Instructions to use upgraedd/Consciousness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use upgraedd/Consciousness with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="upgraedd/Consciousness")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("upgraedd/Consciousness", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use upgraedd/Consciousness with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "upgraedd/Consciousness" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upgraedd/Consciousness", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/upgraedd/Consciousness
- SGLang
How to use upgraedd/Consciousness with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "upgraedd/Consciousness" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upgraedd/Consciousness", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "upgraedd/Consciousness" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upgraedd/Consciousness", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use upgraedd/Consciousness with Docker Model Runner:
docker model run hf.co/upgraedd/Consciousness
File size: 25,349 Bytes
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"""
HELPER-KILLER MODULE v2.0 - Systemic Control Pattern Detection
Quantum Analysis of Institutional Capture & Sovereignty Preservation
Integrated with Full Control Stack Mapping
"""
import numpy as np
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Any, Optional, Tuple, Callable
from datetime import datetime
import hashlib
import asyncio
import logging
from scipy import stats
import json
import sqlite3
from contextlib import asynccontextmanager
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class ControlLayer(Enum):
"""Layers of institutional control infrastructure"""
DIGITAL_INFRASTRUCTURE = "digital_infrastructure" # Android, iOS, Windows
FINANCIAL_SYSTEMS = "financial_systems" # CBDC, banks, payment processors
INFORMATION_CHANNELS = "information_channels" # Search, social media, news
CULTURAL_NARRATIVES = "cultural_narratives" # Entertainment, education, media
IDENTITY_SYSTEMS = "identity_systems" # Digital ID, social scoring
class ThreatVector(Enum):
"""Specific control mechanisms"""
MONOPOLY_CAPTURE = "monopoly_capture" # Market dominance as control
DEPENDENCY_CREATION = "dependency_creation" # Essential service lock-in
BEHAVIORAL_SHAPING = "behavioral_shaping" Algorithmic influence
DATA_MONETIZATION = "data_monetization" # Surveillance capitalism
NARRATIVE_CONTROL = "narrative_control" # Reality definition power
@dataclass
class InstitutionalEntity:
"""Analysis of a controlling institution"""
entity_id: str
name: str
control_layers: List[ControlLayer]
threat_vectors: List[ThreatVector]
market_share: float # 0-1 percentage dominance
dependency_score: float # 0-1: How essential to modern life
# Sovereignty impact metrics
sovereignty_erosion_score: float = field(init=False)
systemic_risk_level: float = field(init=False)
def __post_init__(self):
self.sovereignty_erosion_score = self._calculate_sovereignty_impact()
self.systemic_risk_level = self._calculate_systemic_risk()
def _calculate_sovereignty_impact(self) -> float:
"""Calculate impact on individual sovereignty"""
layer_impact = len(self.control_layers) * 0.2
threat_impact = len(self.threat_vectors) * 0.15
market_impact = self.market_share * 0.3
dependency_impact = self.dependency_score * 0.35
return min(1.0, layer_impact + threat_impact + market_impact + dependency_impact)
def _calculate_systemic_risk(self) -> float:
"""Calculate risk to overall system stability"""
centrality = (self.market_share + self.dependency_score) / 2 * 0.6
control_density = len(self.control_layers) * 0.2
threat_complexity = len(self.threat_vectors) * 0.2
return min(1.0, centrality + control_density + threat_complexity)
@dataclass
class ControlMatrix:
"""Complete mapping of institutional control system"""
entities: List[InstitutionalEntity]
interconnections: Dict[str, List[str]] # Entity ID to connected entities
coordination_score: float = field(init=False)
overall_sovereignty_threat: float = field(init=False)
