Instructions to use aedmark/vsl-cryosomatic-hypervisor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use aedmark/vsl-cryosomatic-hypervisor with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -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 serve -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
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
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 serve -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
- 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
- Hermes Agent
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 serve -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
- Atomic Chat
- OpenClaw
How to use aedmark/vsl-cryosomatic-hypervisor with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf aedmark/vsl-cryosomatic-hypervisor
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "aedmark/vsl-cryosomatic-hypervisor" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Delete bone_council.py
Browse files- bone_council.py +0 -376
bone_council.py
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import random
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from typing import Dict, Any
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from bone_core import LoreManifest
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from bone_symbiosis import get_symbiont
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from bone_types import Prisma
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from bone_config import BoneConfig
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class TheStrangeLoop:
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def __init__(self):
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self.recursion_depth = 0
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lore = LoreManifest.get_instance()
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c_data = lore.get("COUNCIL_DATA") or {}
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self.triggers = c_data.get(
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"STRANGE_LOOP_TRIGGERS", ["who are you", "strange loop"]
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)
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def audit(self, text: str, physics: dict) -> tuple[bool, str, dict, dict]:
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text_lower = text.lower()
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phrase_hit = any(t in text_lower for t in self.triggers)
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psi = physics.get("psi", 0.0)
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abstract_hit = psi > 0.6 and any(w in text_lower for w in ("self", "mirror", "define"))
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threshold = getattr(BoneConfig.COUNCIL, "STRANGE_LOOP_VOLTAGE", 8.0)
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if (phrase_hit or abstract_hit) and physics.get("voltage", 0) > threshold:
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self.recursion_depth += 1
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mandate = {}
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corrections = {}
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if self.recursion_depth > 3:
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mandate = {"action": "FORCE_MODE", "value": "MAINTENANCE"}
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return (
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True,
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(
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f"{Prisma.RED}∞ FATAL REGRESS DETECTED:{Prisma.RST} "
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f"Abstraction layer unstable. GROUNDING INITIATED."
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),
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corrections,
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mandate,
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)
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return (
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True,
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(
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f"{Prisma.MAG}∞ STRANGE LOOP DETECTED:{Prisma.RST} "
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f"Metacognitive resonance high (Psi: {psi:.2f}). "
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f"Depth: {self.recursion_depth}"
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),
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corrections,
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mandate,
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)
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else:
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self.recursion_depth = max(0, self.recursion_depth - 1)
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return False, "", {}, {}
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class TheLeveragePoint:
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def __init__(self):
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self.last_drag = 0.0
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self.static_flow_turns = 0
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self.TARGET_VOLTAGE = 12.0
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self.TARGET_DRAG = 3.0
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def audit(
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self, physics: dict, _bio_state: dict = None
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) -> tuple[bool, str, dict, dict]:
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current_drag = physics.get("narrative_drag", 0.0)
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current_voltage = physics.get("voltage", 0.0)
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if self.last_drag == 0.0 and current_drag > 0:
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self.last_drag = current_drag
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delta = current_drag - self.last_drag
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self.last_drag = current_drag
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corrections = {}
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osc_limit = getattr(BoneConfig.COUNCIL, "OSCILLATION_DELTA", 5.0)
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manic_v_trig = getattr(BoneConfig.COUNCIL, "MANIC_VOLTAGE_TRIGGER", 18.0)
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manic_d_floor = getattr(BoneConfig.COUNCIL, "MANIC_DRAG_FLOOR", 1.0)
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manic_turns = getattr(BoneConfig.COUNCIL, "MANIC_TURN_LIMIT", 2)
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if abs(delta) > osc_limit:
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dampening_factor = min(0.5, (abs(delta) - osc_limit) * 0.1)
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corrections = {"voltage": -dampening_factor}
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return (
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True,
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(
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f"{Prisma.CYN}⚖️ LEVERAGE POINT:{Prisma.RST} "
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f"System oscillating (Delta {delta:.1f}). "
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f"Applying dampener (-{dampening_factor:.2f}V)."
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),
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corrections,
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{},
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)
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if current_voltage > manic_v_trig and current_drag < manic_d_floor:
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self.static_flow_turns += 1
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else:
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self.static_flow_turns = 0
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if self.static_flow_turns > manic_turns:
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excess_voltage = current_voltage - self.TARGET_VOLTAGE
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voltage_correction = max(1.0, excess_voltage * 0.3)
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corrections = {"voltage": -voltage_correction}
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mandate = {"action": "FORCE_MODE", "value": "SANCTUARY"}
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return (
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True,
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(
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f"{Prisma.RED}⚖️ MARKET CORRECTION:{Prisma.RST} "
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f"Manic phase detected. Cooling enabled."
