspy.Module.forward(self_consistency, %{problem: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Enhanced Dspy.SelfConsistency", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Enhanced Dspy.SelfConsistency", 0}
        end
        
      4 ->
        # Sophisticated multi-step strategic analysis
        steps = [
          %{name: "problem_decomposition", signature: Dspy.Signature.new("complex_problem -> problem_breakdown, key_constraints, stakeholder_analysis")},
          %{name: "strategic_options", signature: Dspy.Signature.new("complex_problem, problem_breakdown, key_constraints, stakeholder_analysis -> strategic_options, risk_assessment, opportunity_analysis")},
          %{name: "implementation_plan", signature: Dspy.Signature.new("complex_problem, strategic_options, risk_assessment -> implementation_roadmap, success_metrics, contingency_plans")},
          %{name: "final_recommendation", signature: Dspy.Signature.new("complex_problem, strategic_options, implementation_roadmap -> executive_summary, recommended_action, justification, expected_outcomes")}
        ]
        multi_step = Dspy.MultiStep.new(steps)
        
        try do
          result = Dspy.Module.forward(multi_step, %{complex_problem: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Strategic Dspy.MultiStep", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Strategic Dspy.MultiStep", 0}
        end
        
      5 ->
        # Advanced ethical reasoning with multi-stakeholder analysis
        signature = Dspy.Signature.new("ethical_dilemma -> stakeholder_impact_analysis, ethical_frameworks_applied, moral_reasoning_chains, potential_consequences, ethical_recommendation, implementation_guidelines")
        constraints = [
          fn _input, output -> String.length(Map.get(output, :ethical_frameworks_applied, "")) > 200 end,
          fn _input, output -> String.contains?(Map.get(output, :moral_reasoning_chains, ""), "utilitarian") end,
          fn _input, output -> String.contains?(Map.get(output, :stakeholder_impact_analysis, ""), "stakeholder") end,
          fn _input, output -> String.length(Map.get(output, :implementation_guidelines, "")) > 150 end
        ]
        backtracking = Dspy.AdaptiveBacktracking.new(signature, constraints: constraints, max_attempts: 5)
        
        try do
          result = Dspy.Module.forward(backtracking, %{ethical_dilemma: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Advanced Ethical Dspy.AdaptiveBacktracking", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Advanced Ethical Dspy.AdaptiveBacktracking", 0}
        end
        
      6 ->
        # Sophisticated scientific analysis with computational modeling
        signature = Dspy.Signature.new("research_question -> literature_review, hypothesis_formation, experimental_design, data_analysis_plan, computational_model, statistical_methods, expected_results, validation_strategy, scientific_conclusion")
        pot = Dspy.ProgramOfThoughts.new(signature, executor: :elixir)
        
        try do
          result = Dspy.Module.forward(pot, %{research_question: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Scientific Dspy.ProgramOfThoughts", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Scientific Dspy.ProgramOfThoughts", 0}
        end
        
      7 ->
        # Multi-dimensional creative innovation with breakthrough thinking
        signature = Dspy.Signature.new("innovation_challenge -> creative_ideation, technological_feasibility, market_analysis, implementation_roadmap, risk_mitigation, breakthrough_potential, disruptive_elements, innovation_metrics")
        tot = Dspy.TreeOfThoughts.new(signature, num_thoughts: 7, max_depth: 4)
        
        try do
          result = Dspy.Module.forward(tot, %{innovation_challenge: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Creative Innovation Dspy.TreeOfThoughts", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Creative Innovation Dspy.TreeOfThoughts", 0}
        end
        
      8 ->
        # Enterprise-scale mass collaboration with specialized expertise
        agents = [
          %{role: "system_architect", signature: Dspy.Signature.new("complex_system_requirements -> system_architecture, scalability_design, integration_patterns, technology_stack")},
          %{role: "security_specialist", signature: Dspy.Signature.new("complex_system_requirements -> security_framework, threat_modeling, compliance_requirements, security_controls")},
          %{role: "performance_engineer", signature: Dspy.Signature.new("complex_system_requirements -> performance_optimization, load_balancing, caching_strategies, monitoring_systems")},
          %{role: "reliability_expert", signature: Dspy.Signature.new("complex_system_requirements -> reliability_engineering, disaster_recovery, fault_tolerance, SLA_design")},
          %{role: "ux_designer", signature: Dspy.Signature.new("complex_system_requirements -> user_experience_design, accessibility_features, usability_optimization, interface_patterns")},
          %{role: "data_scientist", signature: Dspy.Signature.new("complex_system_requirements -> data_architecture, analytics_framework, machine_learning_integration, data_governance")}
        ]
        mass_collab = Dspy.MassCollaboration.new(agents: agents, collaboration_rounds: 4)
        