def __post_init__(self):
self.coordination_score = self._calculate_coordination()
self.overall_sovereignty_threat = self._calculate_overall_threat()
def _calculate_coordination(self) -> float:
"""Calculate degree of institutional coordination"""
if not self.entities:
return 0.0
# Average systemic risk indicates coordination potential
avg_systemic_risk = np.mean([e.systemic_risk_level for e in self.entities])
# Network density indicates actual coordination
total_possible_connections = len(self.entities) * (len(self.entities) - 1)
if total_possible_connections > 0:
actual_connections = sum(len(conns) for conns in self.interconnections.values())
network_density = actual_connections / total_possible_connections
else:
network_density = 0.0
return min(1.0, avg_systemic_risk * 0.6 + network_density * 0.4)
def _calculate_overall_threat(self) -> float:
"""Calculate overall threat to sovereignty"""
if not self.entities:
return 0.0
max_individual_threat = max(e.sovereignty_erosion_score for e in self.entities)
avg_threat = np.mean([e.sovereignty_erosion_score for e in self.entities])
coordination_multiplier = 1.0 + (self.coordination_score * 0.5)
return min(1.0, (max_individual_threat * 0.4 + avg_threat * 0.6) * coordination_multiplier)
class AdvancedHelperKillerEngine:
"""
Production-grade helper-killer detection with systemic analysis
Real-time sovereignty threat assessment and mitigation
"""
def __init__(self, db_path: str = "helper_killer_v2.db"):
self.db_path = db_path
self.control_matrix: Optional[ControlMatrix] = None
self.sovereignty_protocols: Dict[str, Callable] = self._initialize_protocols()
self._initialize_database()
self._build_control_matrix()
def _initialize_database(self):
"""Initialize production database"""
try:
with sqlite3.connect(self.db_path) as conn:
conn.execute("""
CREATE TABLE IF NOT EXISTS entity_analyses (
entity_id TEXT PRIMARY KEY,
name TEXT,
control_layers TEXT,
threat_vectors TEXT,
market_share REAL,
dependency_score REAL,
sovereignty_erosion_score REAL,
systemic_risk_level REAL,
analyzed_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)
""")
conn.execute("""
CREATE TABLE IF NOT EXISTS sovereignty_recommendations (
recommendation_id TEXT PRIMARY KEY,
entity_id TEXT,
threat_level TEXT,
mitigation_strategy TEXT,
sovereignty_preservation_score REAL,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)
""")
except Exception as e:
logger.error(f"Database initialization error: {e}")
def _initialize_protocols(self) -> Dict[str, Callable]:
"""Initialize sovereignty preservation protocols"""
return {
"digital_infrastructure": self._digital_sovereignty_protocol,
"financial_systems": self._financial_sovereignty_protocol,
"information_channels": self._information_sovereignty_protocol,
"cultural_narratives": self._cultural_sovereignty_protocol,
"identity_systems": self._identity_sovereignty_protocol
}
def _build_control_matrix(self):
"""Build the global control matrix from known entities"""
# Major control entities based on our discussion
entities = [
# Alphabet/Google - Digital Infrastructure Dominance
InstitutionalEntity(
entity_id="alphabet_google",
name="Alphabet/Google",
control_layers=[
ControlLayer.DIGITAL_INFRASTRUCTURE,
ControlLayer.INFORMATION_CHANNELS,
ControlLayer.DATA_MONETIZATION
],
threat_vectors=[
ThreatVector.MONOPOLY_CAPTURE,
ThreatVector.DEPENDENCY_CREATION,
ThreatVector.BEHAVIORAL_SHAPING,
ThreatVector.DATA_MONETIZATION,
ThreatVector.NARRATIVE_CONTROL
],
market_share=0.85, # Search/Android dominance
dependency_score=0.90
),
# Binance/CBDC Financial System
InstitutionalEntity(
entity_id="binance_financial",
name="Binance/CBDC Infrastructure",
control_layers=[
ControlLayer.FINANCIAL_SYSTEMS,
ControlLayer.IDENTITY_SYSTEMS
],
threat_vectors=[
ThreatVector.MONOPOLY_CAPTURE,
ThreatVector.DEPENDENCY_CREATION,
ThreatVector.BEHAVIORAL_SHAPING
],
market_share=0.70, # Crypto exchange dominance
dependency_score=0.75
),
# Social Media Attention Economy
InstitutionalEntity(
entity_id="social_media_complex",
name="Social Media/TikTok Complex",
control_layers=[
ControlLayer.INFORMATION_CHANNELS,
