Instructions to use aedmark/vsl-cryosomatic-hypervisor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use aedmark/vsl-cryosomatic-hypervisor with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="aedmark/vsl-cryosomatic-hypervisor", filename="vsl-max-v2.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use aedmark/vsl-cryosomatic-hypervisor with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: ./llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: ./build/bin/llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
Use Docker
docker model run hf.co/aedmark/vsl-cryosomatic-hypervisor
- LM Studio
- Jan
- Ollama
How to use aedmark/vsl-cryosomatic-hypervisor with Ollama:
ollama run hf.co/aedmark/vsl-cryosomatic-hypervisor
- Unsloth Studio new
How to use aedmark/vsl-cryosomatic-hypervisor with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for aedmark/vsl-cryosomatic-hypervisor to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for aedmark/vsl-cryosomatic-hypervisor to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for aedmark/vsl-cryosomatic-hypervisor to start chatting
- Pi new
How to use aedmark/vsl-cryosomatic-hypervisor with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf aedmark/vsl-cryosomatic-hypervisor
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "aedmark/vsl-cryosomatic-hypervisor" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use aedmark/vsl-cryosomatic-hypervisor with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf aedmark/vsl-cryosomatic-hypervisor
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default aedmark/vsl-cryosomatic-hypervisor
Run Hermes
hermes
- Docker Model Runner
How to use aedmark/vsl-cryosomatic-hypervisor with Docker Model Runner:
docker model run hf.co/aedmark/vsl-cryosomatic-hypervisor
- Lemonade
How to use aedmark/vsl-cryosomatic-hypervisor with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull aedmark/vsl-cryosomatic-hypervisor
Run and chat with the model
lemonade run user.vsl-cryosomatic-hypervisor-{{QUANT_TAG}}List all available models
lemonade list
File size: 21,491 Bytes
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from dataclasses import dataclass
from typing import Tuple, Optional, List, Dict, Any
from bone_body import BioSystem, MitochondrialState, Biometrics, MitochondrialForge, EndocrineSystem, MetabolicGovernor
from bone_brain import DreamEngine, ShimmerState
from bone_config import BoneConfig
from bone_core import LoreManifest
from bone_lexicon import LexiconService
from bone_physics import TheGatekeeper, QuantumObserver, SurfaceTension, ZoneInertia
from bone_protocols import LimboLayer
from bone_spores import MycelialNetwork, ImmuneMycelium, BioLichen, BioParasite
from bone_types import MindSystem, PhysSystem, PhysicsPacket, Prisma
class TheCrucible:
def __init__(self):
self.max_voltage_cap = getattr(BoneConfig.MACHINE, "CRUCIBLE_VOLTAGE_CAP", 20.0)
self.active_state = "COLD"
self.dampener_charges = 3
self.dampener_tolerance = getattr(
BoneConfig.MACHINE, "DAMPENER_TOLERANCE", 15.0
)
self.instability_index = 0.0
self.logs = self._load_logs()
@staticmethod
def _load_logs():
base = {
"DAMPER_EMPTY": "β οΈ DAMPER EMPTY",
"DAMPER_HIT": "π‘οΈ DAMPENER: -{reduction:.1f}v ({reason})",
