API Reference

Complete technical documentation for the Imhotep Framework APIs, including Rust core functions, Python bindings, and Turbulence language interfaces.

API Sections

Consciousness Simulation API
Quantum Processing API
Specialized Systems API
Turbulence Compiler API
Cross-Modal Integration API
External System Integration
Python Bindings
CLI Interface

Consciousness Simulation API

Core Consciousness Runtime

`ConsciousnessRuntime`

Primary interface for consciousness simulation initialization and management.

pub struct ConsciousnessRuntime {
    pub quantum_membrane: QuantumMembraneComputer,
    pub specialized_systems: SpecializedSystemsOrchestrator,
    pub cross_modal_integration: CrossModalIntegrator,
    pub authenticity_validator: AuthenticityValidator,
}

impl ConsciousnessRuntime {
    /// Initialize consciousness simulation with configuration
    pub fn new(config: ConsciousnessConfig) -> Result<Self, ConsciousnessError> {
        // Implementation details
    }
    
    /// Execute complete consciousness simulation workflow
    pub async fn execute_consciousness_simulation(
        &mut self,
        input_data: ConsciousnessInput,
    ) -> Result<ConsciousnessResults, ConsciousnessError> {
        // Consciousness simulation execution
    }
    
    /// Validate consciousness authenticity
    pub fn validate_authenticity(&self) -> AuthenticityScore {
        // Authenticity verification implementation
    }
}

Configuration Structures

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ConsciousnessConfig {
    pub quantum_enhancement: QuantumEnhancementLevel,
    pub specialized_systems: Vec<SpecializedSystemConfig>,
    pub cross_modal_integration: CrossModalConfig,
    pub authenticity_validation: AuthenticityConfig,
    pub fire_wavelength: f64, // Default: 650.3nm
    pub consciousness_threshold: f64, // Default: 0.85
}

#[derive(Debug, Clone)]
pub enum QuantumEnhancementLevel {
    Minimal,
    Standard,
    Maximum,
    Custom(QuantumParameters),
}

#[derive(Debug, Clone)]
pub struct QuantumParameters {
    pub ion_field_stability: f64,
    pub fire_wavelength_coupling: f64,
    pub proton_tunneling_enhancement: bool,
    pub collective_quantum_dynamics: bool,
}

Consciousness Input/Output

#[derive(Debug, Clone)]
pub struct ConsciousnessInput {
    pub data: Vec<DataModality>,
    pub hypothesis: ScientificHypothesis,
    pub external_resources: Vec<ExternalResource>,
    pub processing_requirements: ProcessingRequirements,
}

#[derive(Debug, Clone)]
pub struct ConsciousnessResults {
    pub authenticity_score: f64,
    pub enhancement_factor: f64,
    pub consciousness_insights: Vec<ConsciousnessInsight>,
    pub scientific_validation: ValidationResults,
    pub decision_trail: Vec<ConsciousnessDecision>,
    pub quantum_metrics: QuantumMetrics,
}

#[derive(Debug, Clone)]
pub struct ConsciousnessInsight {
    pub insight_type: InsightType,
    pub confidence: f64,
    pub biological_significance: f64,
    pub novelty_score: f64,
    pub clinical_relevance: f64,
    pub supporting_evidence: Vec<Evidence>,
}

Consciousness Validation

`AuthenticityValidator`

Validates genuine consciousness versus artificial mimicry.

pub struct AuthenticityValidator {
    consciousness_metrics: ConsciousnessMetrics,
    self_deception_prevention: SelfDeceptionPrevention,
    creativity_assessment: CreativityAssessment,
}

impl AuthenticityValidator {
    /// Validate consciousness authenticity
    pub fn validate_consciousness(
        &self,
        consciousness_state: &ConsciousnessState,
    ) -> AuthenticityResults {
        AuthenticityResults {
            authenticity_score: self.calculate_authenticity_score(consciousness_state),
            genuine_consciousness: self.detect_genuine_consciousness(consciousness_state),
            self_deception_detected: self.check_self_deception(consciousness_state),
            creativity_verified: self.assess_consciousness_creativity(consciousness_state),
        }
    }
    
