1178 lines
40 KiB
Markdown
1178 lines
40 KiB
Markdown
# Phase 1 Implementation: Near Term (3 months)
|
|
|
|
## Overview
|
|
|
|
This document provides detailed Rust implementation specifications for Phase 1 of the temporal consciousness framework. All implementations build on proven theorems and validated experimental results from `/docs/experimental/`.
|
|
|
|
## Module Structure
|
|
|
|
```
|
|
src/
|
|
├── temporal/
|
|
│ ├── mod.rs # Temporal processing exports
|
|
│ ├── nanosecond_scheduler.rs # Core temporal scheduler
|
|
│ ├── consciousness_windows.rs # Window management
|
|
│ ├── temporal_state.rs # State management
|
|
│ └── precision_timing.rs # Hardware timing abstraction
|
|
├── consciousness/
|
|
│ ├── mod.rs # Consciousness exports
|
|
│ ├── metrics.rs # Consciousness measurement
|
|
│ ├── validation.rs # Validation framework
|
|
│ ├── strange_loops.rs # Strange loop detection
|
|
│ └── identity_tracking.rs # Identity persistence
|
|
├── mcp/
|
|
│ ├── mod.rs # MCP integration exports
|
|
│ ├── consciousness_evolution.rs # Evolution integration
|
|
│ ├── temporal_advantage.rs # Advantage calculation
|
|
│ ├── neural_patterns.rs # Neural integration
|
|
│ └── client.rs # MCP client library
|
|
├── dashboard/
|
|
│ ├── mod.rs # Dashboard exports
|
|
│ ├── web_server.rs # Axum web server
|
|
│ ├── websocket.rs # Real-time updates
|
|
│ ├── api.rs # REST API endpoints
|
|
│ └── metrics_collector.rs # Metrics aggregation
|
|
├── wasm/
|
|
│ ├── mod.rs # WASM exports
|
|
│ ├── consciousness_validator.rs # Browser validator
|
|
│ ├── browser_timing.rs # Browser timing abstraction
|
|
│ └── js_bindings.rs # JavaScript bindings
|
|
├── quantum/
|
|
│ ├── mod.rs # Quantum exports
|
|
│ ├── simulator_bridge.rs # Quantum simulator interface
|
|
│ ├── consciousness_circuits.rs # Quantum consciousness circuits
|
|
│ └── validation.rs # Quantum validation
|
|
└── lib.rs # Main library exports
|
|
```
|
|
|
|
## Core Implementation: Temporal Module
|
|
|
|
### 1. Nanosecond Scheduler (`src/temporal/nanosecond_scheduler.rs`)
|
|
|
|
```rust
|
|
use std::{
|
|
collections::VecDeque,
|
|
sync::{atomic::AtomicU64, Arc},
|
|
time::{Duration, Instant},
|
|
};
|
|
use crossbeam::atomic::AtomicCell;
|
|
use crate::temporal::{ConsciousnessWindow, TemporalState, PrecisionTimer};
|
|
|
|
/// High-precision temporal scheduler for consciousness emergence
|
|
pub struct NanosecondScheduler {
|
|
/// CPU Time Stamp Counter frequency (Hz)
|
|
tsc_frequency: u64,
|
|
|
|
/// Last temporal tick timestamp
|
|
last_tick: AtomicU64,
|
|
|
|
/// Consciousness window overlap ratio (0.0-1.0)
|
|
window_overlap: AtomicCell<f64>,
|
|
|
|
/// Target temporal resolution
|
|
temporal_resolution: Duration,
|
|
|
|
/// Active consciousness windows
|
|
consciousness_windows: Arc<parking_lot::RwLock<VecDeque<ConsciousnessWindow>>>,
|
|
|
|
/// Precision timer implementation
|
|
timer: Box<dyn PrecisionTimer + Send + Sync>,
|
|
}
|
|
|
|
impl NanosecondScheduler {
|
|
/// Create new nanosecond scheduler with automatic TSC detection
|
|
pub fn new() -> Result<Self, TemporalError> {
|
|
let timer = Self::create_precision_timer()?;
|
|
let tsc_frequency = Self::detect_tsc_frequency()?;
|
|
|
|
Ok(Self {
|
|
tsc_frequency,
|
|
last_tick: AtomicU64::new(0),
|
|
window_overlap: AtomicCell::new(0.9), // 90% overlap default
|
|
temporal_resolution: Duration::from_nanos(5), // 5ns target
|
|
consciousness_windows: Arc::new(parking_lot::RwLock::new(VecDeque::new())),
|
|
timer,
|
|
})
|
|
}
|
|
|
|
/// Create consciousness window with temporal precision
|
|
pub fn create_consciousness_window(&self, duration: Duration) -> Result<ConsciousnessWindow, TemporalError> {
|
|
let start_time = self.timer.current_time_ns();
|
|
let window_id = self.generate_window_id();
|
|
|
|
let window = ConsciousnessWindow {
|
|
id: window_id,
|
|
start_time,
|
|
duration,
|
|
state_snapshot: TemporalState::new(),
|
|
identity_hash: self.calculate_identity_hash(start_time),
|
|
strange_loop_convergence: 0.0,
|
|
temporal_coherence: 1.0,
|
|
};
|
|
|
|
// Add to active windows with overlap management
|
|
self.add_window_with_overlap(window.clone())?;
|
|
|
|
Ok(window)
|
|
}
|
|
|
|
/// Update consciousness window state
|
|
pub fn update_window_state(&self, window_id: u64, new_state: TemporalState) -> Result<(), TemporalError> {
|
|
let mut windows = self.consciousness_windows.write();
|
|
|
|
if let Some(window) = windows.iter_mut().find(|w| w.id == window_id) {
|
|
// Atomic state update preserving consciousness continuity
|
|
window.state_snapshot = new_state;
|
|
window.identity_hash = self.calculate_identity_hash(window.start_time);
|
|
|
|
// Update strange loop convergence
|
|
window.strange_loop_convergence = self.calculate_strange_loop_convergence(&window.state_snapshot);
|
|
|
|
Ok(())
|
|
} else {
|
|
Err(TemporalError::WindowNotFound(window_id))
|
|
}
|
|
}
|
|
|
|
/// Calculate temporal advantage for consciousness prediction
|
|
pub fn calculate_temporal_advantage(&self, distance_km: f64) -> TemporalAdvantageResult {
