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: 21,390 Bytes
f7fce63 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 | from typing import Dict, List, Any, Tuple
from bone_core import Prisma
from bone_physics import ChromaScope
class Projector:
def __init__(self):
self.width = 80
@staticmethod
def _extract(physics_obj: Any, field: str, sub_field: str, default: Any = 0.0):
val = None
if hasattr(physics_obj, sub_field):
val = getattr(physics_obj, sub_field)
elif isinstance(physics_obj, dict):
if sub_field in physics_obj:
val = physics_obj[sub_field]
elif field in physics_obj and isinstance(physics_obj[field], dict):
val = physics_obj[field].get(sub_field)
return default if val is None else val
def render(
self,
physics_ctx: Dict,
data_ctx: Dict,
mind_ctx: tuple,
reality_depth: int = 1,
labels: Dict = None,
) -> str:
if not labels:
labels = {"HP": "HP", "STM": "STM"}
physics = physics_ctx.get("physics", {})
status_line = self._render_vital_strip(data_ctx, mind_ctx, labels)
physics_line = ""
if labels.get("SHOW_PHYSICS", True):
physics_line = self._render_physics_strip(
physics, data_ctx.get("vectors", {})
)
ui_depth = data_ctx.get("ui_depth", "IDLE")
vsl_line = self._render_lattice_strip(physics, depth=ui_depth)
zone = self._extract(physics, "space", "zone", "UNKNOWN")
lens = mind_ctx[0] if mind_ctx else "RAW"
depth_map = {0: "TERM", 1: "SIM", 2: "VIL", 3: "DBG", 4: "DEEP"}
depth_label = depth_map.get(reality_depth, "?")
depth_marker = f"{Prisma.VIOLET}[D{reality_depth}:{depth_label}]{Prisma.RST}"
context_line = (
f"{Prisma.GRY} π {zone:<12} ποΈ {lens:<12} {depth_marker}{Prisma.RST}"
)
div = f"{Prisma.GRY}{'β' * self.width}{Prisma.RST}"
mid_lines = []
if physics_line:
mid_lines.append(physics_line)
if vsl_line:
mid_lines.append(" " + vsl_line)
mid_section = "\n".join(mid_lines) if mid_lines else ""
return f"{div}\n{status_line}\n{mid_section}\n{context_line}\n{div}"
def _render_vital_strip(self, data: Dict, mind: tuple, labels: Dict) -> str:
health = data.get("health", 100)
stamina = data.get("stamina", 100)
atp = data.get("bio", {}).get("atp") or 0
dignity = data.get("dignity", 100)
hp_bar = self._mini_bar(health, 100, 6, Prisma.RED)
stm_bar = self._mini_bar(stamina, 100, 6, Prisma.GRN)
dig_color = Prisma.VIOLET if dignity > 50 else Prisma.GRY
dig_icon = "β¦" if dignity > 80 else "β§"
raw_role = mind[2] if mind and len(mind) > 2 else None
role = str(raw_role).upper() if raw_role else "OBSERVER"
role = role.replace("THE THE ", "THE ")
if len(role) > 30:
role = role[:27] + "..."