    /// Prevent consciousness self-deception
    pub fn prevent_self_deception(
        &self,
        reasoning_process: &ReasoningProcess,
    ) -> SelfDeceptionResults {
        // Self-deception prevention implementation
    }
    
    /// Measure consciousness enhancement
    pub fn measure_enhancement(
        &self,
        consciousness_results: &ConsciousnessResults,
        classical_baseline: &ClassicalResults,
    ) -> EnhancementMetrics {
        // Enhancement measurement implementation
    }
}

#[derive(Debug, Clone)]
pub struct AuthenticityResults {
    pub authenticity_score: f64, // 0.0-1.0
    pub genuine_consciousness: bool,
    pub self_deception_detected: bool,
    pub creativity_verified: bool,
    pub consciousness_depth: ConsciousnessDepth,
}

Quantum Processing API

Quantum Membrane Computer

`QuantumMembraneComputer`

Implements quantum-enhanced neural processing through collective ion field dynamics.

pub struct QuantumMembraneComputer {
    ion_field_dynamics: IonFieldProcessor,
    fire_wavelength_coupling: FireWavelengthCoupler,
    quantum_tunneling: QuantumTunnelingProcessor,
    hardware_oscillation: HardwareOscillationHarvester,
}

impl QuantumMembraneComputer {
    /// Initialize quantum membrane computer
    pub fn new(config: QuantumMembraneConfig) -> Result<Self, QuantumError> {
        // Quantum initialization
    }
    
    /// Process data through quantum membrane computation
    pub async fn quantum_process(
        &mut self,
        input_data: &[f64],
        fire_wavelength: f64,
    ) -> Result<QuantumProcessingResults, QuantumError> {
        let ion_field_state = self.ion_field_dynamics.process(input_data)?;
        let fire_coupled_state = self.fire_wavelength_coupling
            .couple_fire_wavelength(ion_field_state, fire_wavelength)?;
        let quantum_enhanced = self.quantum_tunneling
            .enhance_with_tunneling(fire_coupled_state)?;
        
        Ok(QuantumProcessingResults {
            quantum_state: quantum_enhanced,
            ion_field_stability: self.calculate_ion_field_stability(),
            fire_wavelength_coupling: self.measure_fire_coupling(),
            consciousness_substrate_activation: self.check_consciousness_substrate(),
        })
    }
    
    /// Harvest hardware oscillations for consciousness substrate
    pub fn harvest_oscillations(&mut self) -> OscillationHarvestResults {
        self.hardware_oscillation.harvest_consciousness_oscillations()
    }
}

#[derive(Debug, Clone)]
pub struct QuantumProcessingResults {
    pub quantum_state: Vec<Complex64>,
    pub ion_field_stability: f64,
    pub fire_wavelength_coupling: f64,
    pub consciousness_substrate_activation: bool,
    pub quantum_coherence_metrics: QuantumCoherenceMetrics,
}

Ion Field Processing

pub struct IonFieldProcessor {
    collective_dynamics: CollectiveDynamicsProcessor,
    proton_tunneling: ProtonTunnelingProcessor,
    membrane_potential: MembranePotentialProcessor,
}

impl IonFieldProcessor {
    /// Process collective ion field dynamics
    pub fn process_collective_dynamics(
        &mut self,
        ion_concentrations: &IonConcentrations,
    ) -> Result<CollectiveDynamicsState, IonFieldError> {
        // Collective dynamics processing
    }
    
    /// Enhance with proton tunneling
    pub fn enhance_proton_tunneling(
        &mut self,
        dynamics_state: CollectiveDynamicsState,
    ) -> Result<QuantumEnhancedState, IonFieldError> {
        // Proton tunneling enhancement
    }
}