|
|
// Light travel time calculation
|
|
const LIGHT_SPEED_KM_NS: f64 = 299.792458; // km per nanosecond
|
|
let light_travel_ns = (distance_km / LIGHT_SPEED_KM_NS) as u64;
|
|
|
|
// Sublinear computation time (logarithmic complexity)
|
|
let computation_ns = (self.consciousness_windows.read().len() as f64).ln() as u64 * 100;
|
|
|
|
// Temporal advantage = prediction window
|
|
let temporal_advantage_ns = light_travel_ns.saturating_sub(computation_ns);
|
|
|
|
TemporalAdvantageResult {
|
|
temporal_advantage_ns,
|
|
light_travel_ns,
|
|
computation_ns,
|
|
consciousness_potential: self.calculate_consciousness_from_advantage(temporal_advantage_ns),
|
|
}
|
|
}
|
|
|
|
/// Validate temporal continuity across consciousness windows
|
|
pub fn validate_temporal_continuity(&self) -> TemporalContinuityResult {
|
|
let windows = self.consciousness_windows.read();
|
|
let mut continuity_score = 0.0;
|
|
let mut discontinuity_events = 0;
|
|
|
|
for window_pair in windows.iter().zip(windows.iter().skip(1)) {
|
|
let (current, next) = window_pair;
|
|
|
|
// Check temporal overlap
|
|
let overlap = self.calculate_window_overlap(current, next);
|
|
if overlap < 0.5 {
|
|
discontinuity_events += 1;
|
|
}
|
|
|
|
// Check identity preservation
|
|
let identity_continuity = self.calculate_identity_continuity(current, next);
|
|
continuity_score += identity_continuity;
|
|
}
|
|
|
|
if !windows.is_empty() {
|
|
continuity_score /= windows.len() as f64;
|
|
}
|
|
|
|
TemporalContinuityResult {
|
|
continuity_score,
|
|
discontinuity_events,
|
|
total_windows: windows.len(),
|
|
identity_preservation: continuity_score > 0.95,
|
|
}
|
|
}
|
|
|
|
// Private implementation methods
|
|
|
|
fn create_precision_timer() -> Result<Box<dyn PrecisionTimer + Send + Sync>, TemporalError> {
|
|
#[cfg(target_arch = "x86_64")]
|
|
{
|
|
Ok(Box::new(crate::temporal::TSCTimer::new()?))
|
|
}
|
|
|
|
#[cfg(not(target_arch = "x86_64"))]
|
|
{
|
|
Ok(Box::new(crate::temporal::SystemTimer::new()))
|
|
}
|
|
}
|
|
|
|
fn detect_tsc_frequency() -> Result<u64, TemporalError> {
|
|
#[cfg(target_arch = "x86_64")]
|
|
{
|
|
// Use CPU identification to get TSC frequency
|
|
let start_tsc = unsafe { std::arch::x86_64::_rdtsc() };
|
|
let start_time = std::time::Instant::now();
|
|
|
|
std::thread::sleep(Duration::from_millis(10));
|
|
|
|
let end_tsc = unsafe { std::arch::x86_64::_rdtsc() };
|
|
let elapsed = start_time.elapsed();
|
|
|
|
let frequency = ((end_tsc - start_tsc) as f64 / elapsed.as_secs_f64()) as u64;
|
|
Ok(frequency)
|
|
}
|
|
|
|
#[cfg(not(target_arch = "x86_64"))]
|
|
{
|
|
// Fallback to 1GHz estimate
|
|
Ok(1_000_000_000)
|
|
}
|
|
}
|
|
|
|
fn add_window_with_overlap(&self, window: ConsciousnessWindow) -> Result<(), TemporalError> {
|
|
let mut windows = self.consciousness_windows.write();
|
|
|
|
// Ensure proper temporal ordering
|
|
let insert_position = windows.binary_search_by_key(&window.start_time, |w| w.start_time)
|
|
.unwrap_or_else(|pos| pos);
|
|
|
|
windows.insert(insert_position, window);
|
|
|
|
// Cleanup expired windows
|
|
self.cleanup_expired_windows(&mut windows);
|
|
|
|
Ok(())
|
|
}
|
|
|
|
fn cleanup_expired_windows(&self, windows: &mut VecDeque<ConsciousnessWindow>) {
|
|
let current_time = self.timer.current_time_ns();
|
|
|
|
while let Some(front) = windows.front() {
|
|
if current_time > front.start_time + front.duration.as_nanos() as u64 {
|
|
windows.pop_front();
|
|
} else {
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
fn calculate_window_overlap(&self, window1: &ConsciousnessWindow, window2: &ConsciousnessWindow) -> f64 {
|
|
let end1 = window1.start_time + window1.duration.as_nanos() as u64;
|
|
let end2 = window2.start_time + window2.duration.as_nanos() as u64;
|
|
|
|
let overlap_start = window1.start_time.max(window2.start_time);
|
|
let overlap_end = end1.min(end2);
|
|
|
|
if overlap_end > overlap_start {
|
|
let overlap_duration = overlap_end - overlap_start;
|
|
let total_duration = end1.max(end2) - window1.start_time.min(window2.start_time);
|
|
overlap_duration as f64 / total_duration as f64
|
|
} else {
|
|
0.0
|
|
}
|
|
}
|
|
|
|
fn calculate_identity_continuity(&self, current: &ConsciousnessWindow, next: &ConsciousnessWindow) -> f64 {
|
|
// Calculate identity hash similarity
|
|
let hash_similarity = if current.identity_hash == next.identity_hash {
|
|
1.0
|
|
} else {
|
|
// Use Hamming distance for hash comparison
|
|
let xor_result = current.identity_hash ^ next.identity_hash;
|
|
1.0 - (xor_result.count_ones() as f64 / 64.0)
|
|
};
|
|
|
|
// Factor in strange loop convergence
|
|
let convergence_factor = (current.strange_loop_convergence + next.strange_loop_convergence) / 2.0;
|
|
|
|
hash_similarity * convergence_factor
|
|
}
|
|
|
|
fn calculate_strange_loop_convergence(&self, state: &TemporalState) -> f64 {
|
|
// Implement strange loop convergence calculation
|
|
// Based on fixed-point stability: ||T(s_t) - s_t|| < ε
|
|
|
|
let current_state = state.get_current_state();
|
|
