Portal Mode

class PortalStrategy:
    """
    Backward simulation strategy for portal-anchored scenarios.
    
    Attributes:
        config: TemporalConfig with mode=PORTAL
        llm: LLM client for state generation and scoring
        store: GraphStore for persistence
        entity_roster: Optional dict of entity definitions from template
    """
    
    def run(self) -> list[PortalPath]:
        """
        Execute portal-anchored backward simulation.
        
        Returns:
            List of PortalPath objects, ranked by coherence score
        
        Process:
        1. Generate portal endpoint state from description
        2. Determine exploration strategy (adaptive/oscillating/random)
        3. Generate backward paths (N paths, M steps each)
        4. Validate forward coherence (can we get from origin to portal?)
        5. Rank paths by hybrid scoring
        6. Detect pivot points using path divergence analysis
        7. Return top K ranked paths with explanations
        """

@dataclass
class PortalState:
    """A state at a specific point in the backward simulation"""
    year: int
    month: int
    description: str
    entities: list[Entity]
    world_state: dict[str, Any]
    plausibility_score: float = 0.0
    parent_state: Optional["PortalState"] = None  # T+1
    children_states: list["PortalState"] = field(default_factory=list)  # T-1
    resolution_level: ResolutionLevel = None

@dataclass
class PortalPath:
    """Complete path from origin to portal"""
    path_id: str
    states: list[PortalState]  # Ordered origin→portal
    coherence_score: float
    pivot_points: list[int]  # Indices of critical decisions
    explanation: str
    validation_details: dict[str, Any]

{
  "temporal": {
    "mode": "portal",
    "portal_description": "The endpoint state description",
    "portal_year": 2031,
    "origin_year": 2026,
    "backward_steps": 10,
    "exploration_mode": "adaptive",
    "candidate_antecedents_per_step": 3,
    "path_count": 5,
    "coherence_threshold": 0.7,
    "use_simulation_judging": true,
    "simulation_forward_steps": 1,
    "judge_model": "meta-llama/llama-3.1-405b-instruct"
  }
}

{
  "scenario_description": "PORTAL backward reasoning from a failed crewed Mars mission in 2031 to its origins in 2026. The Ares III crew of 4 astronauts launched successfully but lost contact during Mars orbital insertion.",
  "temporal": {
    "mode": "portal",
    "portal_description": "Ares III crewed Mars mission loses contact during orbital insertion in March 2031. Last telemetry shows cascading systems failures in life support and communications. Trace backward to understand how this disaster was built, decision by decision.",
    "portal_year": 2031,
    "origin_year": 2026,
    "backward_steps": 10,
    "exploration_mode": "adaptive",
    "candidate_antecedents_per_step": 3,
    "path_count": 5,
    "coherence_threshold": 0.7,
    "use_simulation_judging": true,
    "judge_model": "meta-llama/llama-3.1-405b-instruct",
    "fidelity_planning_mode": "hybrid",
    "token_budget": 200000.0
  },
  "metadata": {
    "entity_roster": {
      "sarah_okafor": {
        "role": "Mission Commander. Experienced but politically pressured.",
        "initial_knowledge": ["mission_parameters", "crew_capabilities"]
      },
      "raj_mehta": {
        "role": "Flight Engineer. Brilliant but conflict-averse.",
        "initial_knowledge": ["flight_systems_status", "anomaly_detection"]
      },
      "lin_zhang": {
        "role": "Systems Engineer. Detected anomalies but was overruled.",
        "initial_knowledge": ["alss_design", "oxygen_generator_failures"]
      },
      "thomas_webb": {
        "role": "Mission Director. Prioritized schedule over safety.",
        "initial_knowledge": ["budget_constraints", "schedule_milestones"]
      }
    }
  }
}

{
  "scenario_description": "PORTAL backward reasoning from $47M trade secret verdict to the chain of decisions that made it inevitable. Working backward from jury verdict through discovery, depositions, document retention failures, and initial IP protection gaps.",
  "temporal": {
    "mode": "portal",
    "portal_description": "$47 million jury verdict for plaintiff in trade secret misappropriation case. Jury found defendant willfully misappropriated 14 proprietary algorithms and customer data. Verdict includes $32M compensatory damages and $15M punitive damages.",
    "portal_year": 2025,
    "origin_year": 2020,
    "backward_steps": 12,
    "path_count": 5,
    "coherence_threshold": 0.75
  }
}

def _score_path(self, path: PortalPath) -> float:
    """
    Composite scoring:
    - LLM plausibility (30%): Does this make narrative sense?
    - Historical precedent (20%): Has something similar happened?
    - Causal necessity (30%): Must A → B given C?
    - Entity capability (20%): Can entity X perform action Y?
    """
    llm_score = self._llm_plausibility(path)
    historical_score = self._historical_similarity(path)
    causal_score = self._causal_necessity(path)
    capability_score = self._entity_capability_check(path)
    
    return (
        llm_score * self.config.llm_scoring_weight +
        historical_score * self.config.historical_precedent_weight +
        causal_score * self.config.causal_necessity_weight +
        capability_score * self.config.entity_capability_weight
    )

def _detect_pivot_points(self, path: PortalPath, divergence_analysis: dict) -> list[int]:
    """
    Identify states where decisions created irreversible consequences.
    
    A pivot point is a state where:
    1. Multiple alternative antecedents were plausible
    2. The chosen antecedent had high causal weight
    3. Alternate paths would have led to different outcomes
    """

{
  "path_id": "portal_path_a8f9",
  "pivot_points": [3, 7, 9],
  "pivot_explanations": [
    "State 3 (Aug 2027): Lin Zhang's anomaly report was marked 'reviewed' without escalation. If escalated, mission would have delayed 6 months for ALSS redesign.",
    "State 7 (Jan 2029): Budget cut forced crew reduction from 6 to 4. Eliminated redundancy in life support operations.",
    "State 9 (Nov 2030): Pre-launch review overrode safety concerns to meet launch window. Final point of no return."
  ]
}

# Run a portal template
./run.sh run mars_mission_portal

# Quick mode (fewer steps, lower cost)
./run.sh run mars_mission_portal --portal-quick

# With simulation judging enabled
./run.sh run mars_mission_portal --portal-simjudged-quick