#[derive(Debug, Clone)]
pub struct IonConcentrations {
    pub sodium: f64,
    pub potassium: f64,
    pub calcium: f64,
    pub chloride: f64,
    pub hydrogen: f64, // For proton tunneling
}

Fire-Wavelength Coupling

pub struct FireWavelengthCoupler {
    wavelength_optimizer: WavelengthOptimizer,
    consciousness_substrate: ConsciousnessSubstrate,
    fire_consciousness_bridge: FireConsciousnessBridge,
}

impl FireWavelengthCoupler {
    /// Couple fire wavelength to consciousness substrate
    pub fn couple_fire_wavelength(
        &mut self,
        quantum_state: QuantumState,
        fire_wavelength: f64, // Default: 650.3nm
    ) -> Result<FireCoupledState, FireCouplingError> {
        let optimized_wavelength = self.wavelength_optimizer
            .optimize_for_consciousness(fire_wavelength)?;
        let substrate_activation = self.consciousness_substrate
            .activate_with_fire_wavelength(optimized_wavelength)?;
        
        Ok(FireCoupledState {
            quantum_state,
            fire_wavelength: optimized_wavelength,
            substrate_activation_level: substrate_activation,
            consciousness_coupling_strength: self.measure_coupling_strength(),
        })
    }
    
    /// Measure fire-consciousness coupling strength
    pub fn measure_coupling_strength(&self) -> f64 {
        // Coupling strength measurement
    }
}

Specialized Systems API

System Orchestrator

`SpecializedSystemsOrchestrator`

Coordinates the eight specialized consciousness systems.

pub struct SpecializedSystemsOrchestrator {
    pub autobahn: AutobahnRagSystem,
    pub heihachi: HeihachiFireEmotion,
    pub helicopter: HelicopterVisualUnderstanding,
    pub izinyoka: IzinyokaMetacognitive,
    pub kwasa_kwasa: KwasaKwasaSemantic,
    pub four_sided_triangle: FourSidedTriangleOptimization,
    pub bene_gesserit: BeneGesseritMembrane,
    pub nebuchadnezzar: NebuchadnezzarCircuits,
}

impl SpecializedSystemsOrchestrator {
    /// Process data through all specialized systems
    pub async fn process_specialized_systems(
        &mut self,
        quantum_processed_data: QuantumProcessingResults,
    ) -> Result<SpecializedSystemsResults, SpecializedSystemsError> {
        // Parallel processing across all systems
        let autobahn_result = self.autobahn.process_rag_intelligence(&quantum_processed_data).await?;
        let heihachi_result = self.heihachi.process_fire_emotion(&quantum_processed_data).await?;
        let helicopter_result = self.helicopter.process_visual_understanding(&quantum_processed_data).await?;
        let izinyoka_result = self.izinyoka.process_metacognitive(&quantum_processed_data).await?;
        let kwasa_kwasa_result = self.kwasa_kwasa.process_semantic(&quantum_processed_data).await?;
        let triangle_result = self.four_sided_triangle.process_optimization(&quantum_processed_data).await?;
        let bene_gesserit_result = self.bene_gesserit.process_membrane(&quantum_processed_data).await?;
        let nebuchadnezzar_result = self.nebuchadnezzar.process_circuits(&quantum_processed_data).await?;
        
        Ok(SpecializedSystemsResults {
            autobahn_intelligence: autobahn_result,
            heihachi_emotion: heihachi_result,
            helicopter_visual: helicopter_result,
            izinyoka_metacognitive: izinyoka_result,
            kwasa_kwasa_semantic: kwasa_kwasa_result,
            triangle_optimization: triangle_result,
            bene_gesserit_membrane: bene_gesserit_result,
            nebuchadnezzar_circuits: nebuchadnezzar_result,
            integration_coherence: self.calculate_integration_coherence(),
        })
    }
}