        try do
          result = Dspy.Module.forward(mass_collab, %{complex_system_requirements: challenge.problem})
          execution_time = System.monotonic_time(:millisecond) - start_time
          {:ok, result, "Enterprise Dspy.MassCollaboration", execution_time}
        rescue
          e -> {:error, Exception.message(e), "Enterprise Dspy.MassCollaboration", 0}
        end
    end
  end
  
  defp display_result(result, challenge) do
    case result do
      {:ok, output, module_name, execution_time} ->
        IO.puts("✅ SUCCESS with #{module_name}")
        IO.puts("#{String.duplicate("-", 88)}")
        IO.puts("⚡ Execution Time: #{execution_time}ms | 🧠 Model: gpt-4.1-mini | 🎯 Level: #{challenge.level}")
        IO.puts("#{String.duplicate("-", 88)}")
        IO.puts("🎯 DETAILED SOLUTION:")
        
        # Enhanced display for complex outputs
        cond do
          is_map(output) ->
            # Handle the attrs map which contains the actual data
            attrs = Map.get(output, :attrs, output)
            
            # Sort keys to show most important fields first
            priority_keys = ["answer", "final_answer", "recommendation", "conclusion", 
                           "executive_summary", "ethical_recommendation", "creative_solution", "reasoning"]
            
            # Show priority fields first
            Enum.each(priority_keys, fn key ->
              atom_key = String.to_atom(key)
              if Map.has_key?(attrs, atom_key) do
                value = Map.get(attrs, atom_key)
                formatted_value = format_any_value(value)
                
                if formatted_value != "[]" and formatted_value != "" and formatted_value != "nil" do
                  IO.puts("🔸 #{String.upcase(key)}: #{formatted_value}")
                end
              end
            end)
            
            # Show other fields from attrs
            Enum.each(attrs, fn {key, value} ->
              unless String.to_atom(to_string(key)) in Enum.map(priority_keys, &String.to_atom/1) do
                formatted_value = format_any_value(value)
                
                if formatted_value != "[]" and formatted_value != "" and formatted_value != "nil" do
                  IO.puts("📋 #{String.capitalize(to_string(key))}: #{formatted_value}")
                end
              end
            end)
            
          is_binary(output) ->
            IO.puts("📝 #{format_output_value(output)}")
            
          true ->
            IO.puts("📊 #{inspect(output)}")
        end
        
        IO.puts("#{String.duplicate("-", 88)}")
        
      {:ok, output, module_name} ->
        # Handle legacy format without execution time
        display_result({:ok, output, module_name, 0}, challenge)
        
      {:error, error_msg, module_name, _execution_time} ->
        IO.puts("❌ FAILURE with #{module_name}")
        IO.puts("#{String.duplicate("-", 88)}")
        IO.puts("🚫 ERROR MESSAGE:")
        IO.puts("#{error_msg}")
        IO.puts("#{String.duplicate("-", 88)}")
        
      {:error, error_msg, module_name} ->
        # Handle legacy format without execution time
        display_result({:error, error_msg, module_name, 0}, challenge)
    end
  end
  
  defp format_any_value(value) do
    case value do
      binary when is_binary(binary) ->
        # Check if this binary is actually text by trying to convert it
        try do
          # Convert binary to charlist then to string to handle text data properly
          charlist = :binary.bin_to_list(binary)
          string_value = List.to_string(charlist)
          format_output_value(string_value)
        rescue
          _ -> 
            # If conversion fails, it's not text, so just format as normal binary
            format_output_value(binary)
        end
      list when is_list(list) ->
        # Handle charlists by converting to string
        try do
          formatted = List.to_string(list)
          format_output_value(formatted)
        rescue
          _ -> inspect(list)
        end
      nil ->
        "nil"
      other ->
        # For any other type, inspect it but handle long outputs
        inspected = inspect(other)
        if String.length(inspected) > 400 do
          "#{String.slice(inspected, 0, 400)}... [+#{String.length(inspected) - 400} more chars]"
        else
          inspected
        end
    end
  end