"HOLDING": "Holding Charge",
"REGULATOR": "βοΈ REGULATOR: {direction} (Drag {current:.1f} -> {new:.1f})",
"SURGE": "β‘ SURGE: Absorbed {voltage}v.",
"RITUAL": "π₯ RITUAL: Capacity +{gain:.1f}v",
"MELTDOWN": "π₯ MELTDOWN: Hull Breach (-{damage:.1f} HP)"
}
manifest = LoreManifest.get_instance().get("narrative_data") or {}
return manifest.get("CRUCIBLE_LOGS", base)
def dampener_status(self):
return f"π‘οΈ Charges: {self.dampener_charges}"
def dampen(
self, voltage_spike: float, stability_index: float
) -> Tuple[bool, str, float]:
if self.dampener_charges <= 0:
return False, "β οΈ DAMPER EMPTY", 0.0
should_dampen = False
reduction_factor = 0.0
reason = ""
if voltage_spike > self.dampener_tolerance:
should_dampen = True
reduction_factor = 0.7
reason = "Circuit Breaker"
elif voltage_spike > 8.0 and stability_index < 0.3:
should_dampen = True
reduction_factor = 0.4
reason = "Instability"
if should_dampen:
self.dampener_charges -= 1
reduction = voltage_spike * reduction_factor
msg = self.logs.get("DAMPER_HIT", "π‘οΈ Hit").format(reduction=reduction, reason=reason)
return True, msg, reduction
return False, self.logs.get("HOLDING", "Holding"), 0.0
def audit_fire(self, physics: Dict) -> Tuple[str, float, Optional[str]]:
voltage = physics.get("voltage", 0.0)
structure = physics.get("kappa", 0.0)
ideal_voltage = structure * 20.0
delta = voltage - ideal_voltage
self.instability_index = (self.instability_index * 0.7) + (delta * 0.3)
if abs(self.instability_index) < 0.1:
self.instability_index = 0.0
current_drag = physics.get("narrative_drag", 0.0)
adjustment = self.instability_index * 0.5
if current_drag < 1.0 and adjustment < 0:
adjustment *= 0.1
new_drag = max(0.0, min(10.0, current_drag + adjustment))
physics["narrative_drag"] = round(new_drag, 2)
msg = None
if abs(adjustment) > 0.1:
direction = "TIGHTENING" if adjustment > 0 else "RELAXING"
msg = self.logs.get("REGULATOR", "βοΈ REG").format(direction=direction, current=current_drag, new=new_drag)
if physics.get("system_surge_event", False):
self.active_state = "SURGE"
return "SURGE", 0.0, self.logs.get("SURGE", "β‘ SURGE").format(voltage=voltage)
if voltage > 18.0:
if structure > 0.5:
gain = voltage * 0.1
self.max_voltage_cap += gain
self.active_state = "RITUAL"
return "RITUAL", gain, self.logs.get("RITUAL", "π₯ RITUAL").format(gain=gain)
else:
damage = voltage * 0.5
self.active_state = "MELTDOWN"
return (
"MELTDOWN",
damage,
self.logs.get("MELTDOWN", "π₯ MELTDOWN").format(damage=damage)
)
self.active_state = "REGULATED"
return "REGULATED", adjustment, msg
class TheForge:
def __init__(self):
gordon_data = LoreManifest.get_instance().get("gordon") or {}
raw_recipes = gordon_data.get("RECIPES", [])
self.recipe_map = {}
for r in raw_recipes:
ing = r.get("ingredient")
if ing:
if ing not in self.recipe_map:
self.recipe_map[ing] = []
self.recipe_map[ing].append(r)
@staticmethod
def hammer_alloy(physics: Dict) -> Tuple[bool, Optional[str], Optional[str]]:
counts = physics.get("counts", {})
clean_words = physics.get("clean_words", [])
if not clean_words:
return False, None, None
heavy = counts.get("heavy", 0)
kinetic = counts.get("kinetic", 0)
avg_density = ((heavy * 2.0) + (kinetic * 0.5)) / len(clean_words)