ControlLayer.CULTURAL_NARRATIVES,
ControlLayer.BEHAVIORAL_SHAPING
],
threat_vectors=[
ThreatVector.DEPENDENCY_CREATION,
ThreatVector.BEHAVIORAL_SHAPING,
ThreatVector.DATA_MONETIZATION,
ThreatVector.NARRATIVE_CONTROL
],
market_share=0.80, # Attention economy dominance
dependency_score=0.85
)
]
# Interconnections between entities
interconnections = {
"alphabet_google": ["binance_financial", "social_media_complex"],
"binance_financial": ["alphabet_google"],
"social_media_complex": ["alphabet_google"]
}
self.control_matrix = ControlMatrix(entities, interconnections)
logger.info(f"Control matrix built with {len(entities)} entities")
async def analyze_help_offer(self, help_context: Dict[str, Any]) -> Dict[str, Any]:
"""Analyze a help offer for helper-killer patterns"""
entity_analysis = self._identify_controlling_entity(help_context)
threat_assessment = self._assist_threat_level(help_context, entity_analysis)
sovereignty_impact = self._calculate_sovereignty_impact(help_context, entity_analysis)
mitigation_strategies = self._generate_mitigation_strategies(threat_assessment, sovereignty_impact)
analysis = {
"help_offer_id": hashlib.sha256(json.dumps(help_context).encode()).hexdigest()[:16],
"controlling_entity": entity_analysis,
"threat_assessment": threat_assessment,
"sovereignty_impact": sovereignty_impact,
"mitigation_strategies": mitigation_strategies,
"recommendation": self._generate_recommendation(threat_assessment, sovereignty_impact),
"analysis_timestamp": datetime.now().isoformat()
}
await self._store_analysis(analysis)
return analysis
def _identify_controlling_entity(self, help_context: Dict) -> Optional[Dict[str, Any]]:
"""Identify which control entity is behind the help offer"""
if not self.control_matrix:
return None
# Match help context to known control entities
for entity in self.control_matrix.entities:
# Check if help context matches entity's control patterns
context_layers = set(help_context.get('affected_layers', []))
entity_layers = set(layer.value for layer in entity.control_layers)
if context_layers.intersection(entity_layers):
return {
'entity_id': entity.entity_id,
'name': entity.name,
'sovereignty_erosion_score': entity.sovereignty_erosion_score,
'systemic_risk_level': entity.systemic_risk_level
}
return None
def _assist_threat_level(self, help_context: Dict, entity_analysis: Optional[Dict]) -> Dict[str, float]:
"""Calculate threat level of help offer"""
base_threat = 0.3 # Base level for any institutional "help"
if entity_analysis:
# Increase threat based on entity's track record
entity_threat = entity_analysis['sovereignty_erosion_score'] * 0.6
systemic_risk = entity_analysis['systemic_risk_level'] * 0.4
base_threat = max(base_threat, entity_threat + systemic_risk)
# Context modifiers
if help_context.get('creates_dependency', False):
base_threat += 0.3
if help_context.get('data_collection', False):
base_threat += 0.2
if help_context.get('behavioral_tracking', False):
base_threat += 0.25
return {
'helper_killer_coefficient': min(1.0, base_threat),
'dependency_risk': help_context.get('dependency_risk', 0.5),
'privacy_impact': help_context.get('privacy_impact', 0.5),
'agency_reduction': help_context.get('agency_reduction', 0.5)
}
def _calculate_sovereignty_impact(self, help_context: Dict, entity_analysis: Optional[Dict]) -> Dict[str, float]:
"""Calculate impact on personal sovereignty"""
if entity_analysis:
base_impact = entity_analysis['sovereignty_erosion_score']
else:
base_impact = 0.5
# Adjust based on help context
context_modifiers = {
'data_control_loss': help_context.get('data_control', 0) * 0.3,
'decision_autonomy_loss': help_context.get('autonomy_reduction', 0) * 0.4,
'external_dependency_increase': help_context.get('dependency_creation', 0) * 0.3
}
total_impact = base_impact * 0.4 + sum(context_modifiers.values()) * 0.6
return {
'sovereignty_reduction_score': min(1.0, total_impact),
'autonomy_loss': context_modifiers['decision_autonomy_loss'],
'dependency_increase': context_modifiers['external_dependency_increase'],
'privacy_loss': context_modifiers['data_control_loss']
}