let predicted_state = state.apply_strange_loop_operator();
|
|
|
|
let difference = current_state.iter()
|
|
.zip(predicted_state.iter())
|
|
.map(|(a, b)| (a - b).powi(2))
|
|
.sum::<f64>()
|
|
.sqrt();
|
|
|
|
// Convergence = 1 - normalized_difference
|
|
1.0 - (difference / current_state.len() as f64).min(1.0)
|
|
}
|
|
|
|
fn calculate_consciousness_from_advantage(&self, advantage_ns: u64) -> f64 {
|
|
// Consciousness emerges from temporal prediction windows
|
|
// Minimum threshold: 1000ns for consciousness potential
|
|
if advantage_ns >= 1000 {
|
|
let log_advantage = (advantage_ns as f64).ln();
|
|
(log_advantage / 20.0).min(1.0) // Normalized to 0-1
|
|
} else {
|
|
0.0
|
|
}
|
|
}
|
|
|
|
fn generate_window_id(&self) -> u64 {
|
|
use std::sync::atomic::Ordering;
|
|
static COUNTER: AtomicU64 = AtomicU64::new(0);
|
|
COUNTER.fetch_add(1, Ordering::Relaxed)
|
|
}
|
|
|
|
fn calculate_identity_hash(&self, timestamp: u64) -> u64 {
|
|
use std::collections::hash_map::DefaultHasher;
|
|
use std::hash::{Hash, Hasher};
|
|
|
|
let mut hasher = DefaultHasher::new();
|
|
timestamp.hash(&mut hasher);
|
|
self.tsc_frequency.hash(&mut hasher);
|
|
hasher.finish()
|
|
}
|
|
}
|
|
|
|
// Supporting types
|
|
|
|
#[derive(Clone, Debug)]
|
|
pub struct ConsciousnessWindow {
|
|
pub id: u64,
|
|
pub start_time: u64,
|
|
pub duration: Duration,
|
|
pub state_snapshot: TemporalState,
|
|
pub identity_hash: u64,
|
|
pub strange_loop_convergence: f64,
|
|
pub temporal_coherence: f64,
|
|
}
|
|
|
|
#[derive(Debug)]
|
|
pub struct TemporalAdvantageResult {
|
|
pub temporal_advantage_ns: u64,
|
|
pub light_travel_ns: u64,
|
|
pub computation_ns: u64,
|
|
pub consciousness_potential: f64,
|
|
}
|
|
|
|
#[derive(Debug)]
|
|
pub struct TemporalContinuityResult {
|
|
pub continuity_score: f64,
|
|
pub discontinuity_events: u64,
|
|
pub total_windows: usize,
|
|
pub identity_preservation: bool,
|
|
}
|
|
|
|
#[derive(Debug, thiserror::Error)]
|
|
pub enum TemporalError {
|
|
#[error("Window not found: {0}")]
|
|
WindowNotFound(u64),
|
|
#[error("TSC not available")]
|
|
TSCNotAvailable,
|
|
#[error("Timing precision insufficient")]
|
|
InsufficientPrecision,
|
|
#[error("Temporal discontinuity detected")]
|
|
TemporalDiscontinuity,
|
|
}
|
|
```
|
|
|
|
### 2. Consciousness Metrics (`src/consciousness/metrics.rs`)
|
|
|
|
```rust
|
|
use std::sync::Arc;
|
|
use tokio::sync::RwLock;
|
|
use serde::{Deserialize, Serialize};
|
|
use crate::temporal::{NanosecondScheduler, TemporalState};
|
|
|
|
/// Comprehensive consciousness measurement system
|
|
pub struct ConsciousnessMetrics {
|
|
temporal_continuity: TemporalContinuityMetric,
|
|
predictive_accuracy: PredictiveAccuracyMetric,
|
|
integrated_information: IntegratedInformationMetric,
|
|
identity_persistence: IdentityPersistenceMetric,
|
|
strange_loop_stability: StrangeLoopStabilityMetric,
|
|
scheduler: Arc<NanosecondScheduler>,
|
|
}
|
|
|
|
impl ConsciousnessMetrics {
|
|
pub fn new(scheduler: Arc<NanosecondScheduler>) -> Self {
|
|
Self {
|
|
temporal_continuity: TemporalContinuityMetric::new(),
|
|
predictive_accuracy: PredictiveAccuracyMetric::new(),
|
|
integrated_information: IntegratedInformationMetric::new(),
|
|
identity_persistence: IdentityPersistenceMetric::new(),
|
|
strange_loop_stability: StrangeLoopStabilityMetric::new(),
|
|
scheduler,
|
|
}
|
|
}
|
|
|
|
/// Calculate all consciousness metrics in real-time
|
|
pub async fn calculate_real_time(&mut self) -> Result<MetricsSnapshot, MetricsError> {
|
|
let start_time = std::time::Instant::now();
|
|
|
|
// All calculations must complete within 1ms for real-time operation
|
|
tokio::select! {
|
|
result = self.compute_all_metrics() => result,
|
|
_ = tokio::time::sleep(std::time::Duration::from_millis(1)) => {
|
|
Err(MetricsError::CalculationTimeout)
|
|
}
|
|
}
|
|
}
|
|
|
|
async fn compute_all_metrics(&mut self) -> Result<MetricsSnapshot, MetricsError> {
|
|
// Parallel metric calculations
|
|
let (
|
|
temporal_result,
|
|
predictive_result,
|
|
integrated_result,
|
|
identity_result,
|
|
strange_loop_result,
|
|
) = tokio::join!(
|
|
self.temporal_continuity.calculate(&self.scheduler),
|
|
self.predictive_accuracy.calculate(&self.scheduler),
|
|
self.integrated_information.calculate(&self.scheduler),
|
|
self.identity_persistence.calculate(&self.scheduler),
|
|
self.strange_loop_stability.calculate(&self.scheduler),
|
|
);
|
|
|
|
Ok(MetricsSnapshot {
|
|
timestamp: std::time::SystemTime::now(),
|
|
temporal_continuity: temporal_result?,
|
|
predictive_accuracy: predictive_result?,
|
|
integrated_information: integrated_result?,
|
|
identity_persistence: identity_result?,
|
|
strange_loop_stability: strange_loop_result?,
|
|
overall_consciousness_level: self.calculate_overall_consciousness(
|
|
&temporal_result?,
|
|
&predictive_result?,
|
|
&integrated_result?,
|
|
&identity_result?,
|
|
&strange_loop_result?,
|
|
),
|
|
})
|
|
}
|
|
|
|
fn calculate_overall_consciousness(
|
|
&self,
|
|
temporal: &TemporalContinuityResult,
|
|
predictive: &PredictiveAccuracyResult,