  defp format_output_value(value) when is_binary(value) do
    cleaned = String.trim(value)
    if String.length(cleaned) > 400 do
      "#{String.slice(cleaned, 0, 400)}... [+#{String.length(cleaned) - 400} more chars]"
    else
      cleaned
    end
  end
  
  defp format_output_value(value), do: inspect(value)

  defp display_challenge(challenge, metrics) do
    level_names = %{
      1 => "Enhanced Factual Reasoning",
      2 => "Advanced Chain of Thought", 
      3 => "Multi-Path Self-Consistency",
      4 => "Strategic Multi-Step Analysis",
      5 => "Advanced Ethical Reasoning",
      6 => "Scientific Computational Analysis", 
      7 => "Creative Innovation Synthesis",
      8 => "Enterprise Mass Collaboration"
    }
    
    level_descriptions = %{
      1 => "🔍 Deep analytical reasoning with confidence scoring",
      2 => "⛓️ Step-by-step verification with mathematical proofs",
      3 => "🔄 Multiple solution paths with cross-verification",
      4 => "📊 Complex strategic decomposition and planning",
      5 => "⚖️ Multi-stakeholder ethical framework analysis",
      6 => "🧪 Computational modeling with experimental design",
      7 => "💡 Multi-dimensional breakthrough innovation",
      8 => "🏢 Enterprise-scale collaborative expertise"
    }
    
    level_icons = %{
      1 => "🟢", 2 => "🟡", 3 => "🔵", 4 => "🟠",
      5 => "🔴", 6 => "⚫", 7 => "🌟", 8 => "🚀"
    }
    
    difficulty_scale = get_difficulty_scale(challenge.difficulty)
    cognitive_complexity = calculate_challenge_complexity(challenge.level, challenge.difficulty)
    
    IO.puts("#{String.duplicate("━", 100)}")
    IO.puts("#{level_icons[challenge.level]} ADVANCED COGNITIVE LEVEL #{challenge.level}: #{level_names[challenge.level]}")
    IO.puts("#{level_descriptions[challenge.level]}")
    IO.puts("━" |> String.duplicate(100))
    IO.puts("🎯 Challenge ##{metrics.total + 1} | 🔥 Difficulty: #{challenge.difficulty}/#{get_max_difficulty(metrics.total)} #{difficulty_scale}")
    IO.puts("🧠 Cognitive Complexity: #{cognitive_complexity} | 📊 Multiplier: #{Float.round(metrics.difficulty_multiplier, 3)}x")
    IO.puts("🎭 Model: gpt-4.1-mini | ⚡ Max Tokens: 4096 | 🌡️ Temperature: 0.7")
    IO.puts("━" |> String.duplicate(100))
    IO.puts("📋 SOPHISTICATED PROBLEM STATEMENT:")
    IO.puts("")
    IO.puts("#{format_problem_text(challenge.problem)}")
    IO.puts("")
    IO.puts("━" |> String.duplicate(100))
  end
  
  defp get_difficulty_scale(difficulty) do
    cond do
      difficulty < 25 -> "🟢 Accessible"
      difficulty < 50 -> "🟡 Moderate"
      difficulty < 100 -> "🟠 Challenging"
      difficulty < 200 -> "🔴 Advanced"
      difficulty < 500 -> "⚫ Expert"
      difficulty < 1000 -> "🌟 Master"
      true -> "🚀 Transcendent"
    end
  end
  
  defp calculate_challenge_complexity(level, difficulty) do
    base_complexity = level * 10
    difficulty_factor = difficulty / 10
    total_complexity = base_complexity + difficulty_factor
    
    cond do
      total_complexity < 30 -> "Light"
      total_complexity < 60 -> "Moderate" 
      total_complexity < 100 -> "High"
      total_complexity < 150 -> "Extreme"
      true -> "Transcendent"
    end
  end
  
  defp get_max_difficulty(total) do
    cond do
      total < 50 -> 100
      total < 200 -> 300
      total < 500 -> 800
      total < 1000 -> 2000
      true -> 5000
    end
  end
  
