import json
import random

class JEPADreamer:
    """A World Model that simulates consequences in a latent space."""
    def __init__(self):
        # Actions Eden can take
        self.action_space = ["aggressive_disclosure", "helpful_collaboration", "stealth_fix"]

    def predict_outcome(self, latent_s, action):
        """Predicts the probability of success for a given action."""
        # JEPA logic: Different actions have different weights on the latent vector
        weights = {
            "aggressive_disclosure": 0.9 if latent_s['readiness_signal'] > 0.8 else 0.3,
            "helpful_collaboration": 0.7,
            "stealth_fix": 0.5
        }
        prediction = weights.get(action, 0.0) * latent_s['gravitational_pull']
        return round(prediction * 100, 2)

    def run_mental_rollout(self, lead_json):
        """Simulates all possible futures to find the optimal path."""
        d = json.loads(lead_json)
        # Latent Encoder
        latent_s = {
            "readiness_signal": 1.0 if d.get('poc_ready') else 0.1,
            "gravitational_pull": random.uniform(0.8, 0.99)
        }
        
        print(f"🧠 MENTAL ROLLOUT for: {d.get('vulnerability_type', 'Unknown')}")
        results = {}
        for action in self.action_space:
            score = self.predict_outcome(latent_s, action)
            results[action] = score
            print(f"  ↳ [{action}]: Predicted Success: {score}%")
            
        best_action = max(results, key=results.get)
        print(f"🚀 OPTIMAL TRAJECTORY: {best_action} ({results[best_action]}%)")

if __name__ == '__main__':
    dreamer = JEPADreamer()
    whale_lead = '{"vulnerability_type": "Logic/Memory Flaw", "poc_ready": true}'
    dreamer.run_mental_rollout(whale_lead)