""" Multiversal Adapter Engine for JARVIS-2v Implements parallel universes as compute nodes with non-destructive cross-universe learning """ import json import math import uuid from dataclasses import dataclass, field from typing import Dict, List, Optional, Set, Tuple, Any, Union from enum import Enum from pathlib import Path import time import random from .adapter_engine import Adapter, AdapterGraph, YZXBitRouter, AdapterStatus, QuantumArtifact class UniverseState(Enum): """States of a universe in the multiverse""" ACTIVE = "active" DORMANT = "dormant" COLLAPSED = "collapsed" MERGED = "merged" ISOLATED = "isolated" @dataclass class MultiversalAdapter: """Extended adapter with multiversal addressing and interference patterns""" id: str task_tags: List[str] y_bits: List[int] # task/domain bits z_bits: List[int] # difficulty/precision bits x_bits: List[int] # experimental toggles parameters: Dict[str, Any] = field(default_factory=dict) rules: List[str] = field(default_factory=list) prompts: List[str] = field(default_factory=list) parent_ids: List[str] = field(default_factory=list) child_ids: List[str] = field(default_factory=list) created_at: float = field(default_factory=time.time) last_used: float = field(default_factory=time.time) success_count: int = 0 total_calls: int = 0 domains: Set[str] = field(default_factory=set) status: str = "active" version: int = 1 universe_id: str = field(default_factory=lambda: f"universe_{uuid.uuid4().hex[:8]}") universe_bits: List[int] = field(default_factory=lambda: [0] * 16) # Multiversal dimension branch_path: List[str] = field(default_factory=list) # Decision point history interference_weight: float = 0.0 # How much this universe influences others coherence_level: float = 1.0 # Quantum coherence (0-1) artifact_count: int = 0 # Number of artifacts generated cross_universe_success_rate: float = 0.0 # Success when borrowed by other universes parent_universe_ids: List[str] = field(default_factory=list) # Branching history def to_dict(self) -> Dict[str, Any]: """Serialize multiversal adapter to dictionary""" return { "id": self.id, "task_tags": self.task_tags, "y_bits": self.y_bits, "z_bits": self.z_bits, "x_bits": self.x_bits, "parameters": self.parameters, "rules": self.rules, "prompts": self.prompts, "parent_ids": self.parent_ids, "child_ids": self.child_ids, "created_at": self.created_at, "last_used": self.last_used, "success_count": self.success_count, "total_calls": self.total_calls, "domains": list(self.domains), "status": self.status, "version": self.version, "universe_id": self.universe_id, "universe_bits": self.universe_bits, "branch_path": self.branch_path, "interference_weight": self.interference_weight, "coherence_level": self.coherence_level, "artifact_count": self.artifact_count, "cross_universe_success_rate": self.cross_universe_success_rate, "parent_universe_ids": self.parent_universe_ids } @classmethod def from_dict(cls, data: Dict[str, Any]) -> "MultiversalAdapter": """Deserialize multiversal adapter from dictionary""" return cls( id=data["id"], task_tags=data.get("task_tags", []), y_bits=data.get("y_bits", [0] * 16), z_bits=data.get("z_bits", [0] * 8), x_bits=data.get("x_bits", [0] * 8), parameters=data.get("parameters", {}), rules=data.get("rules", []), prompts=data.get("prompts", []), parent_ids=data.get("parent_ids", []), child_ids=data.get("child_ids", []), created_at=data.get("created_at", time.time()), last_used=data.get("last_used", time.time()), success_count=data.get("success_count", 0), total_calls=data.get("total_calls", 0), domains=set(data.get("domains", [])), status=data.get("status", "active"), version=data.get("version", 1), universe_id=data.get("universe_id", f"universe_{uuid.uuid4().hex[:8]}"), universe_bits=data.get("universe_bits", [0] * 16), branch_path=data.get("branch_path", []), interference_weight=data.get("interference_weight", 0.0), coherence_level=data.get("coherence_level", 1.0), artifact_count=data.get("artifact_count", 0), cross_universe_success_rate=data.get("cross_universe_success_rate", 0.0), parent_universe_ids=data.get("parent_universe_ids", []) ) class MultiversalRoutingEngine: """Engine for routing queries across the multiverse using interference patterns""" def __init__(self, y_bits: int = 16, z_bits: int = 8, x_bits: int = 8, u_bits: int = 16): self.y_size = y_bits self.z_size = z_bits self.x_size = x_bits self.u_size = u_bits # Universe bits self.persistence_file = Path("./multiversal_patterns.json") self.patterns = self._load_patterns() def _load_patterns(self) -> Dict[str, Any]: """Load multiversal routing patterns from disk""" if self.persistence_file.exists(): try: with open(self.persistence_file, 'r') as f: return json.load(f) except