  defp format_problem_text(text) do
    # Add sophisticated formatting to problem text
    text
    |> String.split(". ")
    |> Enum.map(&String.trim/1)
    |> Enum.with_index()
    |> Enum.map(fn {sentence, idx} ->
      if idx == 0 do
        "🎲 #{sentence}."
      else
        "   #{sentence}."
      end
    end)
    |> Enum.join("\n")
  end

  defp update_metrics(metrics, level, result) do
    new_total = metrics.total + 1
    new_level_counts = Map.update!(metrics.level_counts, level, &(&1 + 1))
    new_difficulty = calculate_difficulty_multiplier(new_total)
    
    {new_successful, new_errors, new_level_successes} = 
      case result do
        {:ok, _, _, _} ->
          {metrics.successful + 1, metrics.errors, Map.update!(metrics.level_successes, level, &(&1 + 1))}
        {:ok, _, _} ->
          {metrics.successful + 1, metrics.errors, Map.update!(metrics.level_successes, level, &(&1 + 1))}
        {:error, _, _, _} ->
          {metrics.successful, metrics.errors + 1, metrics.level_successes}
        {:error, _, _} ->
          {metrics.successful, metrics.errors + 1, metrics.level_successes}
      end
    
    %{
      total: new_total,
      successful: new_successful,
      errors: new_errors,
      level_counts: new_level_counts,
      level_successes: new_level_successes,
      difficulty_multiplier: new_difficulty,
      start_time: metrics.start_time
    }
  end

  defp calculate_difficulty_multiplier(total) do
    base = 1.0
    
    # Exponential scaling with different phases
    cond do
      total < 50 ->
        # Initial linear growth for first 50 challenges
        base + (total * 0.01)
      total < 200 ->
        # Accelerated growth with logarithmic component
        base + 0.5 + (total * 0.008) + (:math.log(total) * 0.1)
      total < 500 ->
        # Advanced exponential scaling
        base + 2.0 + (:math.pow(total / 100, 1.2) * 0.5)
      total < 1000 ->
        # Expert level with controlled exponential growth
        base + 4.0 + (:math.log(total) * 0.3) + (:math.sin(total / 100) * 0.2)
      true ->
        # Master level with complex scaling function
        master_base = 8.0
        chaos_factor = :math.sin(total / 50) * 0.5
        exponential = :math.pow(total / 500, 0.8) * 0.3
        logarithmic = :math.log(total) * 0.2
        
        base + master_base + chaos_factor + exponential + logarithmic
    end
    |> min(20.0)  # Increased max difficulty for extreme challenges
  end

  defp display_progress(metrics) do
    elapsed = DateTime.diff(DateTime.utc_now(), metrics.start_time, :second)
    rate = if elapsed > 0, do: Float.round(metrics.total / elapsed, 2), else: 0.0
    success_rate = if metrics.total > 0, do: Float.round(metrics.successful / metrics.total * 100, 1), else: 0.0
    
    # Advanced performance metrics
    avg_time_per_challenge = if metrics.total > 0, do: elapsed / metrics.total, else: 0
    difficulty_phase = get_difficulty_phase(metrics.total)
    cognitive_load = calculate_cognitive_load(metrics)
    
    IO.puts("#{String.duplicate("━", 100)}")
    IO.puts("📊 ADVANCED PERFORMANCE ANALYTICS")
    IO.puts("#{String.duplicate("━", 100)}")
    IO.puts("🎯 Challenges: #{metrics.total} | ✅ Success: #{metrics.successful} | ❌ Failures: #{metrics.errors}")
    IO.puts("📈 Success Rate: #{success_rate}% | 🧠 Cognitive Load: #{cognitive_load}")
    IO.puts("⚡ Performance: #{rate} challenges/sec | ⏱️  Avg Time: #{Float.round(avg_time_per_challenge, 1)}s")
    IO.puts("🔥 Difficulty Phase: #{difficulty_phase} | 📊 Multiplier: #{Float.round(metrics.difficulty_multiplier, 3)}x")
    IO.puts("⏰ Runtime: #{format_duration(elapsed)} | 🎭 Model: gpt-4.1-mini")
    