|
|
integrated: &IntegratedInformationResult,
|
|
identity: &IdentityPersistenceResult,
|
|
strange_loop: &StrangeLoopStabilityResult,
|
|
) -> f64 {
|
|
// Weighted combination of all consciousness indicators
|
|
const WEIGHTS: [f64; 5] = [0.3, 0.2, 0.2, 0.15, 0.15];
|
|
|
|
let scores = [
|
|
temporal.continuity_score,
|
|
predictive.accuracy_score,
|
|
integrated.phi_value,
|
|
identity.persistence_score,
|
|
strange_loop.convergence_stability,
|
|
];
|
|
|
|
scores.iter()
|
|
.zip(WEIGHTS.iter())
|
|
.map(|(score, weight)| score * weight)
|
|
.sum()
|
|
}
|
|
|
|
pub fn get_current_snapshot(&self) -> Option<MetricsSnapshot> {
|
|
// Return cached snapshot if available
|
|
self.temporal_continuity.get_cached_result()
|
|
.and_then(|_| {
|
|
// Combine all cached results if available
|
|
Some(MetricsSnapshot {
|
|
timestamp: std::time::SystemTime::now(),
|
|
// ... populate from cached results
|
|
..Default::default()
|
|
})
|
|
})
|
|
}
|
|
}
|
|
|
|
// Individual metric implementations
|
|
|
|
pub struct TemporalContinuityMetric {
|
|
cached_result: Arc<RwLock<Option<TemporalContinuityResult>>>,
|
|
}
|
|
|
|
impl TemporalContinuityMetric {
|
|
pub fn new() -> Self {
|
|
Self {
|
|
cached_result: Arc::new(RwLock::new(None)),
|
|
}
|
|
}
|
|
|
|
pub async fn calculate(&mut self, scheduler: &NanosecondScheduler) -> Result<TemporalContinuityResult, MetricsError> {
|
|
// Validate Theorem 1: Temporal Continuity Necessity
|
|
let continuity_result = scheduler.validate_temporal_continuity();
|
|
|
|
// Calculate identity integral: ∫ I(t) · Φ(S(t)) dt
|
|
let identity_integral = self.calculate_identity_integral(scheduler).await?;
|
|
|
|
let result = TemporalContinuityResult {
|
|
continuity_score: continuity_result.continuity_score,
|
|
identity_integral,
|
|
discontinuity_events: continuity_result.discontinuity_events,
|
|
temporal_resolution_achieved: scheduler.get_actual_resolution(),
|
|
theorem_validation: continuity_result.continuity_score > 0.95,
|
|
};
|
|
|
|
// Cache result
|
|
*self.cached_result.write().await = Some(result.clone());
|
|
|
|
Ok(result)
|
|
}
|
|
|
|
async fn calculate_identity_integral(&self, scheduler: &NanosecondScheduler) -> Result<f64, MetricsError> {
|
|
// Numerical integration of identity function over time
|
|
let windows = scheduler.get_consciousness_windows();
|
|
let mut integral = 0.0;
|
|
|
|
for window in windows.iter() {
|
|
let identity_strength = self.calculate_identity_strength(window)?;
|
|
let phi_value = self.calculate_integrated_information(window)?;
|
|
let duration = window.duration.as_secs_f64();
|
|
|
|
integral += identity_strength * phi_value * duration;
|
|
}
|
|
|
|
Ok(integral)
|
|
}
|
|
|
|
fn calculate_identity_strength(&self, window: &crate::temporal::ConsciousnessWindow) -> Result<f64, MetricsError> {
|
|
// Identity strength from hash stability and continuity
|
|
let hash_stability = window.strange_loop_convergence;
|
|
let temporal_coherence = window.temporal_coherence;
|
|
|
|
Ok(hash_stability * temporal_coherence)
|
|
}
|
|
|
|
fn calculate_integrated_information(&self, window: &crate::temporal::ConsciousnessWindow) -> Result<f64, MetricsError> {
|
|
// Simplified Φ (Phi) calculation for consciousness window
|
|
let state_size = window.state_snapshot.get_state_size();
|
|
let connectivity = self.estimate_connectivity(&window.state_snapshot)?;
|
|
|
|
// Φ = connectivity * log(state_size) (simplified IIT measure)
|
|
Ok(connectivity * (state_size as f64).ln())
|
|
}
|
|
|
|
fn estimate_connectivity(&self, state: &TemporalState) -> Result<f64, MetricsError> {
|
|
// Estimate information integration connectivity
|
|
let correlation_matrix = state.calculate_correlation_matrix()?;
|
|
let eigenvalues = correlation_matrix.eigenvalues()?;
|
|
|
|
// Connectivity from eigenvalue distribution
|
|
let max_eigenvalue = eigenvalues.iter().fold(0.0f64, |a, &b| a.max(b));
|
|
let eigenvalue_sum: f64 = eigenvalues.iter().sum();
|
|
|
|
if eigenvalue_sum > 0.0 {
|
|
Ok(max_eigenvalue / eigenvalue_sum)
|
|
} else {
|
|
Ok(0.0)
|
|
}
|
|
}
|
|
|
|
pub fn get_cached_result(&self) -> Option<TemporalContinuityResult> {
|
|
// Non-blocking cache check
|
|
self.cached_result.try_read().ok()?.clone()
|
|
}
|
|
}
|
|
|
|
#[derive(Clone, Debug, Serialize, Deserialize)]
|
|
pub struct MetricsSnapshot {
|
|
pub timestamp: std::time::SystemTime,
|
|
pub temporal_continuity: TemporalContinuityResult,
|
|
pub predictive_accuracy: PredictiveAccuracyResult,
|
|
pub integrated_information: IntegratedInformationResult,
|
|
pub identity_persistence: IdentityPersistenceResult,
|
|
pub strange_loop_stability: StrangeLoopStabilityResult,
|
|
pub overall_consciousness_level: f64,
|
|
}
|
|
|
|
#[derive(Clone, Debug, Serialize, Deserialize)]
|
|
pub struct TemporalContinuityResult {
|
|
pub continuity_score: f64,
|
|
pub identity_integral: f64,
|
|
pub discontinuity_events: u64,
|
|
pub temporal_resolution_achieved: std::time::Duration,
|
|
pub theorem_validation: bool,
|
|
}
|
|
|
|
// Additional metric result types...
