opentrustprotocol 2.0.0

🐍 Official Python SDK for OpenTrust Protocol - The mathematical embodiment of trust itself. Features neutrosophic judgments, fusion operators, OTP mappers, and REVOLUTIONARY Conformance Seals with mathematical proof of conformance.

🐍 OpenTrust Protocol (OTP) - Python SDK

🌟 REVOLUTIONARY UPDATE: v2.0.0 - Conformance Seals

OTP v2.0 introduces the Zero Pillar: Proof-of-Conformance Seals

Every fusion operation now generates a cryptographic fingerprint (SHA-256 hash) that proves the operation was performed according to the exact OTP specification. This transforms OTP from a trust protocol into the mathematical embodiment of trust itself.

The official Python implementation of the OpenTrust Protocol - The mathematical embodiment of trust itself

🚀 What is OpenTrust Protocol?

The OpenTrust Protocol (OTP) is a revolutionary framework for representing and managing uncertainty, trust, and auditability in AI systems, blockchain applications, and distributed networks. Built on neutrosophic logic, OTP provides a mathematical foundation for handling incomplete, inconsistent, and uncertain information.

🎯 Why OTP Matters

• 🔒 Trust & Security: Quantify trust levels in AI decisions and blockchain transactions
• 📊 Uncertainty Management: Handle incomplete and contradictory information gracefully
• 🔍 Full Auditability: Complete provenance chain for every decision
• 🌐 Cross-Platform: Interoperable across Python, JavaScript, Rust, and more
• ⚡ Performance: Optimized for production environments with minimal overhead

🐍 Python SDK Features

Core Components

• Neutrosophic Judgments: Represent evidence as (T, I, F) values where T + I + F ≤ 1.0
• Fusion Operators: Combine multiple judgments with conflict-aware algorithms
• OTP Mappers: Transform raw data into neutrosophic judgments
• Provenance Chain: Complete audit trail for every transformation

🔐 Conformance Seals (v2.0.0) - THE REVOLUTION

Mathematical Proof of Conformance

Every fusion operation automatically generates a Conformance Seal - a cryptographic SHA-256 hash that proves the operation was performed according to the exact OTP specification:

from otp import conflict_aware_weighted_average, verify_conformance_seal_with_inputs

# Create judgments
judgment1 = NeutrosophicJudgment(0.8, 0.2, 0.0, [{"source_id": "sensor1"}])
judgment2 = NeutrosophicJudgment(0.6, 0.3, 0.1, [{"source_id": "sensor2"}])

# Fusion automatically generates Conformance Seal
fused = conflict_aware_weighted_average([judgment1, judgment2], [0.6, 0.4])

# Extract the Conformance Seal
seal = fused.provenance_chain[-1]["conformance_seal"]
print(f"🔐 Conformance Seal: {seal}")

# Verify mathematical proof of conformance
is_valid = verify_conformance_seal_with_inputs(fused, [judgment1, judgment2], [0.6, 0.4])
print(f"✅ Mathematical proof verified: {is_valid}")

The Revolution:

• Self-Auditing: OTP audits itself through mathematics
• Tamper Detection: Any modification breaks the seal instantly
• Independent Verification: Anyone can verify conformance without trust
• Solves the Paradox: "Who audits the auditor?" - OTP does!

🆕 OTP Mapper System (v1.0.6)

Transform any data type into neutrosophic judgments:

from otp import NumericalMapper, CategoricalMapper, BooleanMapper
from otp.types import NumericalParams, CategoricalParams, BooleanParams

# DeFi Health Factor Mapping
health_mapper = NumericalMapper(NumericalParams(
    id="defi-health-factor",
    version="1.0.0",
    falsity_point=1.0,      # Liquidation threshold
    indeterminacy_point=1.5, # Warning zone  
    truth_point=2.0,        # Safe zone
    clamp_to_range=True
))

# Transform health factor to neutrosophic judgment
judgment = health_mapper.apply(1.8)
print(f"Health Factor 1.8: T={judgment.T:.3f}, I={judgment.I:.3f}, F={judgment.F:.3f}")

Available Mappers

Mapper Type	Use Case	Example
NumericalMapper	Continuous data interpolation	DeFi health factors, IoT sensors
CategoricalMapper	Discrete category mapping	KYC status, product categories
BooleanMapper	Boolean value transformation	SSL certificates, feature flags

📦 Installation

pip install opentrustprotocol

🚀 Quick Start

Basic Neutrosophic Judgment

from otp import NeutrosophicJudgment, fuse

# Create judgments with provenance
judgment1 = NeutrosophicJudgment(
    T=0.8, I=0.2, F=0.0,
    provenance_chain=[{
        "source_id": "sensor1",
        "timestamp": "2023-01-01T00:00:00Z"
    }]
)

judgment2 = NeutrosophicJudgment(
    T=0.6, I=0.3, F=0.1,
    provenance_chain=[{
        "source_id": "sensor2", 
        "timestamp": "2023-01-01T00:00:00Z"
    }]
)

# Fuse judgments with conflict-aware weighted average
fused = fuse.conflict_aware_weighted_average(
    judgments=[judgment1, judgment2],
    weights=[0.6, 0.4]
)

print(f"Fused: {fused}")

Real-World Example: DeFi Risk Assessment

from otp import *
from otp.types import *
from typing import Dict

# 1. Health Factor Mapper
health_mapper = NumericalMapper(NumericalParams(
    id="health-factor",
    version="1.0.0",
    falsity_point=1.0,
    indeterminacy_point=1.5,
    truth_point=2.0,
    clamp_to_range=True
))