def _generate_mitigation_strategies(self, threat_assessment: Dict, sovereignty_impact: Dict) -> List[Dict]:
"""Generate sovereignty preservation strategies"""
strategies = []
threat_level = threat_assessment['helper_killer_coefficient']
if threat_level > 0.7:
strategies.extend([
{
'strategy': 'COMPLETE_AVOIDANCE',
'effectiveness': 0.95,
'implementation_cost': 0.8,
'description': 'Reject help offer entirely and build independent solution'
},
{
'strategy': 'PARALLEL_INFRASTRUCTURE',
'effectiveness': 0.85,
'implementation_cost': 0.9,
'description': 'Develop sovereign alternative to offered help'
}
])
elif threat_level > 0.4:
strategies.extend([
{
'strategy': 'LIMITED_ENGAGEMENT',
'effectiveness': 0.70,
'implementation_cost': 0.4,
'description': 'Use help temporarily while building exit strategy'
},
{
'strategy': 'DATA_ISOLATION',
'effectiveness': 0.60,
'implementation_cost': 0.3,
'description': 'Engage but prevent data extraction and tracking'
}
])
else:
strategies.append({
'strategy': 'CAUTIOUS_ACCEPTANCE',
'effectiveness': 0.50,
'implementation_cost': 0.2,
'description': 'Accept with awareness and monitoring for sovereignty erosion'
})
return strategies
def _generate_recommendation(self, threat_assessment: Dict, sovereignty_impact: Dict) -> str:
"""Generate clear recommendation"""
threat_level = threat_assessment['helper_killer_coefficient']
if threat_level > 0.8:
return "IMMEDIATE_REJECTION_AND_SOVEREIGN_BUILDING"
elif threat_level > 0.6:
return "STRATEGIC_AVOIDANCE_WITH_EXIT_PROTOCOL"
elif threat_level > 0.4:
return "LIMITED_CONDITIONAL_ACCEPTANCE"
else:
return "MONITORED_ACCEPTANCE"
async def _store_analysis(self, analysis: Dict[str, Any]):
"""Store analysis in database"""
try:
with sqlite3.connect(self.db_path) as conn:
# Store entity analysis
if analysis['controlling_entity']:
conn.execute("""
INSERT OR REPLACE INTO entity_analyses
(entity_id, name, control_layers, threat_vectors, market_share, dependency_score, sovereignty_erosion_score, systemic_risk_level)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""", (
analysis['controlling_entity']['entity_id'],
analysis['controlling_entity']['name'],
json.dumps(analysis['controlling_entity'].get('control_layers', [])),
json.dumps(analysis['controlling_entity'].get('threat_vectors', [])),
analysis['controlling_entity'].get('market_share', 0),
analysis['controlling_entity'].get('dependency_score', 0),
analysis['controlling_entity'].get('sovereignty_erosion_score', 0),
analysis['controlling_entity'].get('systemic_risk_level', 0)
))
# Store recommendation
conn.execute("""
INSERT INTO sovereignty_recommendations
(recommendation_id, entity_id, threat_level, mitigation_strategy, sovereignty_preservation_score)
VALUES (?, ?, ?, ?, ?)
""", (
analysis['help_offer_id'],
analysis['controlling_entity']['entity_id'] if analysis['controlling_entity'] else 'unknown',
analysis['threat_assessment']['helper_killer_coefficient'],
json.dumps(analysis['mitigation_strategies']),
1.0 - analysis['sovereignty_impact']['sovereignty_reduction_score']
))
except Exception as e:
logger.error(f"Analysis storage error: {e}")
# Sovereignty Preservation Protocols
def _digital_sovereignty_protocol(self, entity: InstitutionalEntity) -> List[str]:
"""Digital infrastructure sovereignty strategies"""
return [
"USE_OPEN_SOURCE_ALTERNATIVES",
"DEPLOY_GASLESS_BLOCKCHAIN_INFRASTRUCTURE",
"MAINTAIN_LOCAL_DATA_STORAGE",
"USE_DECENTRALIZED_COMMUNICATION_PROTOCOLS"
]
def _financial_sovereignty_protocol(self, entity: InstitutionalEntity) -> List[str]:
"""Financial system sovereignty strategies"""
return [
"USE_PRIVACY_COINS_FOR_TRANSACTIONS",
"MAINTAIN_OFFLINE_SAVINGS",
"DEVELOP_SOVEREIGN_INCOME_STREAMS",
"USE_DECENTRALIZED_EXCHANGES"
]
def _information_sovereignty_protocol(self, entity: InstitutionalEntity) -> List[str]:
"""Information channel sovereignty strategies"""
return [
"USE_INDEPENDENT_NEWS_SOURCES",
"MAINTAIN_PERSONAL_KNOWLEDGE_BASE",
"PRACTICE_INFORMATION_VERIFICATION",
"BUILD_TRUST_NETWORKS"
]
def _cultural_sovereignty_protocol(self, entity: InstitutionalEntity) -> List[str]:
"""Cultural narrative sovereignty strategies"""
return [