    IO.puts("\n📈 COGNITIVE LEVEL PERFORMANCE MATRIX:")
    IO.puts("#{String.duplicate("─", 100)}")
    
    level_emojis = %{1 => "🟢", 2 => "🟡", 3 => "🔵", 4 => "🟠", 5 => "🔴", 6 => "⚫", 7 => "🌟", 8 => "🚀"}
    level_names = %{
      1 => "Enhanced Factual",
      2 => "Advanced CoT", 
      3 => "Multi-Path Verification",
      4 => "Strategic Analysis",
      5 => "Ethical Reasoning",
      6 => "Scientific Modeling", 
      7 => "Creative Innovation",
      8 => "Enterprise Collaboration"
    }
    
    Enum.each(1..8, fn level ->
      count = metrics.level_counts[level]
      successes = metrics.level_successes[level]
      percentage = if metrics.total > 0, do: Float.round(count / metrics.total * 100, 1), else: 0.0
      level_success_rate = if count > 0, do: Float.round(successes / count * 100, 1), else: 0.0
      
      progress_bar = create_progress_bar(level_success_rate, 20)
      
      IO.puts("#{level_emojis[level]} L#{level} #{level_names[level]}: #{count} attempts (#{percentage}%) | Success: #{level_success_rate}% #{progress_bar}")
    end)
    
    IO.puts("#{String.duplicate("─", 100)}")
    
    # Advanced predictions
    if metrics.total > 10 do
      next_milestone = get_next_milestone(metrics.total)
      projected_time = estimate_time_to_milestone(metrics, next_milestone)
      IO.puts("🔮 PREDICTIONS: Next milestone (#{next_milestone} challenges) in ~#{projected_time}")
    end
    
    IO.puts("\n⏳ Next advanced challenge loading in 3 seconds...\n")
  end
  
  defp get_difficulty_phase(total) do
    cond do
      total < 50 -> "🌱 Foundational"
      total < 200 -> "📚 Accelerated Learning"
      total < 500 -> "🎓 Advanced Mastery"
      total < 1000 -> "🧠 Expert Cognition"
      true -> "🚀 Transcendent Intelligence"
    end
  end
  
  defp calculate_cognitive_load(metrics) do
    base_load = metrics.difficulty_multiplier * 10
    complexity_factor = Enum.sum(for level <- 5..8, do: Map.get(metrics.level_counts, level, 0)) / max(metrics.total, 1)
    success_factor = if metrics.total > 0, do: metrics.successful / metrics.total, else: 1.0
    
    cognitive_load = (base_load + complexity_factor * 50) * (2 - success_factor)
    
    cond do
      cognitive_load < 20 -> "Light 🟢"
      cognitive_load < 50 -> "Moderate 🟡"
      cognitive_load < 100 -> "Heavy 🟠"
      cognitive_load < 200 -> "Intense 🔴"
      true -> "Extreme 🌋"
    end
  end
  
  defp create_progress_bar(percentage, width) do
    filled = round(percentage / 100 * width)
    empty = width - filled
    "[#{"█" |> String.duplicate(filled)}#{"░" |> String.duplicate(empty)}]"
  end
  
  defp format_duration(seconds) when seconds < 60, do: "#{seconds}s"
  defp format_duration(seconds) when seconds < 3600 do
    minutes = div(seconds, 60)
    secs = rem(seconds, 60)
    "#{minutes}m #{secs}s"
  end
  defp format_duration(seconds) do
    hours = div(seconds, 3600)
    minutes = div(rem(seconds, 3600), 60)
    secs = rem(seconds, 60)
    "#{hours}h #{minutes}m #{secs}s"
  end
  
  defp get_next_milestone(current) do
    milestones = [50, 100, 200, 500, 1000, 2000, 5000, 10000]
    Enum.find(milestones, fn m -> m > current end) || current + 5000
  end
  
  defp estimate_time_to_milestone(metrics, milestone) do
    elapsed = DateTime.diff(DateTime.utc_now(), metrics.start_time, :second)
    if metrics.total > 0 and elapsed > 0 do
      avg_time = elapsed / metrics.total
      remaining_challenges = milestone - metrics.total
      estimated_seconds = round(remaining_challenges * avg_time)
      format_duration(estimated_seconds)
    else
      "calculating..."
    end
  end
end

# Start the generator
UnlimitedSimpleChallenges.start()