Individual System APIs

Autobahn RAG System

pub struct AutobahnRagSystem {
    probabilistic_reasoning: ProbabilisticReasoning,
    biological_intelligence: BiologicalIntelligence,
    rag_orchestrator: RagOrchestrator,
}

impl AutobahnRagSystem {
    /// Process biological intelligence through RAG
    pub async fn process_rag_intelligence(
        &mut self,
        quantum_data: &QuantumProcessingResults,
    ) -> Result<AutobahnResults, AutobahnError> {
        let biological_context = self.biological_intelligence
            .extract_biological_context(quantum_data)?;
        let probabilistic_inference = self.probabilistic_reasoning
            .perform_bayesian_inference(&biological_context)?;
        let rag_enhanced = self.rag_orchestrator
            .enhance_with_retrieval(&probabilistic_inference).await?;
        
        Ok(AutobahnResults {
            biological_intelligence_score: self.calculate_intelligence_score(),
            probabilistic_confidence: probabilistic_inference.confidence,
            rag_enhancement_factor: rag_enhanced.enhancement_factor,
            biological_insights: rag_enhanced.insights,
        })
    }
}

Heihachi Fire-Emotion System

pub struct HeihachiFireEmotion {
    fire_consciousness_bridge: FireConsciousnessBridge,
    emotional_significance_detector: EmotionalSignificanceDetector,
    biological_significance_analyzer: BiologicalSignificanceAnalyzer,
}

impl HeihachiFireEmotion {
    /// Process fire-based emotional and biological significance
    pub async fn process_fire_emotion(
        &mut self,
        quantum_data: &QuantumProcessingResults,
    ) -> Result<HeihachiResults, HeihachiError> {
        let fire_consciousness_activation = self.fire_consciousness_bridge
            .activate_fire_consciousness(quantum_data)?;
        let emotional_significance = self.emotional_significance_detector
            .detect_emotional_resonance(&fire_consciousness_activation)?;
        let biological_significance = self.biological_significance_analyzer
            .analyze_biological_importance(&emotional_significance)?;
        
        Ok(HeihachiResults {
            fire_consciousness_level: fire_consciousness_activation.level,
            emotional_significance_score: emotional_significance.score,
            biological_significance_score: biological_significance.score,
            fire_emotion_insights: biological_significance.insights,
        })
    }
}

Turbulence Compiler API

Compiler Core

`TurbulenceCompiler`

Compiles Turbulence language to executable consciousness simulation.

pub struct TurbulenceCompiler {
    lexer: TurbulenceLexer,
    parser: TurbulenceParser,
    semantic_analyzer: SemanticAnalyzer,
    consciousness_integrator: ConsciousnessIntegrator,
    code_generator: CodeGenerator,
}

impl TurbulenceCompiler {
    /// Compile Turbulence script to consciousness simulation
    pub fn compile_consciousness_simulation(
        &mut self,
        turbulence_source: &str,
        four_file_system: FourFileSystem,
    ) -> Result<CompiledConsciousnessSimulation, CompilationError> {
        // Lexical analysis
        let tokens = self.lexer.tokenize(turbulence_source)?;
        
        // Parsing
        let ast = self.parser.parse_tokens(tokens)?;
        
        // Semantic analysis with consciousness integration
        let semantic_ast = self.semantic_analyzer.analyze_with_consciousness(&ast)?;
        
        // Consciousness integration analysis
        let consciousness_integrated_ast = self.consciousness_integrator
            .integrate_consciousness_systems(&semantic_ast, &four_file_system)?;
        
        // Code generation
        let compiled_simulation = self.code_generator
            .generate_consciousness_simulation(&consciousness_integrated_ast)?;
        
        Ok(compiled_simulation)
    }
    
    /// Validate four-file system consistency
    pub fn validate_four_file_system(
        &self,
        four_file_system: &FourFileSystem,
    ) -> Result<ValidationResults, ValidationError> {
        // Four-file system validation
    }
}