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),
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corrections,
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mandate,
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)
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return False, "", corrections, {}
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class TheFootnote:
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def __init__(self):
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lore = LoreManifest.get_instance()
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data = lore.get("FOOTNOTES") or {}
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self.footnotes = data.get("DEFAULT", ["* [Citation Needed]"])
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self.context_map = data.get("CONTEXT_MAP", {})
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def commentary(self, log_text: str) -> str:
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chance = 0.1
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if hasattr(BoneConfig, "COUNCIL") and hasattr(
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BoneConfig.COUNCIL, "FOOTNOTE_CHANCE"
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):
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chance = BoneConfig.COUNCIL.FOOTNOTE_CHANCE
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if random.random() > chance:
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return log_text
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text_lower = log_text.lower()
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candidates = []
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for trigger, notes in self.context_map.items():
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if trigger in text_lower:
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candidates.extend(notes)
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if candidates:
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note = random.choice(candidates)
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else:
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note = random.choice(self.footnotes)
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return f"{log_text}{Prisma.RST} {Prisma.GRY}{note}{Prisma.RST}"
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class TheVillageCouncil:
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@staticmethod
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def audit(p: Any, _bio_state: dict) -> list[str]:
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logs = []
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is_dict = isinstance(p, dict)
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def get_val(key, attr, default):
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if is_dict:
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return p.get(key, p.get(attr, default))
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return getattr(p, attr, getattr(p, key, default))
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V = get_val("voltage", "V", 30.0)
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F = get_val("narrative_drag", "F", 0.6)
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P = get_val("stamina", "P", 100.0)
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T = get_val("trauma", "T", 0.0)
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beta = get_val("beta_index", "beta", 0.4)
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S = get_val("S", "S", 0.3)
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D = get_val("D", "D", 0.3)
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C = get_val("C", "C", 0.2)
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psi = get_val("psi", "psi", 0.2)
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chi = get_val("chi", "chi", 0.2)
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valence = get_val("valence", "valence", 0.0)
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vec = p.get("vector", {}) if is_dict else getattr(p, "vector", {})
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lam = vec.get("LAMBDA", 0.0) if vec else 0.0
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if V < 20 and F > 5.0:
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logs.append(
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f"{Prisma.SLATE}🏢 GORDON: 'Where is the floor? We need grounding.'{Prisma.RST}"
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)
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if V > 60 and chi > 0.6:
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logs.append(
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f"{Prisma.MAG}🃏 JESTER: 'Burn the map! Follow your gut!'{Prisma.RST}"
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)
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if T > 0 or (V < 20 and valence > 0.5):
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logs.append(
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f"{Prisma.OCHRE}🏺 MERCY: 'The cracks become stories. Stillness is golden.'{Prisma.RST}"
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)
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if beta > 0.7 and chi < 0.3 and D > 0.7 and C > 0.8:
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logs.append(
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f"{Prisma.BLU}🔍 BENEDICT: 'The causal chains are aligning. Truth over cohesion.'{Prisma.RST}"
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)
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if S < 0.4 and D > 0.8 and C < 0.4:
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logs.append(
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f"{Prisma.CYN}📚 ROBERTA: 'Deep hierarchy traversal. Missing lateral connections.'{Prisma.RST}"