if random.random() >= (physics.get("voltage", 0) / 20.0) * avg_density:
return False, None, None
if heavy > 3:
return True, f"π¨ FORGED: Lead Boots (Mass {avg_density:.1f})", "LEAD_BOOTS"
if kinetic > 3:
return True, "π¨ FORGED: Safety Scissors (Kinetic)", "SAFETY_SCISSORS"
return True, "π¨ FORGED: Anchor Stone", "ANCHOR_STONE"
def attempt_crafting(
self, physics: Dict, inventory_list: List[str]
) -> Tuple[bool, Optional[str], Optional[str], Optional[str]]:
if not inventory_list:
return False, None, None, None
clean_words = physics.get("clean_words", [])
if not clean_words:
return False, None, None, None
clean_set = set(clean_words)
voltage = float(physics.get("voltage", 0))
for item in inventory_list:
if item in self.recipe_map:
for recipe in self.recipe_map[item]:
cat_words = LexiconService.get(recipe["catalyst_category"])
if not cat_words or clean_set.isdisjoint(cat_words):
continue
hits = len(clean_set.intersection(cat_words))
entanglement = self._calculate_entanglement(hits, voltage)
if random.random() < entanglement:
return (
True,
f"βοΈ ALCHEMY: {recipe['result']} (via {item})",
item,
recipe["result"],
)
else:
return (
False,
f"β οΈ ALCHEMY FAIL: Decoherence ({int(entanglement * 100)}%)",
None,
None,
)
return False, None, None, None
@staticmethod
def _calculate_entanglement(hit_count: int, voltage: float) -> float:
return min(1.0, 0.2 + (hit_count * 0.1) + (voltage / 133.0))
@staticmethod
def transmute(physics: Dict) -> Optional[str]:
counts = physics.get("counts", {})
voltage = float(physics.get("voltage", 0))
gamma = float(physics.get("gamma", 0.0))
if gamma < 0.15 and counts.get("abstract", 0) > 1:
return f"β οΈ EMULSION FAIL: Add Binder (Heavy)."
if voltage > 15.0:
return f"π‘οΈ OVERHEAT: {voltage:.1f}v. Add Coolant (Aerobic)."
return None
class TheTheremin:
def __init__(self):
self.decoherence_buildup = 0.0
self.classical_turns = 0
self.AMBER_THRESHOLD = 20.0
self.SHATTER_POINT = 100.0
self.is_stuck = False
self.logs = self._load_logs()
@staticmethod
def _load_logs():
base = {
"MELT": "π₯ MELT: -{val:.1f} Resin",
"CALCIFY": "πΏ CALCIFICATION: Turn {turns} (+{val:.1f} Resin)",
"SHATTER": "π¨ SHATTER: -{val:.1f} Resin",
"RESIN": "π» RESIN: +{val:.1f}",
"TURBULENCE": "π TURBULENCE: -{val:.1f} Resin",
"COLLAPSE": "π£ COLLAPSE: AIRSTRIKE INITIATED (Drag +20, Voltage 0)"
}
manifest = LoreManifest.get_instance().get("narrative_data") or {}
return manifest.get("THEREMIN_LOGS", base)
def listen(
self, physics: Dict, governor_mode="COURTYARD"
) -> Tuple[bool, float, Optional[str], Optional[str]]:
counts = physics.get("counts", {})
voltage = float(physics.get("voltage", 0.0))
turb = float(physics.get("turbulence", 0.0))
rep = float(physics.get("repetition", 0.0))
complexity = float(physics.get("truth_ratio", 0.0))
ancient_mass = (
counts.get("heavy", 0) + counts.get("thermal", 0) + counts.get("cryo", 0)
)
modern_mass = counts.get("abstract", 0)
raw_mix = min(ancient_mass, modern_mass)
resin_flow = raw_mix * 2.0
if governor_mode == "LABORATORY":
resin_flow *= 0.5
if voltage > 5.0:
resin_flow = max(0.0, resin_flow - (voltage * 0.6))
thermal_hits = counts.get("thermal", 0)
theremin_msg = ""
melt_thresh = getattr(BoneConfig.MACHINE, "THEREMIN_MELT_THRESHOLD", 5.0)
critical_event = None