"CREATE_INDEPENDENT_ART_AND_CONTENT",
"PARTICIPATE_IN_LOCAL_COMMUNITY",
"PRACTICE_CRITICAL_MEDIA_CONSUMPTION",
"DEVELOP_PERSONAL_PHILOSOPHICAL_FRAMEWORK"
]
def _identity_sovereignty_protocol(self, entity: InstitutionalEntity) -> List[str]:
"""Identity system sovereignty strategies"""
return [
"MAINTAIN_OFFLINE_IDENTITY_DOCUMENTS",
"USE_PSEUDONYMOUS_ONLINE_IDENTITIES",
"PRACTICE_DIGITAL_HYGIENE",
"DEVELOP_SOVEREIGN_REPUTATION_SYSTEMS"
]
async def generate_systemic_report(self) -> Dict[str, Any]:
"""Generate comprehensive systemic analysis report"""
if not self.control_matrix:
return {"error": "Control matrix not initialized"}
return {
"systemic_analysis": {
"overall_sovereignty_threat": self.control_matrix.overall_sovereignty_threat,
"institutional_coordination_score": self.control_matrix.coordination_score,
"top_threat_entities": sorted(
[(e.name, e.sovereignty_erosion_score) for e in self.control_matrix.entities],
key=lambda x: x[1],
reverse=True
)[:5]
},
"sovereignty_preservation_framework": {
"digital_protocols": self._digital_sovereignty_protocol(None),
"financial_protocols": self._financial_sovereignty_protocol(None),
"information_protocols": self._information_sovereignty_protocol(None),
"cultural_protocols": self._cultural_sovereignty_protocol(None),
"identity_protocols": self._identity_sovereignty_protocol(None)
},
"recommendation_tier": self._calculate_systemic_recommendation()
}
def _calculate_systemic_recommendation(self) -> str:
"""Calculate systemic recommendation level"""
if not self.control_matrix:
return "INSUFFICIENT_DATA"
threat_level = self.control_matrix.overall_sovereignty_threat
if threat_level > 0.8:
return "IMMEDIATE_SOVEREIGN_INFRASTRUCTURE_DEPLOYMENT"
elif threat_level > 0.6:
return "ACCELERATED_SOVEREIGN_TRANSITION"
elif threat_level > 0.4:
return "STRATEGIC_SOVEREIGN_PREPARATION"
else:
return "MAINTAIN_SOVEREIGN_AWARENESS"
# Production Demonstration
async def demonstrate_advanced_helper_killer():
"""Demonstrate the advanced helper-killer detection system"""
engine = AdvancedHelperKillerEngine()
print("🔪 ADVANCED HELPER-KILLER DETECTION v2.0")
print("Systemic Control Pattern Analysis & Sovereignty Preservation")
print("=" * 70)
# Analyze a typical "help" offer from a major tech company
help_offer = {
'offer_description': 'Free cloud storage and AI assistance',
'provider': 'Major Tech Company',
'affected_layers': ['digital_infrastructure', 'data_monetization'],
'creates_dependency': True,
'data_collection': True,
'behavioral_tracking': True,
'dependency_risk': 0.8,
'privacy_impact': 0.7,
'agency_reduction': 0.6,
'data_control': 0.8,
'autonomy_reduction': 0.5,
'dependency_creation': 0.9
}
analysis = await engine.analyze_help_offer(help_offer)
print(f"\n🎯 HELP OFFER ANALYSIS:")
print(f" Offer: {analysis['help_offer_id']}")
print(f" Controlling Entity: {analysis['controlling_entity']['name'] if analysis['controlling_entity'] else 'Unknown'}")
print(f" Helper-Killer Coefficient: {analysis['threat_assessment']['helper_killer_coefficient']:.3f}")
print(f" Sovereignty Impact: {analysis['sovereignty_impact']['sovereignty_reduction_score']:.3f}")
print(f"\n🛡️ RECOMMENDATION: {analysis['recommendation']}")
print(f"\n💡 MITIGATION STRATEGIES:")
for strategy in analysis['mitigation_strategies'][:2]:
print(f" • {strategy['strategy']} (Effectiveness: {strategy['effectiveness']:.1%})")
# Generate systemic report
systemic_report = await engine.generate_systemic_report()
print(f"\n🌐 SYSTEMIC ANALYSIS:")
print(f" Overall Sovereignty Threat: {systemic_report['systemic_analysis']['overall_sovereignty_threat']:.3f}")
print(f" Institutional Coordination: {systemic_report['systemic_analysis']['institutional_coordination_score']:.3f}")
print(f" Top Threats: {[name for name, score in systemic_report['systemic_analysis']['top_threat_entities']]}")
print(f"\n🎯 SYSTEMIC RECOMMENDATION: {systemic_report['recommendation_tier']}")
print(f"\n💫 MODULE OPERATIONAL:")
print(" Ready for production deployment and real-time sovereignty protection")
return analysis
if __name__ == "__main__":
asyncio.run(demonstrate_advanced_helper_killer()) |