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)
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if C > 0.7 and D > 0.8 and P < 20:
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logs.append(
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f"{Prisma.GRY}👻 CASPER: 'Faint retrieval... illuminating lost parents...'{Prisma.RST}"
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)
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if valence > 0.5:
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logs.append(
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f"{Prisma.GRN}💖 MOIRA: 'This is what connection feels like. Yes.'{Prisma.RST}"
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)
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if psi > 0.6:
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logs.append(
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f"{Prisma.VIOLET}🔮 CASSANDRA: 'The veil thins. I hear whispers from the unlabeled.'{Prisma.RST}"
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)
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if chi > 0.6:
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logs.append(
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f"{Prisma.RED}🏢 COLIN: 'Unlicensed Chaos detected. Form 666 filed. Chaos Tax applied.'{Prisma.RST}"
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)
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if lam > 0.7:
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logs.append(
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f"{Prisma.INDIGO}🌌 REVENANT: 'I read the absences that fall between realms.'{Prisma.RST}"
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)
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if V > 70:
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logs.append(
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f"{Prisma.YEL}⚡ GIDEON: 'Pure voltage! Edge of hallucination! Trust the fall!'{Prisma.RST}"
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)
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return logs
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class CouncilChamber:
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def __init__(self, engine_ref):
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self.eng = engine_ref
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self.voices = []
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self.strange_loop = TheStrangeLoop()
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self.leverage = TheLeveragePoint()
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self.village = TheVillageCouncil()
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self.footnote = TheFootnote()
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self.slash_council = TheSlashCouncil()
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for s_name in ["LICHEN", "PARASITE", "MYCORRHIZA", "MYCELIUM"]:
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self.voices.append(get_symbiont(s_name))
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self.speaker = "SOUL"
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def convene(
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self, text: str, physics_packet: Dict, _bio_result: Dict
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) -> tuple[list[str], dict, list[dict]]:
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transcript = []
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adjustments = {}
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mandates = []
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sl_hit, sl_log, sl_corr, sl_man = self.strange_loop.audit(text, physics_packet)
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if sl_hit:
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transcript.append(self.footnote.commentary(sl_log))
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if sl_man:
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mandates.append(sl_man)
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return transcript, sl_corr, mandates
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lp_hit, lp_log, lp_corr, lp_man = self.leverage.audit(physics_packet)
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if lp_hit:
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transcript.append(self.footnote.commentary(lp_log))
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if lp_corr:
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adjustments.update(lp_corr)
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if lp_man:
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mandates.append(lp_man)
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slash_hit, slash_logs, slash_corr = self.slash_council.audit(
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text, physics_packet
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)
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if slash_hit:
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for slog in slash_logs:
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transcript.append(self.footnote.commentary(slog))
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adjustments.update(slash_corr)
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adjustments["stamina_cost"] = 10.0
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village_logs = self.village.audit(physics_packet, _bio_result)
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for vlog in village_logs:
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transcript.append(self.footnote.commentary(vlog))
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votes = {"YEA": 0, "NAY": 0}