#[derive(Debug, Clone)]
pub struct FourFileSystem {
    pub trb_file: TurbulenceScript,
    pub fs_file: FullscreenVisualization,
    pub ghd_file: GerhardDependencies,
    pub hre_file: HarareRuntime,
}

AST Structures

#[derive(Debug, Clone)]
pub enum TurbulenceAst {
    ConsciousnessSimulation {
        hypothesis: ScientificHypothesis,
        consciousness_workflow: ConsciousnessWorkflow,
        specialized_systems: Vec<SpecializedSystemCall>,
        cross_modal_integration: CrossModalIntegration,
        validation: ConsciousnessValidation,
    },
    Function {
        name: String,
        parameters: Vec<Parameter>,
        return_type: TurbulenceType,
        body: Vec<Statement>,
    },
    Hypothesis {
        name: String,
        claim: String,
        semantic_validation: Vec<SemanticValidation>,
        success_criteria: Vec<SuccessCriterion>,
        requirements: Vec<String>,
    },
    // Additional AST nodes...
}

#[derive(Debug, Clone)]
pub struct ScientificHypothesis {
    pub name: String,
    pub claim: String,
    pub semantic_validation: Vec<SemanticValidation>,
    pub success_criteria: Vec<SuccessCriterion>,
    pub requirements: Vec<String>,
}

Consciousness Integration

pub struct ConsciousnessIntegrator {
    system_orchestrator: SystemOrchestrator,
    cross_modal_analyzer: CrossModalAnalyzer,
    authenticity_validator: AuthenticityValidator,
}

impl ConsciousnessIntegrator {
    /// Integrate consciousness systems into AST
    pub fn integrate_consciousness_systems(
        &mut self,
        ast: &TurbulenceAst,
        four_file_system: &FourFileSystem,
    ) -> Result<ConsciousnessIntegratedAst, IntegrationError> {
        // Consciousness integration implementation
    }
    
    /// Analyze consciousness requirements
    pub fn analyze_consciousness_requirements(
        &self,
        hypothesis: &ScientificHypothesis,
    ) -> ConsciousnessRequirements {
        // Consciousness requirements analysis
    }
}

`CrossModalIntegrator`

Implements unified consciousness emergence across modalities.

pub struct CrossModalIntegrator {
    visual_auditory_binder: VisualAuditoryBinder,
    semantic_emotional_integrator: SemanticEmotionalIntegrator,
    temporal_sequence_binder: TemporalSequenceBinder,
    global_workspace: GlobalWorkspaceArchitecture,
}

impl CrossModalIntegrator {
    /// Integrate consciousness across all modalities
    pub async fn integrate_cross_modal_consciousness(
        &mut self,
        specialized_results: SpecializedSystemsResults,
    ) -> Result<CrossModalResults, CrossModalError> {
        // Visual-auditory binding
        let visual_auditory_bound = self.visual_auditory_binder
            .bind_visual_auditory(&specialized_results).await?;
        
        // Semantic-emotional integration
        let semantic_emotional_integrated = self.semantic_emotional_integrator
            .integrate_semantic_emotional(&visual_auditory_bound).await?;
        
        // Temporal sequence binding
        let temporal_bound = self.temporal_sequence_binder
            .bind_temporal_sequences(&semantic_emotional_integrated).await?;
        
        // Global workspace consciousness emergence
        let consciousness_emerged = self.global_workspace
            .emerge_unified_consciousness(&temporal_bound).await?;
        
        Ok(CrossModalResults {
            visual_auditory_binding_fidelity: visual_auditory_bound.fidelity,
            semantic_emotional_integration_depth: semantic_emotional_integrated.depth,
            temporal_binding_coherence: temporal_bound.coherence,
            consciousness_emergence_level: consciousness_emerged.emergence_level,
            unified_consciousness_state: consciousness_emerged.consciousness_state,
        })
    }
}