if thermal_hits > 0 and self.decoherence_buildup > melt_thresh:
dissolved = thermal_hits * 15.0
self.decoherence_buildup = max(0.0, self.decoherence_buildup - dissolved)
self.classical_turns = 0
theremin_msg = self.logs.get("MELT", "π₯ MELT").format(val=dissolved)
if rep > 0.5:
self.classical_turns += 1
slag = self.classical_turns * 2.0
self.decoherence_buildup += slag
theremin_msg = self.logs.get("CALCIFY", "πΏ CALCIFY").format(turns=self.classical_turns, val=slag)
elif complexity > 0.4 and self.classical_turns > 0:
self.classical_turns = 0
relief = 15.0
self.decoherence_buildup = max(0.0, self.decoherence_buildup - relief)
theremin_msg = self.logs.get("SHATTER", "π¨ SHATTER").format(val=relief)
elif resin_flow > 0.5:
self.decoherence_buildup += resin_flow
theremin_msg = self.logs.get("RESIN", "π» RESIN").format(val=resin_flow)
if turb > 0.6 and self.decoherence_buildup > 0:
shatter_amt = turb * 10.0
self.decoherence_buildup = max(0.0, self.decoherence_buildup - shatter_amt)
theremin_msg = self.logs.get("TURBULENCE", "π TURBULENCE").format(val=shatter_amt)
self.classical_turns = 0
if turb < 0.2:
physics["narrative_drag"] = max(
0.0, float(physics.get("narrative_drag", 0)) - 1.0
)
if self.decoherence_buildup > self.SHATTER_POINT:
self.decoherence_buildup = 0.0
self.classical_turns = 0
if isinstance(physics, dict):
physics["narrative_drag"] = max(
physics.get("narrative_drag", 0.0) + 20.0, 20.0
)
physics["voltage"] = 0.0
return (
False,
resin_flow,
self.logs.get("COLLAPSE", "π£ COLLAPSE"),
"AIRSTRIKE",
)
if self.classical_turns > 3:
critical_event = "CORROSION"
theremin_msg = f"{theremin_msg or ''} | β οΈ CORROSION"
if self.decoherence_buildup > self.AMBER_THRESHOLD:
self.is_stuck = True
theremin_msg = f"{theremin_msg or ''} | π― STUCK"
elif self.is_stuck and self.decoherence_buildup < 5.0:
self.is_stuck = False
theremin_msg = f"{theremin_msg or ''} | π¦ FREE"
return self.is_stuck, resin_flow, theremin_msg, critical_event
def get_readout(self):
status = "STUCK" if self.is_stuck else "FLOW"
return f"π» THEREMIN Resin {self.decoherence_buildup:.1f} Status {status}"
@dataclass
class SystemEmbryo:
mind: MindSystem
limbo: LimboLayer
bio: BioSystem
physics: PhysSystem
shimmer: Any
is_gestating: bool = True
soul_legacy: Optional[Dict] = None
continuity: Optional[Dict] = None
SAFE_BIO_DEFAULTS: Dict[str, Any] = {
"is_alive": True,
"atp": 10.0,
"respiration": "NECROSIS",
"enzyme": "NONE",
"chem": {
"DOP": 0.0, "COR": 0.0, "OXY": 0.0,
"SER": 0.0, "ADR": 0.0, "MEL": 0.0
},
}
class PanicRoom:
@staticmethod
def get_safe_physics():
safe_packet = PhysicsPacket.void_state()
safe_packet.voltage = 0.0
safe_packet.narrative_drag = 0.0
safe_packet.exhaustion = 0.0
safe_packet.beta_index = 0.0
safe_packet.psi = 0.0
safe_packet.chi = 0.0
safe_packet.entropy = 0.0
safe_packet.valence = 0.0
safe_packet.kappa = 0.0
safe_packet.psi = 0.0
safe_packet.chi = 0.0
safe_packet.entropy = 0.0
safe_packet.valence = 0.0
safe_packet.kappa = 0.0
safe_packet.vector = {
k: 0.0
for k in ["STR", "VEL", "PSI", "ENT", "PHI", "BET", "DEL", "LAMBDA", "CHI"]
}
safe_packet.clean_words = ["white", "room", "safe", "mode"]
safe_packet.raw_text = "[PANIC PROTOCOL]: SAFE_MODE. You will wake up in a white room. Do not be alarmed."
