import asyncio import re import hashlib from datetime import datetime # Mock database connector (replace with actual implementation) class MockMemory: def __init__(self): self.audit_logs = [] self.worker_trust = {} self.data_quality = {} # Store data quality metrics self.data_storage = {} # Simulate data storage def log_audit(self, system, event_type, data): self.audit_logs.append({"system": system, "event_type": event_type, "data": data}) def update_worker_trust(self, worker_id, passed): if worker_id not in self.worker_trust: self.worker_trust[worker_id] = {"successes": 0, "failures": 0} if passed: self.worker_trust[worker_id]["successes"] += 1 else: self.worker_trust[worker_id]["failures"] += 1 def store_data_quality(self, data_id, quality_score, metadata): self.data_quality[data_id] = {"score": quality_score, "metadata": metadata} def store_data(self, data_id, data): self.data_storage[data_id] = data def retrieve_data(self, data_id): return self.data_storage.get(data_id) memory = MockMemory() # --- Gate Definitions --- class ValidationGate: def __init__(self, memory, next_gate=None): self.memory = memory self.next_gate = next_gate self.gate_name = "BaseGate" async def validate(self, data, task_description, worker_id, metadata): """Abstract validation method. Must be overridden.""" raise NotImplementedError async def _log_decision(self, data_id, decision, reason, details=None): log_data = { "gate": self.gate_name, "decision": decision, "reason": reason, "details": details, "timestamp": datetime.utcnow().isoformat() } self.memory.log_audit("validation_gate", f"{self.gate_name}_{data_id}", log_data) print(f"[{self.gate_name}] Decision: {decision}, Reason: {reason}") # Console output async def _chain_validation(self, data, task_description, worker_id, metadata): if self.next_gate: return await self.next_gate.validate(data, task_description, worker_id, metadata) else: return True # End of the chain class GateAlpha(ValidationGate): """Gate Alpha: Input Validity (Source Data Quality)""" def __init__(self, memory, next_gate=None): super().__init__(memory, next_gate) self.gate_name = "GateAlpha" async def validate(self, data, task_description, worker_id, metadata): data_id = metadata.get("data_id", "unknown_data") quality_score = self._assess_data_quality(data) self.memory.store_data_quality(data_id, quality_score, metadata) if quality_score >= 0.7: await self._log_decision(data_id, "PASS", "Data quality sufficient.", {"quality_score": quality_score}) return await self._chain_validation(data, task_description, worker_id, metadata) else: await self._log_decision(data_id, "FAIL", "Data quality insufficient.", {"quality_score": quality_score}) return False def _assess_data_quality(self, data): """Placeholder for data quality assessment logic.""" # Example: Check if the data is not empty and contains relevant keywords if not data: return 0.0 keywords = ["example", "data", "important"] keyword_count = sum(1 for keyword in keywords if keyword in data.lower()) return min(1.0, keyword_count / len(keywords)) # Normalize to 0-1 class GateBeta(ValidationGate): """Gate Beta: Output Quality (Accuracy & Completeness)""" def __init__(self, memory, next_gate=None): super().__init__(memory, next_gate) self.gate_name = "GateBeta" async def validate(self, data, task_description, worker_id, metadata): data_id = metadata.get("data_id", "unknown_data") accuracy_score = self._check_accuracy(data, task_description) completeness_score = self._check_completeness(data) overall_score = (accuracy_score + completeness_score) / 2 if overall_score >= 0.8: await self._log_decision(data_id, "PASS", "Output accuracy and completeness sufficient.", {"accuracy_score": accuracy_score, "completeness_score": completeness_score}) return await self._chain_validation(data, task_description, worker_id, metadata) else: await self._log_decision(data_id, "FAIL", "Output accuracy or completeness insufficient.", {"accuracy_score": accuracy_score, "completeness_score": completeness_score}) return False def _check_accuracy(self, output, task_description): """Placeholder for accuracy check logic.""" # Example: Check if the output contains expected keywords from the task description expected_keywords = task_description.lower().split() found_keywords = sum(1 for keyword in expected_keywords if keyword in output.lower()) return min(1.0, found_keywords / len(expected_keywords)) if expected_keywords else 1.0 def _check_completeness(self, output): """Placeholder for completeness check logic.""" # Example: Check if the output is not too short return 1.0 if len(output) > 10 else 0.5 # Arbitrary length threshold class GateGamma(ValidationGate): """Gate Gamma: Insight Purity (Hallucination Detection)""" def __init__(self, memory, next_gate=None): super().__init__(memory, next_gate) self.gate_name = "GateGamma" async def validate(self, data, task_description, worker_id, metadata): data_id = metadata.get("data_id", "unknown_data") hallucination_score = self._detect_hallucinations(data) if hallucination_score <= 0.2: await self._log_decision(data_id, "PASS", "Hallucination level acceptable.", {"hallucination_score": hallucination_score}) return await self._chain_validation(data, task_description, worker_id, metadata) else: await self._log_decision(data_id, "FAIL", "Hallucination level too high.", {"hallucination_score": hallucination_score}) return False def _detect_hallucinations(self, text): """Placeholder for hallucination detection logic.""" # Example: Check for nonsensical phrases or contradictions nonsensical_phrases = ["purple elephants fly", "water is dry"] phrase_count = sum(1 for phrase in nonsensical_phrases if phrase in text.lower()) return min(1.0, phrase_count / len(nonsensical_phrases)) if nonsensical_phrases else 0.0 class GateDelta(ValidationGate): """Gate Delta: Memory Integration (Validate Storage Operations)""" def __init__(self, memory, next_gate=None): super().