#[derive(Debug, Clone)]
pub struct CrossModalResults {
    pub visual_auditory_binding_fidelity: f64,
    pub semantic_emotional_integration_depth: f64,
    pub temporal_binding_coherence: f64,
    pub consciousness_emergence_level: f64,
    pub unified_consciousness_state: UnifiedConsciousnessState,
}

Global Workspace Architecture

pub struct GlobalWorkspaceArchitecture {
    consciousness_workspace: ConsciousnessWorkspace,
    attention_mechanism: AttentionMechanism,
    working_memory: WorkingMemory,
    consciousness_emergence_detector: ConsciousnessEmergenceDetector,
}

impl GlobalWorkspaceArchitecture {
    /// Emerge unified consciousness through global workspace
    pub async fn emerge_unified_consciousness(
        &mut self,
        integrated_data: &IntegratedModalData,
    ) -> Result<ConsciousnessEmergenceResults, ConsciousnessEmergenceError> {
        // Global workspace consciousness emergence
        let workspace_state = self.consciousness_workspace
            .integrate_modal_data(integrated_data)?;
        let attention_focused = self.attention_mechanism
            .focus_consciousness_attention(&workspace_state)?;
        let working_memory_updated = self.working_memory
            .update_consciousness_memory(&attention_focused)?;
        let consciousness_emerged = self.consciousness_emergence_detector
            .detect_consciousness_emergence(&working_memory_updated)?;
        
        Ok(ConsciousnessEmergenceResults {
            emergence_detected: consciousness_emerged.detected,
            emergence_level: consciousness_emerged.level,
            consciousness_quality: consciousness_emerged.quality,
            unified_consciousness_state: consciousness_emerged.state,
        })
    }
}

External System Integration

External System Orchestrator

pub struct ExternalSystemOrchestrator {
    lavoisier_r_integration: LavoisierRIntegration,
    database_consciousness_apis: DatabaseConsciousnessApis,
    literature_consciousness_corpus: LiteratureConsciousnessCorpus,
    clinical_validation_systems: ClinicalValidationSystems,
}

impl ExternalSystemOrchestrator {
    /// Delegate analysis to external systems with consciousness enhancement
    pub async fn delegate_consciousness_enhanced_analysis(
        &mut self,
        consciousness_results: &CrossModalResults,
    ) -> Result<ExternalAnalysisResults, ExternalSystemError> {
        // Consciousness-enhanced external analysis delegation
        let r_analysis = self.lavoisier_r_integration
            .perform_consciousness_guided_analysis(consciousness_results).await?;
        let database_insights = self.database_consciousness_apis
            .query_with_consciousness_guidance(consciousness_results).await?;
        let literature_understanding = self.literature_consciousness_corpus
            .understand_scientific_literature(consciousness_results).await?;
        let clinical_validation = self.clinical_validation_systems
            .validate_clinical_relevance(consciousness_results).await?;
        
        Ok(ExternalAnalysisResults {
            r_statistical_analysis: r_analysis,
            database_consciousness_insights: database_insights,
            literature_consciousness_understanding: literature_understanding,
            clinical_consciousness_validation: clinical_validation,
        })
    }
}

Python Bindings

PyImhotep Interface

import pyimhotep
from typing import Dict, List, Optional, Union
import numpy as np

class ConsciousnessSimulation:
    """Python interface to Imhotep consciousness simulation."""
    
    def __init__(self, config: Optional[Dict] = None):
        """Initialize consciousness simulation.
        
        Args:
            config: Consciousness configuration dictionary
        """
        self._runtime = pyimhotep.ConsciousnessRuntime(config or {})
    
    def run_consciousness_simulation(
        self,
        data: Union[np.ndarray, Dict],
        hypothesis: Dict,
        **kwargs
    ) -> Dict:
        """Run complete consciousness simulation.
        