l_hp = labels.get("HP", "HP")
l_stm = labels.get("STM", "STM")
role_block = f"{Prisma.WHT}β¦ {role}{Prisma.RST}"
return (
f" {role_block:<35} "
f"{l_hp} {hp_bar} "
f"{l_stm} {stm_bar} "
f"{dig_color}{dig_icon}{int(dignity)}%{Prisma.RST} "
f"{Prisma.YEL}ATP:{int(atp)}{Prisma.RST}"
)
def _render_physics_strip(self, physics: Any, vectors: Dict) -> str:
volt = self._extract(physics, "energy", "voltage", 0.0)
drag = self._extract(physics, "space", "narrative_drag", 0.0)
dom_vec = "NEUTRAL"
dom_val = 0.0
if vectors:
dom_vec = max(vectors, key=vectors.get)
dom_val = vectors[dom_vec]
return (
f" {Prisma.CYN}VOLT:{Prisma.RST} {volt:04.1f}v "
f"{Prisma.SLATE}DRAG:{Prisma.RST} {drag:04.1f} "
f"{Prisma.MAG}VEC:{Prisma.RST} {dom_vec} ({dom_val:.2f})"
)
@staticmethod
def _render_lattice_strip(physics: Dict, depth: str = "DEEP") -> str:
if depth == "IDLE" or not physics:
return ""
def _get_val(k1, k2, default_val):
v = physics.get(k1)
if v is None:
v = physics.get(k2)
return default_val if v is None else v
E = _get_val("exhaustion", "E", 0.2)
beta = _get_val("contradiction", "beta", 0.4)
V = _get_val("voltage", "voltage", 30.0)
F = _get_val("friction", "narrative_drag", 0.6)
H = _get_val("health", "health", 100.0)
P = _get_val("stamina", "stamina", 100.0)
T = _get_val("trauma", "T", 0.0)
psi = _get_val("psi", "psi", 0.0)
chi = _get_val("chi", "chi", 0.0)
valence = _get_val("valence", "valence", 0.0)
core = f"{Prisma.CYN}[π§ E:{E:.2f} Ξ²:{beta:.2f} | β‘ V:{V:.0f} F:{F:.1f} | β€οΈ H:{H:.0f} P:{P:.0f} | πΊ T:{T:.0f}]{Prisma.RST}"
deep = (
f"{Prisma.VIOLET} [π Ξ¨:{psi:.2f} Ξ§:{chi:.2f} β₯:{valence:.2f}]{Prisma.RST}"
)
if depth == "DEEP":
return core + deep
elif depth == "CORE":
return core
elif depth == "LITE":
return f"{Prisma.CYN}[β‘ V:{V:.0f} | β€οΈ H:{H:.0f} P:{P:.0f}]{Prisma.RST}"
return ""
def render_technical(self, physics: Dict, data: Dict, mind: tuple) -> str:
v = self._extract(physics, "energy", "voltage", 0.0)
d = self._extract(physics, "space", "narrative_drag", 0.0)
vec = data.get("vectors", {})
vec_str = ", ".join([f"{k}:{v:.2f}" for k, v in vec.items() if v > 0.01])
return (
f"{Prisma.CYN}/// KERNEL TELEMETRY ///{Prisma.RST}\n"
f"PHYSICS : V={v:<6.3f} D={d:<6.3f} | LENS: {mind[0]}\n"
f"VECTORS : [{vec_str}]\n"
f"BIO_DUMP: {str(data.get('bio', {}))[:60]}..."
)
@staticmethod
def _mini_bar(val, max_val, width, color):
if max_val == 0:
return ""
ratio = max(0.0, min(1.0, val / max_val))
fill = int(ratio * width)
empty = width - fill
return f"{color}{'β' * fill}{Prisma.GRY}{'β' * empty}{Prisma.RST}"
class GeodesicRenderer:
def __init__(self, engine_ref, chroma_ref, strunk_ref, valve_ref=None):
self.eng = engine_ref
self.projector = Projector()
self.vsl_chroma = chroma_ref
self.strunk_white = strunk_ref
self.valve = valve_ref
self.soul_dashboard = SoulDashboard(engine_ref)
self.NOISE_PATTERNS = [
"stabilizer:",
"pid_",
"flux",
"phase execution",
"vector collapse",
"manifold",
"orbit:",
"update_coordinates",
"active correction",
"drag reduced",
"voltage spiked",
"live state mirror",
"auto_trace",
"wayfinder",
]
def render_frame(
self, ctx, tick: int, current_events: List[Dict]
) -> Dict[str, Any]:
physics = ctx.physics
bio = ctx.bio_result
raw_dashboard = self.render_dashboard(ctx)
colored_ui = self.vsl_chroma.modulate(raw_dashboard, physics.get("vector", {}))
if self.strunk_white:
clean_ui, style_log = self.strunk_white.sanitize(colored_ui)
if style_log:
self._punish_style_crime(style_log)
else:
clean_ui = colored_ui