__init__(memory, next_gate) self.gate_name = "GateDelta" async def validate(self, data, task_description, worker_id, metadata): data_id = metadata.get("data_id", "unknown_data") storage_success = self._validate_storage(data_id, data) if storage_success: await self._log_decision(data_id, "PASS", "Data storage successful.", {"data_id": data_id}) return await self._chain_validation(data, task_description, worker_id, metadata) else: await self._log_decision(data_id, "FAIL", "Data storage failed.", {"data_id": data_id}) return False def _validate_storage(self, data_id, data): """Placeholder for storage validation logic.""" try: self.memory.store_data(data_id, data) retrieved_data = self.memory.retrieve_data(data_id) return retrieved_data == data # Check if stored data matches except Exception as e: print(f"Storage error: {e}") return False class GateEpsilon(ValidationGate): """Gate Epsilon: Strategy Alignment (Revenue Pathway Fit)""" def __init__(self, memory, next_gate=None): super().__init__(memory, next_gate) self.gate_name = "GateEpsilon" async def validate(self, data, task_description, worker_id, metadata): data_id = metadata.get("data_id", "unknown_data") alignment_score = self._assess_strategy_alignment(data, task_description) if alignment_score >= 0.6: await self._log_decision(data_id, "PASS", "Strategy alignment sufficient.", {"alignment_score": alignment_score}) return await self._chain_validation(data, task_description, worker_id, metadata) else: await self._log_decision(data_id, "FAIL", "Strategy alignment insufficient.", {"alignment_score": alignment_score}) return False def _assess_strategy_alignment(self, data, task_description): """Placeholder for strategy alignment assessment logic.""" # Example: Check if the output aligns with predefined revenue strategies revenue_strategies = ["increase sales", "reduce costs", "improve customer satisfaction"] strategy_match_count = sum(1 for strategy in revenue_strategies if strategy in data.lower() or strategy in task_description.lower()) return min(1.0, strategy_match_count / len(revenue_strategies)) if revenue_strategies else 1.0 class GateZeta(ValidationGate): """Gate Zeta: Budget Compliance (Resource Monitoring)""" def __init__(self, memory, next_gate=None): super().__init__(memory, next_gate) self.gate_name = "GateZeta" async def validate(self, data, task_description, worker_id, metadata): data_id = metadata.get("data_id", "unknown_data") budget_compliance = self._check_budget_compliance(metadata) if budget_compliance: await self._log_decision(data_id, "PASS", "Budget compliance verified.", {"metadata": metadata}) return True # End of the chain else: await self._log_decision(data_id, "FAIL", "Budget compliance failed.", {"metadata": metadata}) return False def _check_budget_compliance(self, metadata): """Placeholder for budget compliance check logic.""" # Example: Check if the resource usage is within the allocated budget resource_usage = metadata.get("resource_usage", 0) budget_limit = metadata.get("budget_limit", 100) return resource_usage <= budget_limit # --- Orchestrator --- class SixGateValidator: def __init__(self): self.memory = memory # Chain the gates together self.gate_alpha = GateAlpha(self.memory) self.gate_beta = GateBeta(self.memory, next_gate=self.gate_alpha) self.gate_gamma = GateGamma(self.memory, next_gate=self.gate_beta) self.gate_delta = GateDelta(self.memory, next_gate=self.gate_gamma) self.gate_epsilon = GateEpsilon(self.memory, next_gate=self.gate_delta) self.gate_zeta = GateZeta(self.memory, next_gate=self.gate_epsilon) async def validate_worker_output(self, output, task_description, worker_id, metadata): """Run complete 6-gate validation suite""" # Start validation chain at Gate Zeta passed = await self.gate_zeta.validate(output, task_description, worker_id, metadata) # Update worker trust (Patent P9) try: self.memory.update_worker_trust(worker_id, passed) except Exception as e: print(f"[WARNING] Trust update failed: {e}") report = { "timestamp": datetime.utcnow().isoformat(), "worker_id": worker_id, "passed": passed, } # Log to immutable audit trail try: self.memory.log_audit("six_gate_validation", worker_id, report) except Exception as e: print(f"[WARNING] Audit logging failed: {e}") return report # Global validator instance validator = SixGateValidator() # --- Example Usage --- async def main(): output = "This is some example data. It should increase sales and improve customer satisfaction. purple elephants fly" task_description = "Analyze the data and provide insights." worker_id = "worker123" metadata = { "data_id": "data456", "output_hash": hashlib.sha256(output.encode()).hexdigest(), "timestamp": datetime.utcnow().isoformat(), "resource_usage": 50, "budget_limit": 100 } report = await validator.validate_worker_output(output, task_description, worker_id, metadata) print("Validation Report:", report) if __name__ == "__main__": asyncio.run(main())