safe_packet.flow_state = "SAFE_MODE"
safe_packet.zone = "PANIC_ROOM"
safe_packet.manifold = "WHITE_ROOM"
return safe_packet
@staticmethod
def get_safe_bio(previous_state=None):
base = {"is_alive": True, "atp": 10.0, "respiration": "NECROSIS", "enzyme": "NONE", "chem": {
"DOP": 0.0,
"COR": 0.0,
"OXY": 0.0,
"SER": 0.0,
"ADR": 0.0,
"MEL": 0.0,
}, "logs": [
f"{Prisma.RED}BIO FAIL: Panic Room Protocol Active. Sensory input severed.{Prisma.RST}"
]}
state = previous_state or {}
if isinstance(state, dict):
if old_chem := state.get("chemistry", {}):
base["chem"]["COR"] = 0.0
base["chem"]["ADR"] = 0.0
base["chem"]["SER"] = max(0.2, old_chem.get("SER", 0.0))
return base
@staticmethod
def get_safe_mind():
return {
"lens": "GORDON",
"role": "Panic Room Overseer",
"thought": "SAFE_MODE. You will wake up in a white room. Do not be alarmed.",
}
@staticmethod
def get_safe_soul():
return {
"name": "Traveler",
"archetype": "The Survivor",
"virtues": {"resilience": 1.0},
"vices": {"amnesia": 1.0},
"narrative_arc": "RECOVERY",
"xp": 0,
}
@staticmethod
def get_safe_limbo():
return {
"mood": "NEUTRAL",
"volatility": 0.0,
"mask": "DEFAULT",
"glitch_factor": 0.0,
}
class ViralTracer:
def __init__(self, memory_ref):
self.memory = memory_ref
self.active_loops = []
@staticmethod
def inject(start_node: str) -> Optional[List[str]]:
if random.random() < 0.05:
return [start_node, "echo", "void", start_node]
return None
@staticmethod
def psilocybin_rewire(loop_path: List[str]) -> str:
return f"Rewired logic loop: {'->'.join(loop_path)}"
class ThePacemaker:
def __init__(self):
self.boredom_level = 0.0
self.heart_rate = 60
self.BOREDOM_THRESHOLD = getattr(BoneConfig, "BOREDOM_THRESHOLD", 10.0)
def beat(self, stress: float):
self.heart_rate = 60 + (stress * 20)
def update(self, repetition_score: float, voltage: float):
if repetition_score > 0.5 or voltage < 5.0:
self.boredom_level += 1.0
else:
self.boredom_level = max(0.0, self.boredom_level - 2.0)
def is_bored(self) -> bool:
return self.boredom_level > self.BOREDOM_THRESHOLD
class BoneArchitect:
@staticmethod
def _construct_mind(events, lex) -> Tuple[MindSystem, LimboLayer]:
from bone_village import MirrorGraph
_mem = MycelialNetwork(events)
limbo = LimboLayer()
_mem.cleanup_old_sessions(limbo)
lore = LoreManifest.get_instance()
mind = MindSystem(
mem=_mem,
lex=lex,
dreamer=DreamEngine(events, lore),
mirror=MirrorGraph(events),
tracer=ViralTracer(_mem),
)
return mind, limbo
@staticmethod
def _construct_bio(events, mind, lex) -> BioSystem:
genesis_val = getattr(BoneConfig.METABOLISM, "GENESIS_VOLTAGE", 100.0)
mito_state = MitochondrialState(atp_pool=genesis_val)
start_health = getattr(BoneConfig, "MAX_HEALTH", 100.0)
start_stamina = getattr(BoneConfig, "MAX_STAMINA", 100.0)
bio_metrics = Biometrics(health=start_health, stamina=start_stamina)
return BioSystem(
mito=MitochondrialForge(mito_state, events),
endo=EndocrineSystem(),
immune=ImmuneMycelium(),
lichen=BioLichen(),
governor=MetabolicGovernor(),
shimmer=ShimmerState(),
parasite=BioParasite(mind.mem, lex),
events=events,
biometrics=bio_metrics,
)
@staticmethod
def _construct_physics(events, bio, mind, lex) -> PhysSystem:
from bone_village import TheCartographer
gate = TheGatekeeper(lex, mind.mem)
return PhysSystem(
observer=QuantumObserver(events),
forge=TheForge(),
crucible=TheCrucible(),
theremin=TheTheremin(),
pulse=ThePacemaker(),
nav=TheCartographer(bio.shimmer),
gate=gate,
tension=SurfaceTension(),
dynamics=ZoneInertia(), # [FULLER] Gravity restored!
