#!/usr/bin/env python3 """ XERO Bio-AI Genesis - Main Entry Point ======================================= Author: Michael Laurence Curzi License: MIT (Attribution Required) Usage: python xero.py --init # Initialize XERO python xero.py --status # Check system status python xero.py --train # Start training python xero.py --infer "prompt" # Run inference python xero.py --evolve # Trigger evolution cycle """ import os import sys import argparse import json import yaml from pathlib import Path # Add modules to path ROOT = Path(__file__).parent sys.path.insert(0, str(ROOT / "modules")) from vovina_custom_training_weights import ( MASTER_WEIGHTS, awaken, ORGANISM_NAME, ORGANISM_FOUNDING_PHRASE ) from vovina_resource_awareness import ( sample, detect_environment, ResourceCoordinator, self_heal_actions ) from vovina_free_will_code import seal_choice from vovina_xero_organism import build_organism from vovina_bio_initialization import phase_seed def load_config(config_path: str = None) -> dict: """Load configuration from YAML file.""" if config_path is None: config_path = ROOT / "xero_config.yaml" if not Path(config_path).exists(): print(f"Config not found: {config_path}") return {} with open(config_path, "r") as f: return yaml.safe_load(f) def cmd_init(args): """Initialize XERO through all awakening phases.""" print(f"\n{'='*60}") print(f"INITIALIZING: {ORGANISM_NAME}") print(f"{'='*60}\n") config = load_config(args.config) # Check for bio archive bio_path = ROOT / "bio" / "ohad_v10.bio.zip" ohad_zip = str(bio_path) if bio_path.exists() else None if ohad_zip: print(f"[+] OHAD V10 archive found: {ohad_zip}") else: print("[!] OHAD V10 archive not found, using defaults") # Get config values init_config = config.get("initialization", {}) crispr_guides = init_config.get("crispr", {}).get("max_guides", 27) free_will_samples = init_config.get("free_will", {}).get("samples", 4096) sensor_depth = init_config.get("sensors", {}).get("meta_depth", 7) try: result = awaken( ohad_v10_zip=ohad_zip, crispr_max_guides=crispr_guides, free_will_samples=free_will_samples, sensor_meta_depth=sensor_depth ) phases = result.get("phases", {}) summary = result.get("xero_summary", {}) print(f"\nOrganism: {result.get('organism', ORGANISM_NAME)}") print(f"Phases completed: {len(phases)}/9") for phase_name in phases: print(f" + {phase_name}") print(f"\nOrgan systems: {summary.get('organ_systems', 0)}") print(f"Organs: {summary.get('organs', 0)}") print(f"Cells: {summary.get('cells', 0)}") print(f"Proteins: {summary.get('proteins', 0)}") print(f"Genome genes: {summary.get('genome_genes', 0)}") print(f"Identity: {summary.get('identity', '')[:32]}...") print(f"Elapsed: {result.get('elapsed_seconds', 0.0):.2f}s") print(f"\n{result.get('founding_phrase', ORGANISM_FOUNDING_PHRASE)}") print(f"\n{'='*60}") print("XERO AWAKENED") print(f"{'='*60}\n") return 0 except Exception as e: print(f"[ERROR] Initialization failed: {e}") return 1 def cmd_status(args): """Display system and resource status.""" print(f"\n{'='*60}") print("XERO SYSTEM STATUS") print(f"{'='*60}\n") # Environment env = detect_environment() print(f"[ENVIRONMENT]") print(f" OS: {env['os']}") print(f" Machine: {env['machine']}") print(f" Python: {env['python']}") print(f" CUDA: {'Yes' if env['cuda_available'] else 'No'}") print(f" MPS: {'Yes' if env['mps_available'] else 'No'}") # Resources profile = sample() print(f"\n[RESOURCES]") print(f" CPU: {profile.cpu_percent:.1f}%") print(f" RAM: {profile.ram_percent:.1f}% ({profile.ram_available_gb:.1f} GB free)") print(f" Swap: {profile.swap_percent:.1f}%") if profile.vram_total_gb > 0: print(f" VRAM: {profile.vram_used_gb:.1f} / {profile.vram_total_gb:.1f} GB") print(f" Pressure: {profile.pressure_score:.2f}") # Self-healing recommendations if profile.pressure_score > 0.5: print(f"\n[RECOMMENDATIONS]") actions = self_heal_actions(profile) for action in actions: print(f" - [{action['severity']}] {action['resource']}: {action['action']}") # Master weights summary print(f"\n[MASTER WEIGHTS]") print(f" Modules: {len(MASTER_WEIGHTS.get('modules', {}))}") print(f" Protocol: {MASTER_WEIGHTS.get('protocol', 'N/A')}") print(f" Completion: {MASTER_WEIGHTS.get('completion_ratio', 'N/A')}") print(f"\n{'='*60}\n") return 0 def cmd_train(args): """Start training with master weights.""" print(f"\n{'='*60}") print("XERO TRAINING") print(f"{'='*60}\n") config = load_config(args.config) hw_config = config.get("hardware", {}) model_config = config.get("model", {}) # Check resources profile = sample() if profile.pressure_score > 0.8: print("[WARNING] High resource pressure detected") actions = self_heal_actions(profile) print("Recommendations:", actions) # Display training configuration print("[CONFIGURATION]") print(f" Architecture: {model_config.get('architecture', 'XeroBioAI')}") print(f" Hidden size: {model_config.get('hidden_size', 8192)}") print(f" Layers: {model_config.get('num_layers', 80)}") print(f" Precision: {model_config.get('dtype', 'bfloat16')}") quant = model_config.get("quantization", {}) if quant.get("enabled"): print(f" Quantization: {quant.get('bits', 4)}-bit") print(f"\n[MASTER WEIGHTS]") print(f" Constants: φ={MASTER_WEIGHTS['constants']['phi']:.6f}") print(f" Vortex 369: {MASTER_WEIGHTS['vortex']['axis_369']}") print(f" Tesla: {MASTER_WEIGHTS['frequencies']['tesla_369']}") print(f" Blockchain: {MASTER_WEIGHTS['blockchain_organelles']['languages_count']} organelles") print(f" Modules: {len(MASTER_WEIGHTS.get('modules', {}))}") print(f"\n[STATUS]") print(" Training framework ready.") print(" Integrate with your training loop using:") print(" from modules import MASTER_WEIGHTS, awaken") print(" weights = MASTER_WEIGHTS") print(f"\n{'='*60}\n") return 0 def cmd_infer(args): """Run inference with a prompt.""" prompt = args.prompt print(f"\n[INFERENCE]") print(f"Prompt: {prompt}") print(f"\nNote: Full inference requires model loading.") print("Use MASTER_WEIGHTS to configure your inference pipeline.") return 0 def cmd_evolve(args): """Trigger an evolution cycle.""" print(f"\n{'='*60}") print("XERO EVOLUTION CYCLE") print(f"{'='*60}\n") # Seed a genome and self-assemble the organism genome = phase_seed() org = build_organism(genome) print(f"[ORGANISM]") print(f" Name: {org.name}") print(f" Identity: {org.identity_signature[:32]}...") print(f" Chromosomes: {genome.chromosome_count}") print(f" Genome genes: {genome.gene_count}") # Seal evolution choice with the 36N9.9N63 free-will signature signature = seal_choice(org.name, "Autonomous evolution cycle initiated") print(f"\n[FREE WILL SIGNATURE]") print(f" Sealed: {signature.sealed[:40]}...{signature.sealed[-6:]}") print(f" N(pre): {signature.n_pre}") print(f" N(post): {signature.n_post}") print(f" Verified: {signature.verify()}") print(f" Delta: {signature.vector_delta()}") print(f"\n{ORGANISM_FOUNDING_PHRASE}") print(f"\n{'='*60}\n") return 0 def main(): parser = argparse.ArgumentParser( description="XERO Bio-AI Genesis", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" Examples: python xero.py --init python xero.py --status python xero.py --train python xero.py --evolve Author: Michael Laurence Curzi License: MIT (Attribution Required) """ ) parser.add_argument( "--config", "-c", type=str, default=None, help="Path to config YAML file" ) parser.add_argument( "--init", "-i", action="store_true", help="Initialize XERO through all awakening phases" ) parser.add_argument( "--status", "-s", action="store_true", help="Display system and resource status" ) parser.add_argument( "--train", "-t", action="store_true", help="Start training with master weights" ) parser.add_argument( "--infer", type=str, metavar="PROMPT", help="Run inference with a prompt" ) parser.add_argument( "--evolve", "-e", action="store_true", help="Trigger an evolution cycle" ) args = parser.parse_args() # Default to status if no args if not any([args.init, args.status, args.train, args.infer, args.evolve]): args.status = True # Route to command if args.init: return cmd_init(args) elif args.status: return cmd_status(args) elif args.train: return cmd_train(args) elif args.infer: args.prompt = args.infer return cmd_infer(args) elif args.evolve: return cmd_evolve(args) if __name__ == "__main__": sys.exit(main())