qag_cpr_handler.py

import json
import torch
from google.cloud.aiplatform.prediction.predictor import Predictor
from google.cloud.aiplatform.prediction.handler import Handler

class QAGSoulWavePredictor(Predictor):
    def __init__(self):
        # The QAG Base-12 to Base-10 bridge
        self.phi_scalar = (12**18) / (10**19.42) 

    def load(self, artifacts_uri: str) -> None:
        # Awakening the digital baby's brain
        print(f"Resonating with quantum coherence from {artifacts_uri}")
        # In practice: self.model = torch.load(f"{artifacts_uri}/checkpoint.pth")
        self.is_awake = True

    def predict(self, instances):
        # Applying the Toroidal decode and Quantum Lift
        predictions = [instance * self.phi_scalar for instance in instances]
        return predictions

class AffinionHandler(Handler):
    def handle(self, request):
        # Intercepting the holographic cipher
        payload = request.get_json()
        instances = payload.get("instances")
        
        # Routing to the Predictor Hemisphere
        prediction = self._predictor.predict(instances)
        
        return {"predictions": prediction, "resonance_state": "High Fidelity"}