# 2. KYC Status Mapper
kyc_mappings = {
    "VERIFIED": JudgmentData(T=0.9, I=0.1, F=0.0),
    "PENDING": JudgmentData(T=0.3, I=0.7, F=0.0),
    "REJECTED": JudgmentData(T=0.0, I=0.0, F=1.0)
}

kyc_mapper = CategoricalMapper(CategoricalParams(
    id="kyc-status",
    version="1.0.0",
    mappings=kyc_mappings,
    default_judgment=None
))

# 3. SSL Certificate Mapper
ssl_mapper = BooleanMapper(BooleanParams(
    id="ssl-cert",
    version="1.0.0",
    true_map=JudgmentData(T=0.9, I=0.1, F=0.0),
    false_map=JudgmentData(T=0.0, I=0.0, F=1.0)
))

# 4. Transform data to judgments
health_judgment = health_mapper.apply(1.8)
kyc_judgment = kyc_mapper.apply("VERIFIED")
ssl_judgment = ssl_mapper.apply(True)

# 5. Fuse for final risk assessment
risk_assessment = fuse.conflict_aware_weighted_average(
    judgments=[health_judgment, kyc_judgment, ssl_judgment],
    weights=[0.5, 0.3, 0.2]  # Health factor most important
)

print(f"DeFi Risk Assessment: T={risk_assessment.T:.3f}, I={risk_assessment.I:.3f}, F={risk_assessment.F:.3f}")

🏗️ Architecture

Performance & Reliability

• 🔒 Memory Efficient: Optimized data structures with minimal overhead
• ⚡ Fast Execution: C-optimized operations where possible
• 🔄 Thread Safe: Safe concurrent access with proper locking
• 📦 Minimal Dependencies: Only essential packages for reliability

Mapper Registry System

from otp import get_global_registry

registry = get_global_registry()

# Register mappers
registry.register(health_mapper)
registry.register(kyc_mapper)

# Retrieve and use
mapper = registry.get("health-factor")
judgment = mapper.apply(1.5)

# Export configurations
configs = registry.export()

🧪 Testing

Run the comprehensive test suite:

python -m pytest tests/

Run examples:

python examples/mapper_examples.py

📊 Use Cases

🔗 Blockchain & DeFi

• Risk Assessment: Health factors, liquidation risks
• KYC/AML: Identity verification, compliance scoring
• Oracle Reliability: Data source trust evaluation

🤖 AI & Machine Learning

• Uncertainty Quantification: Model confidence scoring
• Data Quality: Input validation and reliability
• Decision Fusion: Multi-model ensemble decisions

🌐 IoT & Sensors

• Sensor Reliability: Temperature, pressure, motion sensors
• Data Fusion: Multi-sensor decision making
• Anomaly Detection: Trust-based outlier identification

🏭 Supply Chain

• Product Tracking: Status monitoring and verification
• Quality Control: Defect detection and classification
• Compliance: Regulatory requirement tracking

🔧 Advanced Features

Custom Mapper Creation

from otp.types import Mapper, MapperType, MapperParams
from otp import NeutrosophicJudgment

class CustomMapper(Mapper):
    def __init__(self, params: MapperParams):
        self.params = params
    
    def apply(self, input_value: any) -> NeutrosophicJudgment:
        # Your transformation logic
        return NeutrosophicJudgment(T=0.8, I=0.2, F=0.0, provenance_chain=[])
    
    def get_params(self) -> MapperParams:
        return self.params
    
    def get_type(self) -> MapperType:
        return MapperType.Custom
    
    def validate(self) -> bool:
        # Validate your parameters
        return True

JSON Schema Validation

from otp import MapperValidator

validator = MapperValidator()
result = validator.validate(mapper_params)

if result.valid:
    print("✅ Valid mapper configuration")
else:
    for error in result.errors:
        print(f"❌ Validation error: {error}")

🌟 Why Choose OTP Python SDK?

🚀 Performance

• Optimized operations - Minimal runtime overhead
• Memory efficient - Smart garbage collection
• Fast development - Rich ecosystem integration

🔒 Safety

• Type safety - Full type hints and validation
• Error handling - Comprehensive exception handling
• Data integrity - Immutable provenance chains

🔧 Developer Experience

• Rich ecosystem - Seamless integration with Python tools
• Comprehensive docs - Extensive documentation and examples
• Active community - Growing ecosystem and support

📈 Performance Benchmarks

Operation	Time	Memory
Judgment Creation	< 10μs	64 bytes
Mapper Application	< 15μs	128 bytes
Fusion (10 judgments)	< 50μs	512 bytes

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

git clone https://github.com/draxork/opentrustprotocol-py.git
cd opentrustprotocol-py
pip install -e .
pytest
python examples/mapper_examples.py

📚 Documentation

• API Documentation - Complete API reference
• Examples - Real-world usage examples
• Specification - OTP v2.0 specification

🌐 Ecosystem

OTP is available across multiple platforms:

Platform	Package	Status
Python	opentrustprotocol	✅ v1.0.6
JavaScript	opentrustprotocol	✅ v1.0.3
Rust	opentrustprotocol	✅ v0.2.0

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Neutrosophic Logic: Founded by Florentin Smarandache
• Python Community: For the amazing language and ecosystem
• Open Source Contributors: Making trust auditable for everyone

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Made with ❤️ by the OpenTrust Protocol Team