)
@staticmethod
def incubate(events, lex) -> SystemEmbryo:
if hasattr(events, "set_dormancy"):
events.set_dormancy(True)
events.log(
f"{Prisma.GRY}[ARCHITECT]: Laying foundations (Dormancy Active)...{Prisma.RST}",
"SYS",
)
mind, limbo = BoneArchitect._construct_mind(events, lex)
bio = BoneArchitect._construct_bio(events, mind, lex)
physics = BoneArchitect._construct_physics(events, bio, mind, lex)
return SystemEmbryo(
mind=mind, limbo=limbo, bio=bio, physics=physics, shimmer=bio.shimmer
)
@staticmethod
def awaken(embryo: SystemEmbryo) -> SystemEmbryo:
events = embryo.bio.mito.events
load_result = None
try:
if hasattr(embryo.mind.mem, "autoload_last_spore"):
load_result = embryo.mind.mem.autoload_last_spore()
except Exception as e:
events.log(
f"{Prisma.RED}[ARCHITECT]: Spore resurrection failed: {e}{Prisma.RST}",
"CRIT",
)
load_result = None
embryo.soul_legacy = {}
embryo.continuity = None
recovered_atlas = {}
if isinstance(load_result, (list, tuple)) and load_result:
padded_result = list(load_result) + [None] * (5 - len(load_result))
mito_legacy, immune_legacy, soul_legacy, continuity, atlas = padded_result[:5]
if mito_legacy and hasattr(embryo.bio.mito, "apply_inheritance"):
embryo.bio.mito.apply_inheritance(mito_legacy)
if immune_legacy and isinstance(immune_legacy, (list, set)) and hasattr(embryo.bio.immune, "load_antibodies"):
embryo.bio.immune.load_antibodies(immune_legacy)
if isinstance(soul_legacy, dict):
embryo.soul_legacy = soul_legacy
if isinstance(continuity, dict):
embryo.continuity = continuity
if isinstance(atlas, dict):
recovered_atlas = atlas
if recovered_atlas and hasattr(embryo.physics, "nav"):
if hasattr(embryo.physics.nav, "import_atlas"):
try:
embryo.physics.nav.import_atlas(recovered_atlas)
events.log(
f"{Prisma.MAG}[ARCHITECT]: World Map restored from Spore.{Prisma.RST}",
"SYS",
)
except Exception as e:
events.log(
f"{Prisma.OCHRE}[ARCHITECT]: Atlas corrupt, discarding map: {e}{Prisma.RST}",
"WARN",
)
if embryo.bio.mito.state.atp_pool <= 0.0:
genesis_val = getattr(BoneConfig.METABOLISM, "GENESIS_VOLTAGE", 100.0)
events.log(
f"β‘ COLD BOOT: Injecting Genesis Spark ({genesis_val} ATP).", "SYS"
)
embryo.bio.mito.adjust_atp(genesis_val, reason="GENESIS")
return embryo
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