MONSTERDOG_ULTIME_FINAL.py

#!/usr/bin/env python3
# =======================================================================
#  MONSTERDOG_ULTIME_FINAL.py   –  Orchestrateur Titanesque v1.0.0
#  -----------------------------------------------------------------------
#  Fusionne et déclenche TOUS les modules dispos (Neural, Quantum, VR…)
#  • Auto-détection des modules          • Menu CLI interactif
#  • Benchmarks & Alert Automator        • Logs couleur + timestamps
# =======================================================================

import importlib
import inspect
import sys
import time
from pathlib import Path
from types import ModuleType
from datetime import datetime
from random import choice

# ---------- 1) UTILITAIRES GÉNÉRIQUES ------------------------------------
def safe_import(name: str) -> ModuleType | None:
    try:
        return importlib.import_module(name)
    except ModuleNotFoundError:
        print(f"[!] Module absent : {name} – stub activé.")
        return None

def call_if_has(obj, func: str, *args, **kw):
    if obj and hasattr(obj, func):
        try:
            return getattr(obj, func)(*args, **kw)
        except Exception as e:
            print(f"[x] Erreur dans {obj}.{func} : {e}")

# ---------- 2) IMPORTS DYNAMIQUES DES MODULES SACRÉS --------------------
mods = {
    "NeuralFusion":       safe_import("NeuralFusion"),
    "SelfEvolutionEngine":safe_import("SelfEvolutionEngine"),
    "QuantumOptimizer":   safe_import("QuantumOptimizer"),
    "ApocalypseSimulator":safe_import("ApocalypseSimulator"),
    "MetricsUltimate":    safe_import("MONSTERDOG_DECORTIFICUM_REALITY"),
    "MetricsUltimateV2":  safe_import("MONSTERDOG_DECORTIFICUM_REALITY._V2"),
    "TotalitySummit":     safe_import("MONSTERDOG_TOTALITY_SUMMIT"),
}

# ---------- 3) CLASSES FACADE POUR CHAQUE FONCTIONNALITÉ ---------------
class NeuralHub:
    def __init__(self):
        cls = getattr(mods["NeuralFusion"], "NeuralFusion", None)
        self.engine = cls() if cls else None
    def run(self):
        call_if_has(self.engine, "fuse_networks")

class EvolutionHub:
    def __init__(self):
        cls = getattr(mods["SelfEvolutionEngine"], "SelfEvolutionEngine", None)
        self.engine = cls() if cls else None
    def run(self):
        call_if_has(self.engine, "evolve")

class QuantumHub:
    def __init__(self):
        cls = getattr(mods["QuantumOptimizer"], "QuantumOptimizer", None)
        self.engine = cls() if cls else None
    def run(self):
        call_if_has(self.engine, "optimize_server", "SERVER-ALPHA")

class ApocalypseHub:
    def __init__(self):
        cls = getattr(mods["ApocalypseSimulator"], "ApocalypseSimulator", None)
        self.sim  = cls() if cls else None
    def run(self):
        call_if_has(self.sim, "run_simulation")

class MetricsHub:
    def run(self):
        call_if_has(mods["MetricsUltimate"], "run_decortificum_analysis")
        call_if_has(mods["MetricsUltimateV2"], "execute_fractal_scan")
        call_if_has(mods["TotalitySummit"], "run_totality_benchmark")

# ---------- 4) ALERT AUTOMATOR + BENCHMARK HUNTER -----------------------
RESPONSES = [
    "[ALERT] Protocole défensif engagé.",
    "[ZORG-MASTER] Réalignement fractal en cours…",
    "[OMNI🔱AEGIS] Analyse émotionnelle enclenchée.",
    "[MONSTERDOG] Réponse cognitive boostée."
]

def alert_automator(message: str):
    print(choice(RESPONSES), f"\n   » {message}")

def bench_hunter():
    hubs = [NeuralHub(), EvolutionHub(), QuantumHub(), ApocalypseHub(), MetricsHub()]
    results = {}
    for hub in hubs:
        name = hub.__class__.__name__
        t0 = time.perf_counter()
        hub.run()
        results[name] = (time.perf_counter() - t0) * 1000
    print("\n== Benchmark Hunter – latence (ms) ==")
    for k, v in results.items():
        print(f"   {k:<18}: {v:7.2f}")

# ---------- 5) MENU CLI PRINCIPAL ---------------------------------------
ACTIONS = {
    "1": ("Fusion neuronale",  NeuralHub().run),
    "2": ("Auto-évolution",    EvolutionHub().run),
    "3": ("Optimisation quantique", QuantumHub().run),
    "4": ("Simulation apocalypse",  ApocalypseHub().run),
    "5": ("Métriques & scans", MetricsHub().run),
    "6": ("Benchmark Hunter",  bench_hunter),
    "7": ("Alert Automator test", lambda: alert_automator("Intrusion détectée sur le Nexus")),
    "q": ("Quitter",           lambda: sys.exit(0)),
}

def main():
    print("\n♾️  MONSTERDOG ULTIME FINAL – Lancement", datetime.utcnow().isoformat(), "♾️")
    while True:
        print("\n--- Menu ---")
        for k, (label, _) in ACTIONS.items():
            print(f"[{k}] {label}")
        choice_ = input("Choix : ").strip().lower()
        ACTIONS.get(choice_, (None, lambda: print("Choix invalide.")))[1]()

if __name__ == "__main__":
    main()