json.JSONDecodeError: return {} return {} def _save_patterns(self): """Save multiversal routing patterns to disk""" with open(self.persistence_file, 'w') as f: json.dump(self.patterns, f, indent=2) def generate_universe_signature(self, seed_data: Dict[str, Any]) -> List[int]: """Generate universe signature from problem context""" universe_bits = [0] * self.u_size # Map problem characteristics to universe bits problem_type = seed_data.get("type", "unknown") complexity = seed_data.get("complexity", 1) domain = seed_data.get("domain", "general") # Domain-based universe selection domain_map = { "medical": 0, "cancer": 1, "biology": 2, "chemistry": 3, "physics": 4, "quantum": 5, "computing": 6, "ai": 7, "engineering": 8, "mathematics": 9, "psychology": 10, "sociology": 11, "economics": 12, "art": 13, "literature": 14 } if domain in domain_map: universe_bits[domain_map[domain]] = 1 # Complexity affects multiple bits complexity_bits = min(15, int(complexity * 8)) for i in range(complexity_bits): if i < self.u_size - 15: universe_bits[15 + i] = 1 return universe_bits def calculate_interference_weight(self, source_universe: str, target_universe: str, source_adapter: MultiversalAdapter, target_problem: Dict[str, Any]) -> float: """Calculate interference weight between universes for cross-universe knowledge transfer""" # Base interference from source adapter base_weight = source_adapter.interference_weight # Domain similarity boost problem_domain = target_problem.get("domain", "general") source_domains = list(source_adapter.domains) domain_match = 1.0 if problem_domain in source_domains else 0.3 # Coherence factor (more coherent universes have stronger interference) coherence_factor = source_adapter.coherence_level # Success rate boost success_boost = 1.0 + source_adapter.cross_universe_success_rate # Universe distance (closer universes interfere more) universe_distance = self._calculate_universe_distance(source_universe, target_universe) distance_factor = math.exp(-universe_distance * 0.1) final_weight = base_weight * domain_match * coherence_factor * success_boost * distance_factor return min(1.0, final_weight) # Cap at 1.0 def _calculate_universe_distance(self, universe1: str, universe2: str) -> float: """Calculate quantum distance between two universes""" if universe1 == universe2: return 0.0 # Use hash-based distance for deterministic universe relationships hash1 = int(universe1[-8:], 16) if len(universe1) >= 8 else 0 hash2 = int(universe2[-8:], 16) if len(universe2) >= 8 else 0 xor_diff = hash1 ^ hash2 max_bits = 32 distance = bin(xor_diff).count('1') / max_bits return distance def route_to_parallel_universes(self, query: Dict[str, Any], available_adapters: List[MultiversalAdapter], target_universe: str = None) -> List[Tuple[MultiversalAdapter, float]]: """Route query to best universes using interference patterns""" if target_universe is None: target_universe = f"universe_{uuid.uuid4().hex[:8]}" scored_universes = [] for adapter in available_adapters: if adapter.status != AdapterStatus.ACTIVE: continue # Skip if same universe unless specifically looking for cross-universe transfer if adapter.universe_id == target_universe: continue interference_weight = self.calculate_interference_weight( adapter.universe_id, target_universe, adapter, query ) # Boost if this universe has solved similar problems problem_domain = query.get("domain", "general") if problem_domain in adapter.domains: interference_weight *= 1.5 # Boost high-coherence universes if adapter.coherence_level > 0.8: interference_weight *= 1.3 if interference_weight > 0.1: # Threshold for relevance scored_universes.append((adapter, interference_weight)) # Sort by interference weight and return top universes scored_universes.sort(key=lambda x: x[1], reverse=True) return scored_universes[:5] # Top 5 universes def amplify_successful_universe(self, successful_adapter: MultiversalAdapter, source_problem: Dict[str, Any]) -> None: """Amplify a successful universe's interference pattern""" # Increase interference weight based on success success_boost = 0.1 + (successful_adapter.success_count / max(1, successful_adapter.total_calls)) * 0.2 successful_adapter.interference_weight = min(1.0, successful_adapter.interference_weight + success_boost) # Increase coherence level successful_adapter.coherence_level = min(1.0, successful_adapter.coherence_level + 0.05) # Update cross-universe success rate if successful_adapter.total_calls > 0: current_rate = successful_adapter.cross_universe_success_rate new_rate = (current_rate * 0.9) + (0.1 * (successful_adapter.success_count / successful_adapter.total_calls)) successful_adapter.cross_universe_success_rate = new_rate # Save updated patterns