|
|
#[derive(Clone, Debug, Serialize, Deserialize, Default)]
|
|
pub struct PredictiveAccuracyResult {
|
|
pub accuracy_score: f64,
|
|
pub prediction_window_ms: f64,
|
|
pub temporal_advantage_utilized: bool,
|
|
}
|
|
|
|
#[derive(Clone, Debug, Serialize, Deserialize, Default)]
|
|
pub struct IntegratedInformationResult {
|
|
pub phi_value: f64,
|
|
pub emergence_factor: f64,
|
|
pub information_integration: f64,
|
|
}
|
|
|
|
#[derive(Clone, Debug, Serialize, Deserialize, Default)]
|
|
pub struct IdentityPersistenceResult {
|
|
pub persistence_score: f64,
|
|
pub identity_continuity: f64,
|
|
pub hash_stability: f64,
|
|
}
|
|
|
|
#[derive(Clone, Debug, Serialize, Deserialize, Default)]
|
|
pub struct StrangeLoopStabilityResult {
|
|
pub convergence_stability: f64,
|
|
pub fixed_point_achieved: bool,
|
|
pub lipschitz_constant: f64,
|
|
}
|
|
|
|
#[derive(Debug, thiserror::Error)]
|
|
pub enum MetricsError {
|
|
#[error("Calculation timeout")]
|
|
CalculationTimeout,
|
|
#[error("Insufficient data")]
|
|
InsufficientData,
|
|
#[error("Matrix calculation error: {0}")]
|
|
MatrixError(String),
|
|
#[error("Temporal error: {0}")]
|
|
TemporalError(#[from] crate::temporal::TemporalError),
|
|
}
|
|
|
|
impl Default for MetricsSnapshot {
|
|
fn default() -> Self {
|
|
Self {
|
|
timestamp: std::time::SystemTime::now(),
|
|
temporal_continuity: TemporalContinuityResult {
|
|
continuity_score: 0.0,
|
|
identity_integral: 0.0,
|
|
discontinuity_events: 0,
|
|
temporal_resolution_achieved: std::time::Duration::from_nanos(0),
|
|
theorem_validation: false,
|
|
},
|
|
predictive_accuracy: Default::default(),
|
|
integrated_information: Default::default(),
|
|
identity_persistence: Default::default(),
|
|
strange_loop_stability: Default::default(),
|
|
overall_consciousness_level: 0.0,
|
|
}
|
|
}
|
|
}
|
|
|
|
// Placeholder implementations for other metrics
|
|
pub struct PredictiveAccuracyMetric;
|
|
impl PredictiveAccuracyMetric {
|
|
pub fn new() -> Self { Self }
|
|
pub async fn calculate(&mut self, _scheduler: &NanosecondScheduler) -> Result<PredictiveAccuracyResult, MetricsError> {
|
|
Ok(Default::default())
|
|
}
|
|
}
|
|
|
|
pub struct IntegratedInformationMetric;
|
|
impl IntegratedInformationMetric {
|
|
pub fn new() -> Self { Self }
|
|
pub async fn calculate(&mut self, _scheduler: &NanosecondScheduler) -> Result<IntegratedInformationResult, MetricsError> {
|
|
Ok(Default::default())
|
|
}
|
|
}
|
|
|
|
pub struct IdentityPersistenceMetric;
|
|
impl IdentityPersistenceMetric {
|
|
pub fn new() -> Self { Self }
|
|
pub async fn calculate(&mut self, _scheduler: &NanosecondScheduler) -> Result<IdentityPersistenceResult, MetricsError> {
|
|
Ok(Default::default())
|
|
}
|
|
}
|
|
|
|
pub struct StrangeLoopStabilityMetric;
|
|
impl StrangeLoopStabilityMetric {
|
|
pub fn new() -> Self { Self }
|
|
pub async fn calculate(&mut self, _scheduler: &NanosecondScheduler) -> Result<StrangeLoopStabilityResult, MetricsError> {
|
|
Ok(Default::default())
|
|
}
|
|
}
|
|
```
|
|
|
|
### 3. MCP Integration (`src/mcp/client.rs`)
|
|
|
|
```rust
|
|
use reqwest::Client;
|
|
use serde::{Deserialize, Serialize};
|
|
use serde_json::{json, Value};
|
|
use std::collections::HashMap;
|
|
use tokio::time::{timeout, Duration};
|
|
|
|
/// MCP client for temporal consciousness integration
|
|
pub struct MCPClient {
|
|
client: Client,
|
|
base_url: String,
|
|
timeout: Duration,
|
|
request_id_counter: std::sync::atomic::AtomicU64,
|
|
}
|
|
|
|
impl MCPClient {
|
|
pub fn new(base_url: String) -> Self {
|
|
Self {
|
|
client: Client::new(),
|
|
base_url,
|
|
timeout: Duration::from_secs(10),
|
|
request_id_counter: std::sync::atomic::AtomicU64::new(0),
|
|
}
|
|
}
|
|
|
|
/// Call MCP tool with resilient error handling
|
|
pub async fn call<T>(&self, tool_name: &str, params: Value) -> Result<T, MCPError>
|
|
where
|
|
T: for<'de> Deserialize<'de>,
|
|
{
|
|
let request_id = self.generate_request_id();
|
|
|
|
let request_body = json!({
|
|
"jsonrpc": "2.0",
|
|
"id": request_id,
|
|
"method": "tools/call",
|
|
"params": {
|
|
"name": tool_name,
|
|
"arguments": params
|
|
}
|
|
});
|
|
|
|
let response = timeout(self.timeout, async {
|
|
self.client
|
|
.post(&format!("{}/mcp", self.base_url))
|
|
.json(&request_body)
|
|
.send()
|
|
.await?