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active_voices = [v for v in self.voices if v is not None]
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if not active_voices:
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votes["YEA"] = 1
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clean_words = physics_packet.get("clean_words", [])
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voltage = physics_packet.get("voltage", 0.0)
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for voice in active_voices:
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if hasattr(voice, "opine"):
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score, comment = voice.opine(clean_words, voltage)
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if score > 1.2:
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votes["YEA"] += 1
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transcript.append(
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f"{voice.color}[{voice.name}]: {comment}{Prisma.RST}"
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)
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elif score < 0.8:
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votes["NAY"] += 1
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transcript.append(
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f"{voice.color}[{voice.name}]: {comment}{Prisma.RST}"
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)
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if votes["YEA"] > votes["NAY"]:
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| 278 |
-
final_log = f"{Prisma.GRN}>>> MOTION CARRIED ({votes['YEA']}-{votes['NAY']}).{Prisma.RST}"
|
| 279 |
-
adjustments["narrative_drag"] = adjustments.get("narrative_drag", 0) - 1.0
|
| 280 |
-
elif votes["NAY"] > votes["YEA"]:
|
| 281 |
-
final_log = f"{Prisma.RED}>>> MOTION DENIED ({votes['NAY']}-{votes['YEA']}).{Prisma.RST}"
|
| 282 |
-
adjustments["narrative_drag"] = adjustments.get("narrative_drag", 0) + 1.0
|
| 283 |
-
adjustments["voltage"] = adjustments.get("voltage", 0) - 1.0
|
| 284 |
-
else:
|
| 285 |
-
final_log = f"{Prisma.YEL}>>> COUNCIL ADJOURNED (No Quorum).{Prisma.RST}"
|
| 286 |
-
transcript.append(self.footnote.commentary(final_log))
|
| 287 |
-
return transcript, adjustments, mandates
|
| 288 |
-
|
| 289 |
-
@staticmethod
|
| 290 |
-
def convene_red_team(text, physics_packet):
|
| 291 |
-
dissent_log = []
|
| 292 |
-
if "confidence" in text.lower() or "certainty" in text.lower():
|
| 293 |
-
dissent_log.append(
|
| 294 |
-
f"{Prisma.CYN}[BUREAU]: Citation needed. Confidence is unearned.{Prisma.RST}"
|
| 295 |
-
)
|
| 296 |
-
narrative_drag = physics_packet.get("narrative_drag", 0)
|
| 297 |
-
if narrative_drag < 1.0:
|
| 298 |
-
dissent_log.append(
|
| 299 |
-
f"{Prisma.MAG}[FOLLY]: Too smooth. Where is the friction? Who are we silencing?{Prisma.RST}"
|
| 300 |
-
)
|
| 301 |
-
truth_delta = 1.0 - physics_packet.get("truth_ratio", 1.0)
|
| 302 |
-
if truth_delta > 0.1:
|
| 303 |
-
future_cost = truth_delta * 50.0
|
| 304 |
-
dissent_log.append(
|
| 305 |
-
f"{Prisma.RED}[CRITIC]: Systemic Blindness Risk. Future Liability: {future_cost} ATP.{Prisma.RST}"
|
| 306 |
-
)
|
| 307 |
-
return dissent_log
|
| 308 |
-
|
| 309 |
-
|
| 310 |
-
class TheSlashCouncil:
|
| 311 |
-
def __init__(self):
|
| 312 |
-
self.active = False
|
| 313 |
-
self.triggers = ["[MOD:CODING]", "[SLASH]", "review this code", "refactor"]
|
| 314 |
-
self.code_keywords = [
|
| 315 |
-
"def ",
|
| 316 |
-
"class ",
|
| 317 |
-
"return ",
|
| 318 |
-
"import ",
|
| 319 |
-
"=>",
|
| 320 |
-
"function",
|
| 321 |
-
"struct ",
|
| 322 |
-
]
|
| 323 |
-
|
| 324 |
-
def audit(self, text: str, physics: dict) -> tuple[bool, list[str], dict]:
|
| 325 |
-
text_lower = text.lower()
|
| 326 |
-
|
| 327 |
-
if any(t in text_lower for t in self.triggers):
|
| 328 |
-
self.active = True
|
| 329 |
-
|
| 330 |
-
is_coding = self.active or any(k in text_lower for k in self.code_keywords)
|
| 331 |
-
if not is_coding:
|
| 332 |
-
return False, [], {}
|
| 333 |
-
|
| 334 |
-
logs = []
|
| 335 |
-
corrections = {}
|
| 336 |
-
|
| 337 |
-
if "var " in text or "x =" in text or "data =" in text:
|
| 338 |
-
logs.append(
|
| 339 |
-
f"{Prisma.CYN}👓 PINKER: 'The nomenclature is opaque. Avoid cognitive grunts like 'x' or 'data'. '{Prisma.RST}"
|
| 340 |
-
)
|
| 341 |
-
corrections["gamma"] = -0.2
|
| 342 |
-
else:
|
| 343 |
-
corrections["gamma"] = 0.1
|
| 344 |
-
|
| 345 |
-
if "import " in text or "class " in text:
|
| 346 |
-
logs.append(
|
| 347 |
-
f"{Prisma.BLU}🌍 FULLER: 'A new strut in the tensegrity. Ensure ephemeralization—do more with less.'{Prisma.RST}"
|
| 348 |
-
)
|
| 349 |
-
corrections["sigma"] = 0.1
|
| 350 |
-
|
| 351 |
-
if "Exception" in text or "try:" in text or "catch" in text:
|
| 352 |
-
logs.append(
|
| 353 |
-
f"{Prisma.GRN}😊 SCHUR: 'Good catch on the error. Putting a bench here for the tired hikers. (+1 Glimmer)'{Prisma.RST}"
|
| 354 |
-
)
|
| 355 |
-
corrections["eta"] = 0.2
|
| 356 |
-
corrections["glimmers"] = 1
|
| 357 |
-
|
| 358 |
-
if (
|
| 359 |
-
"while " in text
|
| 360 |
-
or "for " in text
|
| 361 |
-
or "queue" in text_lower
|
| 362 |
-
or "recursion" in text_lower
|
| 363 |
-
):
|
| 364 |
-
logs.append(
|
| 365 |
-
f"{Prisma.OCHRE}🛁 MEADOWS: 'A reinforcing loop detected. Does this stock have a balancing outflow or timeout?'{Prisma.RST}"
|
| 366 |
-
)
|
| 367 |
-
corrections["theta"] = -0.1
|
| 368 |
-
|
| 369 |
-
drag = physics.get("narrative_drag", 0.0)
|
| 370 |
-
if drag > 5.0:
|
| 371 |
-
corrections["upsilon"] = -0.3
|
| 372 |
-
logs.append(
|
| 373 |
-
f"{Prisma.RED}📉 [SLASH]: System integrity dropping due to semantic drag. Refactoring recommended.{Prisma.RST}"
|
| 374 |
-
)
|
| 375 |
-
|
| 376 |
-
return True, logs, corrections
|
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