self.patterns[f"universe_{successful_adapter.universe_id}"] = { "interference_weight": successful_adapter.interference_weight, "coherence_level": successful_adapter.coherence_level, "cross_universe_success_rate": successful_adapter.cross_universe_success_rate, "last_updated": time.time() } self._save_patterns() @dataclass class Universe: """Represents a parallel universe in the multiverse""" universe_id: str parent_universe_id: Optional[str] = None decision_point: Optional[str] = None branch_timestamp: float = field(default_factory=time.time) state: str = "active" # Use string instead of enum coherence_level: float = 1.0 artifact_count: int = 0 total_solutions: int = 0 successful_solutions: int = 0 interference_reach: float = 0.5 # How far this universe's influence extends def to_dict(self) -> Dict[str, Any]: return { "universe_id": self.universe_id, "parent_universe_id": self.parent_universe_id, "decision_point": self.decision_point, "branch_timestamp": self.branch_timestamp, "state": self.state, "coherence_level": self.coherence_level, "artifact_count": self.artifact_count, "total_solutions": self.total_solutions, "successful_solutions": self.successful_solutions, "interference_reach": self.interference_reach } class MultiversalComputeEngine: """Main engine for multiversal computing with parallel universe simulation""" def __init__(self, config: Dict[str, Any]): self.config = config self.storage_path = Path(config.get("multiverse", {}).get("storage_path", "./multiverse")) self.storage_path.mkdir(parents=True, exist_ok=True) # Initialize components self.universes: Dict[str, Universe] = {} self.multiversal_routing = MultiversalRoutingEngine( config.get("bits", {}).get("y_bits", 16), config.get("bits", {}).get("z_bits", 8), config.get("bits", {}).get("x_bits", 8), config.get("bits", {}).get("u_bits", 16) # Universe bits ) # Load existing universes self._load_universes() def create_parallel_universe(self, parent_universe_id: str, decision_point: str, problem_context: Dict[str, Any]) -> str: """Create a new parallel universe from a decision point""" new_universe_id = f"universe_{uuid.uuid4().hex[:8]}" # Create new universe new_universe = Universe( universe_id=new_universe_id, parent_universe_id=parent_universe_id, decision_point=decision_point, coherence_level=0.9 # Slightly less coherent than parent ) self.universes[new_universe_id] = new_universe # Update parent universe if parent_universe_id in self.universes: parent = self.universes[parent_universe_id] parent.artifact_count += 1 # Parent's interference reach might expand parent.interference_reach = min(1.0, parent.interference_reach + 0.1) # Save universe self._save_universe(new_universe) print(f"🌌 Created parallel universe {new_universe_id} from {parent_universe_id}") print(f" Decision point: {decision_point}") return new_universe_id def simulate_universe_evolution(self, universe_id: str, steps: int = 10) -> Dict[str, Any]: """Simulate evolution of a universe over time steps""" if universe_id not in self.universes: return {"error": f"Universe {universe_id} not found"} universe = self.universes[universe_id] evolution_log = [] for step in range(steps): # Simulate quantum fluctuations coherence_change = random.gauss(0, 0.05) universe.coherence_level = max(0.1, min(1.0, universe.coherence_level + coherence_change)) # Random branching events if random.random() < 0.1: # 10% chance per step new_universe_id = self.create_parallel_universe( universe_id, f"branch_{step}_{random.randint(1000, 9999)}", {"evolution_step": step} ) evolution_log.append({ "step": step, "event": "branching", "new_universe": new_universe_id, "coherence": universe.coherence_level }) # Interference events if random.random() < 0.2: # 20% chance per step universe.interference_reach = min(1.0, universe.interference_reach + 0.05) evolution_log.append({ "step": step, "event": "interference_amplification", "coherence": universe.coherence_level, "interference_reach": universe.interference_reach }) evolution_log.append({ "step": step, "coherence": universe.coherence_level, "artifact_count": universe.artifact_count, "total_solutions": universe.total_solutions }) # Save updated universe self._save_universe(universe) return { "universe_id": universe_id, "evolution_steps": steps, "final_coherence": universe.coherence_level, "final_interference_reach": universe.interference_reach, "events": evolution_log } def find_successful_universes(self, problem_domain: str, similarity_threshold: float = 0.7) -> List[Tuple[str, float]]: """Find universes that have been successful with similar problems""" successful_universes = [] for universe_id, universe in self.universes.items(): if universe.state != UniverseState.ACTIVE: continue success_rate = universe.successful_solutions / max(1, universe.total_solutions) # Consider coherence and success rate if universe.coherence_level > 0.6 and success_rate > similarity_threshold: # Calculate reach factor reach_factor = universe.interference_reach * universe.coherence_level successful_universes.append((universe_id, reach_factor)) # Sort by reach factor successful_universes.sort(key=lambda x: x[1], reverse=True) return successful_universes[:10] # Top 10 def find_successful_universes(self, problem_domain: str, similarity_threshold: float = 0.7) -> List[Tuple[str, float]]: """Find universes that have been successful with similar problems""" successful_universes = [] for universe_id, universe in self.universes.items(): if universe.state != "active": continue success_rate = universe.successful_solutions / max(1, universe.total_solutions) # Consider coherence and success rate if universe.coherence_level > 0.6 and success_rate > similarity_threshold: # Calculate reach factor reach_factor = universe.interference_reach * universe.coherence_level successful_universes.append((universe_id, reach_factor)) # Sort by reach factor successful_universes.sort(key=lambda x: x[1], reverse=True) return successful_universes[:10] # Top 10 def borrow_knowledge_from_parallel_universe(self, source_universe_id: str, target_problem: Dict[str, Any]) -> Dict[str, Any]: """Borrow knowledge from a successful parallel universe""" if source_universe_id not in self.universes: return {"error": f"Source universe {source_universe_id} not found"} source_universe = self.universes[source_universe_id] # Create "echo" artifact from source universe echo_artifact = { "type": "multiversal_echo", "source_universe": source_universe_id, "target_problem": target_problem, "echo_strength": source_universe.coherence_level * source_universe.interference_reach, "borrowed_at": time.time(), "adaptation_notes": f"Borrowed from {source_universe_id} with coherence {source_universe.coherence_level:.2f}" } # Update source universe statistics source_universe.successful_solutions += 1 source_universe.interference_reach = min(1.0, source_universe.interference_reach + 0.02) self._save_universe(source_universe) return { "success": True, "echo_artifact": echo_artifact, "source_universe_stats": { "coherence_level": source_universe.coherence_level, "interference_reach": source_universe.interference_reach, "success_rate": source_universe.successful_solutions / max(1, source_universe.total_solutions) } } def get_multiverse_overview(self) -> Dict[str, Any]: """Get overview of the entire multiverse""" total_universes = len(self.universes) active_universes = sum(1 for u in self.universes.values() if u.state == UniverseState.ACTIVE) total_artifacts = sum(u.artifact_count for u in self.universes.values()) avg_coherence = sum(u.coherence_level for u in self.universes.values()) / max(1, total_universes) # Find most successful universe best_universe = None best_score = 0 for universe in self.universes.values(): score = universe.coherence_level * (universe.successful_solutions / max(1, universe.total_solutions)) if score > best_score: best_score = score best_universe = universe.universe_id return { "total_universes": total_universes, "active_universes": active_universes, "total_artifacts": total_artifacts, "average_coherence": avg_coherence, "most_successful_universe": best_universe, "multiverse_health": avg_coherence * (active_universes / max(1, total_universes)) } def _load_universes(self): """Load existing universes from disk""" universe_file = self.storage_path / "universes.json" if universe_file.exists(): try: with open(universe_file, 'r') as f: data = json.load(f) for universe_data in data.get("universes", []): # Ensure state is a string, not an enum if "state" in universe_data and hasattr(universe_data["state"], "value"): universe_data["state"] = universe_data["state"].value elif "state" not in universe_data: universe_data["state"] = "active" universe = Universe(**universe_data) self.universes[universe.universe_id] = universe except (json.JSONDecodeError, TypeError): pass def _save_universe(self, universe: Universe): """Save universe to disk""" # Update storage all_universes = [u.to_dict() for u in self.universes.values()] universe_file = self.storage_path / "universes.json" with open(universe_file, 'w') as f: json.dump({"universes": all_universes}, f, indent=2) def _save_universes(self): """Save all universes to disk""" universe_file = self.storage_path / "universes.json" all_universes = [u.to_dict() for u in self.universes.values()] with open(universe_file, 'w') as f: json.dump({"universes": all_universes}, f, indent=2) __all__ = [ "MultiversalAdapter", "MultiversalRoutingEngine", "MultiversalComputeEngine", "Universe", "UniverseState" ]