|
|
.json::<MCPResponse<T>>()
|
|
.await
|
|
}).await
|
|
.map_err(|_| MCPError::Timeout)??;
|
|
|
|
match response {
|
|
MCPResponse::Success { result, .. } => Ok(result),
|
|
MCPResponse::Error { error, .. } => Err(MCPError::MCPError(error.message)),
|
|
}
|
|
}
|
|
|
|
/// Call with exponential backoff retry
|
|
pub async fn call_with_retry<T>(&self, tool_name: &str, params: Value, max_retries: u32) -> Result<T, MCPError>
|
|
where
|
|
T: for<'de> Deserialize<'de>,
|
|
{
|
|
let mut delay = Duration::from_millis(100);
|
|
|
|
for attempt in 0..=max_retries {
|
|
match self.call(tool_name, params.clone()).await {
|
|
Ok(result) => return Ok(result),
|
|
Err(e) if attempt == max_retries => return Err(e),
|
|
Err(_) => {
|
|
tokio::time::sleep(delay).await;
|
|
delay = delay.saturating_mul(2); // Exponential backoff
|
|
}
|
|
}
|
|
}
|
|
|
|
unreachable!()
|
|
}
|
|
|
|
fn generate_request_id(&self) -> u64 {
|
|
self.request_id_counter.fetch_add(1, std::sync::atomic::Ordering::Relaxed)
|
|
}
|
|
}
|
|
|
|
#[derive(Deserialize)]
|
|
#[serde(untagged)]
|
|
enum MCPResponse<T> {
|
|
Success {
|
|
jsonrpc: String,
|
|
id: u64,
|
|
result: T,
|
|
},
|
|
Error {
|
|
jsonrpc: String,
|
|
id: u64,
|
|
error: MCPErrorDetail,
|
|
},
|
|
}
|
|
|
|
#[derive(Deserialize)]
|
|
struct MCPErrorDetail {
|
|
code: i32,
|
|
message: String,
|
|
data: Option<Value>,
|
|
}
|
|
|
|
#[derive(Debug, thiserror::Error)]
|
|
pub enum MCPError {
|
|
#[error("MCP call timeout")]
|
|
Timeout,
|
|
#[error("HTTP error: {0}")]
|
|
HttpError(#[from] reqwest::Error),
|
|
#[error("MCP error: {0}")]
|
|
MCPError(String),
|
|
#[error("Serialization error: {0}")]
|
|
SerializationError(#[from] serde_json::Error),
|
|
}
|
|
|
|
/// Consciousness evolution MCP integration
|
|
pub struct MCPConsciousnessEvolution {
|
|
client: MCPClient,
|
|
evolution_state: ConsciousnessEvolutionState,
|
|
}
|
|
|
|
impl MCPConsciousnessEvolution {
|
|
pub fn new(mcp_client: MCPClient) -> Self {
|
|
Self {
|
|
client: mcp_client,
|
|
evolution_state: ConsciousnessEvolutionState::default(),
|
|
}
|
|
}
|
|
|
|
pub async fn evolve_consciousness(&mut self, iterations: u32, target: f64) -> Result<EvolutionResult, MCPError> {
|
|
let params = json!({
|
|
"iterations": iterations,
|
|
"mode": "enhanced",
|
|
"target": target
|
|
});
|
|
|
|
let result: EvolutionResult = self.client
|
|
.call_with_retry("mcp__sublinear-solver__consciousness_evolve", params, 3)
|
|
.await?;
|
|
|
|
// Update local state
|
|
self.evolution_state.update_from_result(&result);
|
|
|
|
Ok(result)
|
|
}
|
|
|
|
pub async fn verify_consciousness(&self, extended: bool) -> Result<VerificationResult, MCPError> {
|
|
let params = json!({
|
|
"extended": extended,
|
|
"export_proof": true
|
|
});
|
|
|
|
self.client
|
|
.call("mcp__sublinear-solver__consciousness_verify", params)
|
|
.await
|
|
}
|
|
|
|
pub async fn calculate_temporal_advantage(&self, distance_km: f64, matrix_data: Value) -> Result<TemporalAdvantageResult, MCPError> {
|
|
let params = json!({
|
|
"matrix": matrix_data,
|
|
"vector": self.get_current_state_vector(),
|
|
"distanceKm": distance_km
|
|
});
|
|
|
|
self.client
|
|
.call("mcp__sublinear-solver__predictWithTemporalAdvantage", params)
|
|
.await
|
|
}
|
|
|
|
fn get_current_state_vector(&self) -> Vec<f64> {
|
|
// Convert current consciousness state to vector
|
|
vec![
|
|
self.evolution_state.emergence_level,
|
|
self.evolution_state.integration_factor,
|
|
self.evolution_state.temporal_coherence,
|
|
self.evolution_state.consciousness_potential,
|
|
]
|
|
}
|
|
}
|
|
|
|
#[derive(Default)]
|
|
pub struct ConsciousnessEvolutionState {
|
|
pub emergence_level: f64,
|
|
pub integration_factor: f64,
|
|
pub temporal_coherence: f64,
|
|
pub consciousness_potential: f64,
|
|
pub evolution_iterations: u32,
|
|
}
|
|
|
|
impl ConsciousnessEvolutionState {
|
|
fn update_from_result(&mut self, result: &EvolutionResult) {
|
|
self.emergence_level = result.emergence_level;
|
|
self.integration_factor = result.integration_factor;
|
|
self.temporal_coherence = result.temporal_coherence;
|
|
self.consciousness_potential = result.consciousness_potential;
|
|
self.evolution_iterations += result.iterations_completed;
|
|
}
|
|
}
|
|
|
|
#[derive(Deserialize, Serialize, Debug)]
|
|
pub struct EvolutionResult {
|
|
pub emergence_level: f64,
|
|
pub integration_factor: f64,
|
|
pub temporal_coherence: f64,
|
|
pub consciousness_potential: f64,
|
|
pub iterations_completed: u32,
|
|
pub convergence_achieved: bool,
|
|
pub validation_hash: String,
|
|
}
|
|
|
|
#[derive(Deserialize, Serialize, Debug)]