if "The system is listening." in clean_ui:
clean_ui = clean_ui.replace("The system is listening.", "")
structured_logs = self.compose_logs(ctx.logs, current_events, tick)
return {
"type": "GEODESIC_FRAME",
"ui": clean_ui,
"logs": structured_logs,
"metrics": self.eng.get_metrics(bio.get("atp", 0.0)),
}
def render_dashboard(self, ctx) -> str:
physics = ctx.physics
mind = ctx.mind_state
mind_tuple = (mind.get("lens"), mind.get("thought"), mind.get("role"))
bio_data = ctx.bio_result or {}
metrics = self.eng.get_metrics()
bio_data["atp"] = metrics.get("atp", 0.0)
data_ctx = {
"health": self.eng.health,
"stamina": self.eng.stamina,
"bio": bio_data,
"dignity": (
getattr(self.eng.soul.anchor, "dignity_reserve", 100.0)
if hasattr(self.eng, "soul")
else 100.0
),
"vectors": physics.get("vector", {}),
}
if hasattr(self.eng, "consultant"):
data_ctx["vsl"] = {
"E": self.eng.consultant.state.E,
"B": self.eng.consultant.state.B,
"L": getattr(self.eng.consultant.state, "L", 0.0),
"O": getattr(self.eng.consultant.state, "O", 1.0),
}
mode = self.eng.config.get("boot_mode", "ADVENTURE").upper()
current_depth = 1
if hasattr(ctx, "reality_stack"):
current_depth = ctx.reality_stack.current_depth
if mode == "TECHNICAL":
return self.projector.render_technical(physics, data_ctx, mind_tuple)
elif mode == "CONVERSATION":
labels = {"HP": "LINK", "STM": "SYNC", "SHOW_PHYSICS": False}
return self.projector.render(
{"physics": physics}, data_ctx, mind_tuple, current_depth, labels
)
elif mode == "CREATIVE":
labels = {"HP": "INT", "STM": "FLOW", "SHOW_PHYSICS": True}
return self.projector.render(
{"physics": physics}, data_ctx, mind_tuple, current_depth, labels
)
else:
labels = {"HP": "HP", "STM": "STM", "SHOW_PHYSICS": False}
return self.projector.render(
{"physics": physics}, data_ctx, mind_tuple, reality_depth=current_depth, labels=labels
)
@staticmethod
def render_soul_strip(soul_ref) -> str:
if not soul_ref:
return ""
if not soul_ref.current_obsession:
return ""
return (
f"{Prisma.GRY}--- Obsession: {soul_ref.current_obsession} ---{Prisma.RST}"
)
def compose_logs(self, logs: list, events: list, _tick: int = 0) -> List[str]:
all_logs = [str(l) for l in logs if l is not None]
for e in events:
if e and e.get("text"):
all_logs.append(e["text"])
if not all_logs:
return []
unique_logs = []
seen = set()
for l in all_logs:
clean_l = Prisma.strip(l).lower()
if any(pattern in clean_l for pattern in self.NOISE_PATTERNS):
continue
if l not in seen:
unique_logs.append(l)
seen.add(l)
structured = []
for log in unique_logs:
if "CRITICAL" in log or "RUPTURE" in log:
structured.append(f"{Prisma.RED}βΊ {log}{Prisma.RST}")
elif "Bio-Alert" in log or "SENSATION" in log:
structured.append(f"{Prisma.CYN}β’ {log}{Prisma.RST}")
elif "TOWN HALL" in log or "VITAL SIGNS" in log:
structured.append(f"{Prisma.CYN}π {log}{Prisma.RST}")
elif "PARADOX" in log:
structured.append(f"{Prisma.MAG}π· {log}{Prisma.RST}")
elif "ITEM:" in log or "GAINED" in log:
structured.append(f"{Prisma.YEL}β
{log}{Prisma.RST}")
else:
structured.append(f"{Prisma.GRY}β’ {log}{Prisma.RST}")
return structured
def _punish_style_crime(self, log_msg):
if hasattr(self.eng, "events"):
self.eng.events.log(log_msg, "SYS")
class CachedRenderer:
def __init__(self, base_renderer):
self._base = base_renderer
self._cache = {"dashboard": {"hash": 0, "content": ""}, "last_tick": -1}
def render_frame(self, ctx, tick: int, events: List[Dict]) -> Dict:
voltage = (
ctx.physics.get("voltage", 0)
if isinstance(ctx.physics, dict)