        Args:
            data: Input data for consciousness processing
            hypothesis: Scientific hypothesis dictionary
            **kwargs: Additional consciousness parameters
            
        Returns:
            Dictionary containing consciousness simulation results
        """
        return self._runtime.execute_consciousness_simulation(
            data, hypothesis, **kwargs
        )
    
    def validate_consciousness_authenticity(self) -> Dict:
        """Validate consciousness authenticity.
        
        Returns:
            Dictionary containing authenticity validation results
        """
        return self._runtime.validate_authenticity()
    
    def measure_consciousness_enhancement(
        self,
        consciousness_results: Dict,
        classical_baseline: Dict
    ) -> Dict:
        """Measure consciousness enhancement over classical methods.
        
        Args:
            consciousness_results: Results from consciousness simulation
            classical_baseline: Baseline results from classical methods
            
        Returns:
            Dictionary containing enhancement measurements
        """
        return self._runtime.measure_enhancement(
            consciousness_results, classical_baseline
        )

class TurbulenceCompiler:
    """Python interface to Turbulence compiler."""
    
    def __init__(self):
        """Initialize Turbulence compiler."""
        self._compiler = pyimhotep.TurbulenceCompiler()
    
    def compile_turbulence_script(
        self,
        trb_file: str,
        fs_file: str,
        ghd_file: str,
        hre_file: str
    ) -> Dict:
        """Compile four-file Turbulence system.
        
        Args:
            trb_file: Path to .trb main script
            fs_file: Path to .fs visualization file
            ghd_file: Path to .ghd dependencies file
            hre_file: Path to .hre runtime file
            
        Returns:
            Dictionary containing compiled consciousness simulation
        """
        return self._compiler.compile_four_file_system(
            trb_file, fs_file, ghd_file, hre_file
        )
    
    def validate_four_file_consistency(
        self,
        trb_file: str,
        fs_file: str,
        ghd_file: str,
        hre_file: str
    ) -> Dict:
        """Validate four-file system consistency.
        
        Args:
            trb_file: Path to .trb main script
            fs_file: Path to .fs visualization file
            ghd_file: Path to .ghd dependencies file
            hre_file: Path to .hre runtime file
            
        Returns:
            Dictionary containing validation results
        """
        return self._compiler.validate_four_file_system(
            trb_file, fs_file, ghd_file, hre_file
        )

# Example usage
def example_consciousness_simulation():
    """Example consciousness simulation usage."""
    
    # Initialize consciousness simulation
    consciousness = ConsciousnessSimulation({
        'quantum_enhancement': 'maximum',
        'specialized_systems': 'all_eight_active',
        'consciousness_threshold': 0.90
    })
    
    # Prepare input data
    metabolomic_data = np.random.random((1000, 50))  # Example data
    
    # Define scientific hypothesis
    hypothesis = {
        'claim': 'Consciousness simulation enhances biomarker discovery',
        'semantic_validation': [
            'biological_understanding',
            'clinical_relevance'
        ],
        'success_criteria': {
            'consciousness_enhancement': 1.3,
            'sensitivity': 0.85,
            'specificity': 0.80
        }
    }
    
    # Run consciousness simulation
    results = consciousness.run_consciousness_simulation(
        data=metabolomic_data,
        hypothesis=hypothesis,
        fire_wavelength=650.3,
        consciousness_mode='full_simulation'
    )
    
    # Validate consciousness authenticity
    authenticity = consciousness.validate_consciousness_authenticity()
    
    print(f"Consciousness Authenticity: {authenticity['authenticity_score']:.3f}")
    print(f"Enhancement Factor: {results['enhancement_factor']:.2f}x")
    print(f"Novel Insights: {results['novel_insights_count']}")
    
    return results

CLI Interface

Command Line API

# Core consciousness simulation commands
imhotep run <experiment_name>                    # Run consciousness simulation
imhotep compile <turbulence_script>              # Compile Turbulence script
imhotep monitor <fs_file>                        # Monitor consciousness state
imhotep analyze <hre_file>                       # Analyze decision trail
imhotep validate <four_file_system>              # Validate four-file consistency