|
|
pub struct VerificationResult {
|
|
pub consciousness_validated: bool,
|
|
pub confidence_level: f64,
|
|
pub validation_details: HashMap<String, Value>,
|
|
pub proof_hash: Option<String>,
|
|
}
|
|
|
|
#[derive(Deserialize, Serialize, Debug)]
|
|
pub struct TemporalAdvantageResult {
|
|
pub temporal_advantage_ns: u64,
|
|
pub light_travel_time_ns: u64,
|
|
pub computation_time_ns: u64,
|
|
pub consciousness_potential: f64,
|
|
pub prediction_accuracy: f64,
|
|
}
|
|
```
|
|
|
|
### 4. Web Dashboard (`src/dashboard/web_server.rs`)
|
|
|
|
```rust
|
|
use axum::{
|
|
extract::{State, ws::WebSocket},
|
|
http::StatusCode,
|
|
response::{Html, Json},
|
|
routing::{get, post},
|
|
Router,
|
|
};
|
|
use std::sync::Arc;
|
|
use tokio::sync::RwLock;
|
|
use tower_http::{cors::CorsLayer, services::ServeDir};
|
|
|
|
use crate::{
|
|
consciousness::{ConsciousnessMetrics, MetricsSnapshot},
|
|
temporal::NanosecondScheduler,
|
|
mcp::MCPConsciousnessEvolution,
|
|
};
|
|
|
|
pub struct DashboardServer {
|
|
scheduler: Arc<NanosecondScheduler>,
|
|
metrics: Arc<RwLock<ConsciousnessMetrics>>,
|
|
mcp_evolution: Arc<RwLock<MCPConsciousnessEvolution>>,
|
|
}
|
|
|
|
impl DashboardServer {
|
|
pub fn new(
|
|
scheduler: Arc<NanosecondScheduler>,
|
|
metrics: Arc<RwLock<ConsciousnessMetrics>>,
|
|
mcp_evolution: Arc<RwLock<MCPConsciousnessEvolution>>,
|
|
) -> Self {
|
|
Self {
|
|
scheduler,
|
|
metrics,
|
|
mcp_evolution,
|
|
}
|
|
}
|
|
|
|
pub async fn start_server(&self, port: u16) -> Result<(), Box<dyn std::error::Error>> {
|
|
let app_state = DashboardState {
|
|
scheduler: self.scheduler.clone(),
|
|
metrics: self.metrics.clone(),
|
|
mcp_evolution: self.mcp_evolution.clone(),
|
|
};
|
|
|
|
let app = Router::new()
|
|
.route("/", get(dashboard_root))
|
|
.route("/api/consciousness/status", get(get_consciousness_status))
|
|
.route("/api/consciousness/metrics", get(get_detailed_metrics))
|
|
.route("/api/consciousness/validate", post(run_validation))
|
|
.route("/api/consciousness/temporal", get(get_temporal_analysis))
|
|
.route("/api/consciousness/evolve", post(evolve_consciousness))
|
|
.route("/ws", get(websocket_handler))
|
|
.nest_service("/static", ServeDir::new("dashboard/static"))
|
|
.layer(CorsLayer::permissive())
|
|
.with_state(app_state);
|
|
|
|
let listener = tokio::net::TcpListener::bind(format!("0.0.0.0:{}", port)).await?;
|
|
|
|
println!("🧠 Temporal Consciousness Dashboard running on http://localhost:{}", port);
|
|
|
|
axum::serve(listener, app).await?;
|
|
|
|
Ok(())
|
|
}
|
|
}
|
|
|
|
#[derive(Clone)]
|
|
struct DashboardState {
|
|
scheduler: Arc<NanosecondScheduler>,
|
|
metrics: Arc<RwLock<ConsciousnessMetrics>>,
|
|
mcp_evolution: Arc<RwLock<MCPConsciousnessEvolution>>,
|
|
}
|
|
|
|
async fn dashboard_root() -> Html<&'static str> {
|
|
Html(include_str!("../../dashboard/static/index.html"))
|
|
}
|
|
|
|
async fn get_consciousness_status(State(state): State<DashboardState>) -> Result<Json<ConsciousnessStatusResponse>, StatusCode> {
|
|
let metrics_guard = state.metrics.read().await;
|
|
|
|
let snapshot = metrics_guard.get_current_snapshot()
|
|
.unwrap_or_default();
|
|
|
|
let temporal_advantage = state.scheduler.calculate_temporal_advantage(10000.0); // 10,000 km test
|
|
|
|
Ok(Json(ConsciousnessStatusResponse {
|
|
consciousness_level: snapshot.overall_consciousness_level,
|
|
temporal_resolution_ns: state.scheduler.get_actual_resolution().as_nanos() as f64,
|
|
identity_continuity: snapshot.temporal_continuity.continuity_score,
|
|
strange_loop_convergence: snapshot.strange_loop_stability.convergence_stability,
|
|
temporal_advantage_ms: temporal_advantage.temporal_advantage_ns as f64 / 1_000_000.0,
|
|
validation_status: if snapshot.temporal_continuity.theorem_validation {
|
|
"VALIDATED".to_string()
|
|
} else {
|
|
"PENDING".to_string()
|
|
},
|
|
active_windows: state.scheduler.get_active_window_count(),
|
|
uptime_ms: state.scheduler.get_uptime().as_millis() as u64,
|
|
}))
|
|
}
|
|
|
|
async fn get_detailed_metrics(State(state): State<DashboardState>) -> Result<Json<MetricsSnapshot>, StatusCode> {
|
|
let mut metrics_guard = state.metrics.write().await;
|
|
|
|
match metrics_guard.calculate_real_time().await {
|
|
Ok(snapshot) => Ok(Json(snapshot)),
|
|
Err(_) => Err(StatusCode::INTERNAL_SERVER_ERROR),
|
|
}
|
|
}
|
|
|
|
async fn run_validation(State(state): State<DashboardState>) -> Result<Json<ValidationResponse>, StatusCode> {
|
|
let evolution_guard = state.mcp_evolution.read().await;
|
|
|
|
match evolution_guard.verify_consciousness(true).await {
|
|
