import asyncio import re import hashlib from datetime import datetime from aiva.db_connector import memory # Placeholder for db_connector.py class memory: def __init__(self): self.audit_log = [] self.worker_trust = {} def log_audit(self, gate_name, worker_id, report): self.audit_log.append({"gate": gate_name, "worker_id": worker_id, "report": report}) 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 get_worker_trust(self, worker_id): return self.worker_trust.get(worker_id, {"successes": 0, "failures": 0}) def get_data(self, data_id): # Simulate data retrieval if data_id == "source_data_123": return "This is good source data." elif data_id == "bad_source_data": return "This data is incomplete and potentially inaccurate." else: return None # Validation Gates Implementation class ValidationGate: def __init__(self, gate_name, memory): self.gate_name = gate_name self.memory = memory async def validate(self, data, task_description, worker_id, metadata): """ Base validation method to be overridden by subclasses. """ raise NotImplementedError async def log_decision(self, worker_id, passed, reason, metadata=None): """ Logs the validation decision with a reason. """ log_entry = { "timestamp": datetime.utcnow().isoformat(), "gate": self.gate_name, "worker_id": worker_id, "passed": passed, "reason": reason, "metadata": metadata } self.memory.log_audit(self.gate_name, worker_id, log_entry) print(f"[{self.gate_name}] Decision: {'Passed' if passed else 'Failed'}, Reason: {reason}") class GateAlpha(ValidationGate): """Gate Alpha: Input validity - verify source data quality""" def __init__(self, memory): super().__init__("GateAlpha", memory) async def validate(self, data, task_description, worker_id, metadata): """Validates the quality of the source data.""" data_id = metadata.get("source_data_id") source_data = self.memory.get_data(data_id) if not source_data: await self.log_decision(worker_id, False, "Source data not found.") return False if "incomplete" in source_data.lower() or "inaccurate" in source_data.lower(): await self.log_decision(worker_id, False, "Source data is of poor quality.") return False await self.log_decision(worker_id, True, "Source data is valid.") return True class GateBeta(ValidationGate): """Gate Beta: Output quality - check accuracy and completeness""" def __init__(self, memory): super().__init__("GateBeta", memory) async def validate(self, data, task_description, worker_id, metadata): """Checks the accuracy and completeness of the output data.""" if not data or len(data) < 10: # Example: require a minimum length await self.log_decision(worker_id, False, "Output is incomplete or too short.") return False if "error" in data.lower() or "incorrect" in data.lower(): # Example: Check for error messages await self.log_decision(worker_id, False, "Output contains errors.") return False await self.log_decision(worker_id, True, "Output is accurate and complete.") return True class GateGamma(ValidationGate): """Gate Gamma: Insight purity - detect hallucinations""" def __init__(self, memory): super().__init__("GateGamma", memory) async def validate(self, data, task_description, worker_id, metadata): """Detects hallucinations in the output.""" # Placeholder: Implement a more sophisticated hallucination detection mechanism # Example: Check for nonsensical statements or contradictions if "unicorn" in data.lower() and "flying" in data.lower(): await self.log_decision(worker_id, False, "Detected a hallucination (flying unicorn).") return False await self.log_decision(worker_id, True, "No hallucinations detected.") return True class GateDelta(ValidationGate): """Gate Delta: Memory integration - validate storage operations""" def __init__(self, memory): super().__init__("GateDelta", memory) self.test_key = "test_data_key" async def validate(self, data, task_description, worker_id, metadata): """Validates storage operations by writing, reading, and verifying data.""" try: # Simulate writing data to memory self.memory.data_store = {self.test_key: data} retrieved_data = self.memory.data_store.get(self.test_key) if retrieved_data != data: await self.log_decision(worker_id, False, "Data retrieval failed.") return False await self.log_decision(worker_id, True, "Memory integration successful.") return True except Exception as e: await self.log_decision(worker_id, False, f"Memory integration failed: {e}") return False class GateEpsilon(ValidationGate): """Gate Epsilon: Strategy alignment - ensure revenue pathway fit""" def __init__(self, memory): super().__init__("GateEpsilon", memory) async def validate(self, data, task_description, worker_id, metadata): """Ensures the output aligns with the revenue generation strategy.""" # Placeholder: Implement a more sophisticated revenue alignment check if "revenue" not in task_description.lower(): await self.log_decision(worker_id, False, "Task does not appear to align with revenue generation.") return False await self.log_decision(worker_id, True, "Task aligns with revenue generation strategy.") return True class GateZeta(ValidationGate): """Gate Zeta: Budget compliance - resource monitoring""" def __init__(self, memory): super().__init__("GateZeta", memory) async def validate(self, data, task_description, worker_id, metadata): """Monitors resource usage and ensures budget compliance.""" # Placeholder: Implement a real resource monitoring and budget check worker_trust = self.memory.get_worker_trust(worker_id) failure_rate = worker_trust["failures"] / (worker_trust["successes"] + worker_trust["failures"] + 1e-9) if failure_rate > 0.5: await self.log_decision(worker_id, False, "Worker failure rate exceeds budget compliance threshold.") return False await self.log_decision(worker_id, True, "Resource usage within budget compliance limits.") return True # Orchestrator for the Six-Gate Validation System class SixGateValidator: def __init__(self): self.memory = memory() self.gate_alpha = GateAlpha(self.memory) self.gate_beta = GateBeta(self.memory) self.gate_gamma = GateGamma(self.memory) self.gate_delta = GateDelta(self.memory) self.gate_epsilon = GateEpsilon(self.memory) self.gate_zeta = GateZeta(self.memory) self.gates = [self.gate_alpha, self.gate_beta, self.gate_gamma, self.gate_delta, self.gate_epsilon, self.gate_zeta] async def validate_worker_output(self, output, task_description, worker_id, metadata): """ Runs the complete six-gate validation suite. """ passed = True for gate in self.gates: gate_passed = await gate.validate(output, task_description, worker_id, metadata) if not gate_passed: passed = False break # Stop on first failure # Update worker trust based on the overall result try: self.memory.update_worker_trust(worker_id, passed) except Exception as e: print(f"[WARNING] Trust update failed: {e}") return passed # Example Usage (for demonstration purposes) async def main(): validator = SixGateValidator() output_data = "This is a valid output." task_description = "Generate a report on customer behavior." worker_id = "worker123" metadata = {"source_data_id": "source_data_123"} validation_result = await validator.validate_worker_output(output_data, task_description, worker_id, metadata) print(f"Overall Validation Result: {'Passed' if validation_result else 'Failed'}") # Example with failing conditions output_data_fail = "error: something went wrong" task_description_fail = "Process data" metadata_fail = {"source_data_id": "bad_source_data"} validation_result_fail = await validator.validate_worker_output(output_data_fail, task_description_fail, worker_id, metadata_fail) print(f"Overall Validation Result (Fail Case): {'Passed' if validation_result_fail else 'Failed'}") if __name__ == "__main__": asyncio.run(main())