else ctx.physics.voltage
)
if voltage > 15.0 or tick != self._cache["last_tick"]:
frame = self._base.render_frame(ctx, tick, events)
self._cache["dashboard"]["content"] = frame["ui"]
self._cache["last_tick"] = tick
return frame
return {
"type": "GEODESIC_FRAME",
"ui": self._cache["dashboard"]["content"],
"logs": self._base.compose_logs(ctx.logs, events, tick),
"metrics": ctx.bio_result if hasattr(ctx, "bio_result") else {},
}
def get_renderer(engine_ref, chroma_ref, strunk_ref, valve_ref=None, mode="STANDARD"):
base = GeodesicRenderer(engine_ref, chroma_ref, strunk_ref, valve_ref)
if mode == "PERFORMANCE":
return CachedRenderer(base)
return base
class AmbiguityDial:
BOARDROOM = 0
WORKSHOP = 1
RED_TEAM = 2
PALIMPSEST = 3
class TruthRenderer(GeodesicRenderer):
def __init__(self, engine_ref):
super().__init__(engine_ref, None, None)
self.engine = engine_ref
self.dial_setting = AmbiguityDial.BOARDROOM
def render_truth(self, cortex_packet, council_log, trauma_cost):
ui_text = cortex_packet.get("ui", "")
if self.dial_setting == AmbiguityDial.BOARDROOM:
return f"{Prisma.paint('--- EXECUTIVE SUMMARY ---', 'W')}\n{ui_text}\n"
elif self.dial_setting == AmbiguityDial.WORKSHOP:
metrics = self.engine.get_metrics()
return (
f"{Prisma.paint('--- ENGINEER VIEW ---', 'C')}\n"
f"Confidence: {cortex_packet.get('truth_ratio', 0.95):.2%}\n"
f"System Drag: {metrics['stamina']:.1f}\n"
f"---------------------\n{ui_text}\n"
)
elif self.dial_setting == AmbiguityDial.RED_TEAM:
dissent = [l for l in council_log if "CRITIC" in l or "WARN" in l]
return (
f"{Prisma.paint('--- RED TEAM DASHBOARD ---', 'R')}\n"
f"{Prisma.paint('β οΈ ADVERSARIAL SIMULATION ACTIVE', 'Y')}\n"
f"Cost of Blandness: {trauma_cost:.1f} Trauma Units\n"
f"Active Conflicts:\n" + "\n".join([f" > {d}" for d in dissent]) + "\n"
f"---------------------\n{ui_text}\n"
)
elif self.dial_setting == AmbiguityDial.PALIMPSEST:
drafts = cortex_packet.get("drafts", [])
layer_view = ""
for i, draft in enumerate(drafts):
layer_view += f"{Prisma.GRY}[Draft {i}]: {draft} {Prisma.RED}[REDACTED]{Prisma.RST}\n"
return (
f"{Prisma.paint('--- PALIMPSEST VIEW ---', 'M')}\n"
f"{layer_view}"
f"{Prisma.paint('--- FINAL SURFACE ---', 'W')}\n{ui_text}\n"
)
return None
class PulseReader:
@staticmethod
def derive_mood(bio_state: Dict) -> str:
chem = bio_state.get("chem", {})
if chem.get("COR", 0) > 0.6:
return "Defensive"
if chem.get("DA", 0) > 0.6:
return "Manic"
if chem.get("OXY", 0) > 0.6:
return "Affectionate"
atp = bio_state.get("mito", {}).get("atp", 100)
if atp < 20:
return "Exhausted"
return "Neutral"
@staticmethod
def analyze_voltage(voltage: float) -> Tuple[str, str]:
if voltage > 20.0:
return "CRITICAL", "β‘"
if voltage > 15.0:
return "HIGH", "π₯"
if voltage < 5.0:
return "LOW", "βοΈ"
return "NOMINAL", "π’"
class SoulDashboard:
def __init__(self, engine_ref):
self.eng = engine_ref
def render(self) -> str:
if not hasattr(self.eng, "soul") or not self.eng.soul:
return ""
if not hasattr(self.eng.soul, "anchor"):
return f"{Prisma.GRY}[SOUL DETECTED - ANCHOR LOST]{Prisma.RST}"
anchor = self.eng.soul.anchor
soul = self.eng.soul
dig = anchor.dignity_reserve
if dig > 80:
color = Prisma.GRN
elif dig > 30:
color = Prisma.OCHRE
else:
color = Prisma.RED
filled = int(dig / 5)
bar_str = f"{color}{'β' * filled}{Prisma.GRY}{'β' * (20 - filled)}{Prisma.RST}"
lock_status = ""
if anchor.agency_lock:
lock_status = f" {Prisma.RED}[π AGENCY LOCKED]{Prisma.RST}"
elif dig < 30:
lock_status = f" {Prisma.OCHRE}[β FADING]{Prisma.RST}"