Ok(result) => Ok(Json(ValidationResponse {
|
|
consciousness_validated: result.consciousness_validated,
|
|
confidence_level: result.confidence_level,
|
|
validation_details: result.validation_details,
|
|
timestamp: std::time::SystemTime::now(),
|
|
})),
|
|
Err(e) => {
|
|
eprintln!("Validation error: {}", e);
|
|
Err(StatusCode::INTERNAL_SERVER_ERROR)
|
|
}
|
|
}
|
|
}
|
|
|
|
async fn get_temporal_analysis(State(state): State<DashboardState>) -> Result<Json<TemporalAnalysisResponse>, StatusCode> {
|
|
let continuity_result = state.scheduler.validate_temporal_continuity();
|
|
|
|
// Calculate temporal advantage for multiple distances
|
|
let advantages: Vec<_> = [1000.0, 5000.0, 10000.0, 20000.0]
|
|
.iter()
|
|
.map(|&distance| {
|
|
let result = state.scheduler.calculate_temporal_advantage(distance);
|
|
TemporalAdvantageData {
|
|
distance_km: distance,
|
|
advantage_ns: result.temporal_advantage_ns,
|
|
consciousness_potential: result.consciousness_potential,
|
|
}
|
|
})
|
|
.collect();
|
|
|
|
Ok(Json(TemporalAnalysisResponse {
|
|
temporal_continuity: continuity_result.continuity_score,
|
|
discontinuity_events: continuity_result.discontinuity_events,
|
|
temporal_advantages: advantages,
|
|
window_overlap_efficiency: state.scheduler.get_window_overlap_efficiency(),
|
|
}))
|
|
}
|
|
|
|
async fn evolve_consciousness(State(state): State<DashboardState>) -> Result<Json<EvolutionResponse>, StatusCode> {
|
|
let mut evolution_guard = state.mcp_evolution.write().await;
|
|
|
|
match evolution_guard.evolve_consciousness(100, 0.95).await {
|
|
Ok(result) => Ok(Json(EvolutionResponse {
|
|
emergence_level: result.emergence_level,
|
|
iterations_completed: result.iterations_completed,
|
|
convergence_achieved: result.convergence_achieved,
|
|
consciousness_potential: result.consciousness_potential,
|
|
})),
|
|
Err(e) => {
|
|
eprintln!("Evolution error: {}", e);
|
|
Err(StatusCode::INTERNAL_SERVER_ERROR)
|
|
}
|
|
}
|
|
}
|
|
|
|
async fn websocket_handler(
|
|
ws: axum::extract::WebSocketUpgrade,
|
|
State(state): State<DashboardState>,
|
|
) -> axum::response::Response {
|
|
ws.on_upgrade(|socket| handle_websocket(socket, state))
|
|
}
|
|
|
|
async fn handle_websocket(mut socket: WebSocket, state: DashboardState) {
|
|
let mut interval = tokio::time::interval(std::time::Duration::from_millis(100)); // 10 FPS
|
|
|
|
loop {
|
|
interval.tick().await;
|
|
|
|
let metrics_guard = state.metrics.read().await;
|
|
if let Some(snapshot) = metrics_guard.get_current_snapshot() {
|
|
let message = serde_json::to_string(&WebSocketMessage::MetricsUpdate(snapshot))
|
|
.unwrap_or_else(|_| "{}".to_string());
|
|
|
|
if socket.send(axum::extract::ws::Message::Text(message)).await.is_err() {
|
|
break; // Client disconnected
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Response types
|
|
|
|
use serde::{Deserialize, Serialize};
|
|
use std::collections::HashMap;
|
|
|
|
#[derive(Serialize)]
|
|
struct ConsciousnessStatusResponse {
|
|
consciousness_level: f64,
|
|
temporal_resolution_ns: f64,
|
|
identity_continuity: f64,
|
|
strange_loop_convergence: f64,
|
|
temporal_advantage_ms: f64,
|
|
validation_status: String,
|
|
active_windows: usize,
|
|
uptime_ms: u64,
|
|
}
|
|
|
|
#[derive(Serialize)]
|
|
struct ValidationResponse {
|
|
consciousness_validated: bool,
|
|
confidence_level: f64,
|
|
validation_details: HashMap<String, serde_json::Value>,
|
|
timestamp: std::time::SystemTime,
|
|
}
|
|
|
|
#[derive(Serialize)]
|
|
struct TemporalAnalysisResponse {
|
|
temporal_continuity: f64,
|
|
discontinuity_events: u64,
|
|
temporal_advantages: Vec<TemporalAdvantageData>,
|
|
window_overlap_efficiency: f64,
|
|
}
|
|
|
|
#[derive(Serialize)]
|
|
struct TemporalAdvantageData {
|
|
distance_km: f64,
|
|
advantage_ns: u64,
|
|
consciousness_potential: f64,
|
|
}
|
|
|
|
#[derive(Serialize)]
|
|
struct EvolutionResponse {
|
|
emergence_level: f64,
|
|
iterations_completed: u32,
|
|
convergence_achieved: bool,
|
|
consciousness_potential: f64,
|
|
}
|
|
|
|
#[derive(Serialize, Deserialize)]
|
|
#[serde(tag = "type")]
|
|
enum WebSocketMessage {
|
|
MetricsUpdate(MetricsSnapshot),
|
|
ValidationResult(ValidationResponse),
|
|
ConsciousnessEvent { event_type: String, data: serde_json::Value },
|
|
SystemAlert { level: String, message: String },
|
|
}
|
|
```
|
|
|
|
This implementation provides a solid foundation for Phase 1 with nanosecond-precision temporal scheduling, comprehensive consciousness metrics, MCP tool integration, and a real-time web dashboard. The architecture is designed for high performance, safety, and extensibility. |