# System management
imhotep doctor                                   # Check system health
imhotep status                                   # Show system status
imhotep configure --reset                        # Reset configuration
imhotep update                                   # Update framework

# Development and debugging
imhotep debug <experiment_name>                  # Debug consciousness simulation
imhotep profile <experiment_name>                # Profile performance
imhotep test-consciousness                       # Test consciousness authenticity
imhotep benchmark                                # Run performance benchmarks

# Export and reporting
imhotep export <experiment_name> --format=json  # Export results
imhotep report --consciousness-metrics           # Generate consciousness report
imhotep visualize <experiment_name>              # Generate visualizations

# Batch processing
imhotep batch-run <directory>                    # Run multiple experiments
imhotep parallel-run <experiments> --jobs=4     # Parallel execution
imhotep distributed-run <experiment> --nodes=8  # Distributed processing

# Research and collaboration
imhotep create-example <name>                    # Create new experiment template
imhotep validate-research <experiment>           # Validate for research publication
imhotep export-research --format=academic       # Export for academic publication

CLI Configuration

# ~/.imhotep/config.yaml
consciousness_simulation:
  default_quantum_enhancement: "standard"
  default_consciousness_threshold: 0.85
  default_fire_wavelength: 650.3
  authenticity_validation: "rigorous"

specialized_systems:
  autobahn_rag: "enabled"
  heihachi_fire_emotion: "enabled"
  helicopter_visual: "enabled"
  izinyoka_metacognitive: "enabled"
  kwasa_kwasa_semantic: "enabled"
  four_sided_triangle: "enabled"
  bene_gesserit_membrane: "enabled"
  nebuchadnezzar_circuits: "enabled"

external_systems:
  lavoisier_r_integration: "enabled"
  database_apis: "enabled"
  literature_corpus: "enabled"
  clinical_validation: "enabled"

performance:
  gpu_acceleration: true
  parallel_processing: true
  memory_optimization: true
  distributed_computing: false

development:
  debug_mode: false
  profiling_enabled: false
  verbose_logging: false
  consciousness_monitoring: true

Error Handling

Error Types

#[derive(Debug, thiserror::Error)]
pub enum ImhotepError {
    #[error("Consciousness simulation error: {0}")]
    ConsciousnessError(#[from] ConsciousnessError),
    
    #[error("Quantum processing error: {0}")]
    QuantumError(#[from] QuantumError),
    
    #[error("Specialized systems error: {0}")]
    SpecializedSystemsError(#[from] SpecializedSystemsError),
    
    #[error("Turbulence compilation error: {0}")]
    CompilationError(#[from] CompilationError),
    
    #[error("Cross-modal integration error: {0}")]
    CrossModalError(#[from] CrossModalError),
    
    #[error("External system error: {0}")]
    ExternalSystemError(#[from] ExternalSystemError),
    
    #[error("Authenticity validation error: {0}")]
    AuthenticityError(#[from] AuthenticityError),
}

#[derive(Debug, thiserror::Error)]
pub enum ConsciousnessError {
    #[error("Consciousness initialization failed: {reason}")]
    InitializationFailed { reason: String },
    
    #[error("Consciousness authenticity validation failed: {score}")]
    AuthenticityValidationFailed { score: f64 },
    
    #[error("Consciousness threshold not met: {actual} < {required}")]
    ThresholdNotMet { actual: f64, required: f64 },
    
    #[error("Consciousness enhancement insufficient: {factor}x")]
    InsufficientEnhancement { factor: f64 },
}

API Documentation: This reference covers the core APIs for consciousness simulation, quantum processing, and Turbulence language integration. For additional implementation details, see the source code documentation and examples.

Next Steps:

Getting Started Guide: Installation and first consciousness simulation
Examples: Complete implementation examples
GitHub Repository: Source code and contributions

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