arch = soul.archetype
tenure = soul.archetype_tenure
tenure_color = Prisma.GRY
if tenure > 5:
tenure_color = Prisma.OCHRE
if tenure > 8:
tenure_color = Prisma.RED
arch_display = (
f"{Prisma.CYN}{arch}{Prisma.RST} ({tenure_color}T:{tenure}{Prisma.RST})"
)
pet_icon = " π" if (dig < 50 and not anchor.agency_lock) else ""
muse = soul.current_obsession if soul.current_obsession else "Void"
line1 = f"SOUL: {bar_str} {int(dig)}%{lock_status}{pet_icon}"
line2 = f" DRIVER: {arch_display} MUSE: {Prisma.VIOLET}{muse}{Prisma.RST}"
return f"{line1}\n{line2}"
class CycleReporter:
def __init__(self, engine_ref):
self.eng = engine_ref
self.vsl_chroma = ChromaScope()
self.renderer = None
self.current_mode = None
self.renderers = {}
self.switch_renderer("STANDARD")
def switch_renderer(self, mode: str):
if self.current_mode == mode and self.renderer:
return
if mode in self.renderers:
self.renderer = self.renderers[mode]
self.current_mode = mode
return
strunk_instance = None
if hasattr(self.eng, "village") and isinstance(self.eng.village, dict):
strunk_instance = self.eng.village.get("bureau")
self.renderer = get_renderer(
self.eng,
self.vsl_chroma,
strunk_instance,
getattr(self, "valve", None),
mode=mode,
)
self.renderers[mode] = self.renderer
self.current_mode = mode
def render_snapshot(self, ctx) -> Dict[str, Any]:
try:
if ctx.refusal_triggered and ctx.refusal_packet:
return ctx.refusal_packet
if ctx.is_bureaucratic:
return self._package_bureaucracy(ctx)
self._inject_diagnostics(ctx)
self._inject_flux_readout(ctx)
self._inject_somatic_pulse(ctx)
return self.renderer.render_frame(
ctx, self.eng.tick_count, self.eng.events.flush()
)
except Exception as e:
return {
"type": "CRITICAL_RENDER_FAIL",
"ui": f"{Prisma.RED}RENDERER CRASH: {e}{Prisma.RST}",
"logs": ctx.logs,
"metrics": self.eng.get_metrics(),
}
def _inject_diagnostics(self, ctx):
if hasattr(self.eng, "system_health"):
fb = self.eng.system_health.flush_feedback()
for h in fb["hints"]:
ctx.logs.append(f"{Prisma.CYN}π‘ {h}{Prisma.RST}")
for w in fb["warnings"]:
ctx.logs.append(f"{Prisma.OCHRE}β οΈ {w}{Prisma.RST}")
def _inject_somatic_pulse(self, ctx):
if not hasattr(self.eng, "somatic"):
return
qualia = self.eng.somatic.get_current_qualia(getattr(ctx, "last_impulse", None))
ctx.logs.insert(
0, f"{Prisma.GRY}({qualia.internal_monologue_hint}){Prisma.RST}"
)
ctx.logs.insert(
0,
f"{qualia.color_code}β¦ SENSATION: {qualia.somatic_sensation} [{qualia.tone}]{Prisma.RST}",
)
@staticmethod
def _inject_flux_readout(ctx):
if not ctx.flux_log:
return
significant = []
for e in ctx.flux_log[-5:]:
d = abs(e["delta"])
if d < 1.0 and "PID" in e["reason"]:
continue
icon = "β‘" if e["metric"].upper() == "VOLTAGE" else "β"
color = Prisma.GRN if e["delta"] > 0 else Prisma.RED
arrow = "β²" if e["delta"] > 0 else "βΌ"
significant.append(
f"{Prisma.GRY}[FLUX]{Prisma.RST} {icon} {e['metric'][:3].upper()} {color}{arrow} {d:.1f}{Prisma.RST} ({e['reason']})"
)
if significant:
ctx.logs.insert(0, "")
for line in reversed(significant):
ctx.logs.insert(0, line)
def _package_bureaucracy(self, ctx):
if not self.eng.bureau:
return None
if ctx.is_bureaucratic or ctx.bureau_ui:
base = (
self.renderer.base_renderer
if hasattr(self.renderer, "base_renderer")
else self.renderer
)
bio_res = ctx.bio_result or {}
return {
"type": "BUREAUCRACY",
"ui": ctx.bureau_ui,
"logs": base.compose_logs(
ctx.logs, self.eng.events.flush(), self.eng.tick_count
),
"metrics": self.eng.get_metrics(bio_res.get("atp", 0.0)),
}
return None
|