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"""Pharma rule engine β€” hard and soft constraint checking.

Hard violations block action execution entirely (the action still
deducts no credits and the simulator returns a ``FailureReport``).
Soft violations allow execution but degrade output quality and incur
penalties.
"""

from __future__ import annotations

from dataclasses import dataclass
from enum import Enum
from typing import Iterable, List, Optional

from models import ActionType, DrugTargetAction

from server.simulator.latent_state import FullLatentState


class Severity(str, Enum):
    HARD = "hard"
    SOFT = "soft"


@dataclass
class RuleViolation:
    rule_id: str
    severity: Severity
    message: str


class RuleEngine:
    """Evaluates drug-target-validation constraints against the current
    latent state before each action is applied.
    """

    def check(
        self,
        action: DrugTargetAction,
        state: FullLatentState,
        *,
        evidence_dimensions_covered: Optional[Iterable[str]] = None,
    ) -> List[RuleViolation]:
        violations: List[RuleViolation] = []
        violations.extend(self._check_resource_constraints(action, state))
        violations.extend(self._check_submission(
            action, state, evidence_dimensions_covered or [],
        ))
        violations.extend(self._check_redundancy(action, state))
        violations.extend(self._check_ordering(action, state))
        return violations

    @staticmethod
    def hard_violations(violations: List[RuleViolation]) -> List[str]:
        return [v.message for v in violations if v.severity == Severity.HARD]

    @staticmethod
    def soft_violations(violations: List[RuleViolation]) -> List[str]:
        return [v.message for v in violations if v.severity == Severity.SOFT]

    # ── resource / credit constraints ───────────────────────────────────

    def _check_resource_constraints(
        self, action: DrugTargetAction, s: FullLatentState
    ) -> List[RuleViolation]:
        vs: List[RuleViolation] = []
        from server.simulator.transition import compute_action_cost

        cost = compute_action_cost(action)
        if s.credits.exhausted and action.action_type != ActionType.SUBMIT_VALIDATION_REPORT:
            vs.append(RuleViolation(
                rule_id="credits_exhausted",
                severity=Severity.HARD,
                message="Credits exhausted - submit validation report or end episode",
            ))
        elif cost > s.credits.credits_remaining and cost > 0:
            vs.append(RuleViolation(
                rule_id="credits_insufficient",
                severity=Severity.HARD,
                message=(
                    f"Action costs {cost} credits but only "
                    f"{s.credits.credits_remaining} remain"
                ),
            ))
        return vs

    # ── submission validation ───────────────────────────────────────────

    def _check_submission(
        self,
        action: DrugTargetAction,
        s: FullLatentState,
        evidence_dimensions_covered: Iterable[str],
    ) -> List[RuleViolation]:
        vs: List[RuleViolation] = []
        if action.action_type != ActionType.SUBMIT_VALIDATION_REPORT:
            return vs

        # Hard: report with no evidence at all.
        if not list(evidence_dimensions_covered):
            vs.append(RuleViolation(
                rule_id="report_without_evidence",
                severity=Severity.HARD,
                message=(
                    "Cannot submit validation report without gathering "
                    "any evidence"
                ),
            ))

        # Hard: report missing decision or confidence.
        if action.final_decision is None:
            vs.append(RuleViolation(
                rule_id="report_missing_decision",
                severity=Severity.HARD,
                message=(
                    "Submitting validation report without a final_decision "
                    "is not allowed"
                ),
            ))
        elif action.final_decision.lower() not in {"go", "no_go"}:
            vs.append(RuleViolation(
                rule_id="report_invalid_decision",
                severity=Severity.HARD,
                message=(
                    f"final_decision must be 'go' or 'no_go', got "
                    f"{action.final_decision!r}"
                ),
            ))

        if action.confidence is None:
            vs.append(RuleViolation(
                rule_id="report_missing_confidence",
                severity=Severity.HARD,
                message=(
                    "Submitting validation report without a confidence "
                    "score is not allowed"
                ),
            ))
        elif action.confidence < 0.30:
            vs.append(RuleViolation(
                rule_id="report_low_confidence",
                severity=Severity.SOFT,
                message=(
                    f"Submitting with very low confidence "
                    f"({action.confidence:.2f}) β€” the agent appears "
                    f"poorly calibrated"
                ),
            ))

        return vs

    # ── redundancy checks ───────────────────────────────────────────────

    def _check_redundancy(
        self, action: DrugTargetAction, s: FullLatentState
    ) -> List[RuleViolation]:
        vs: List[RuleViolation] = []
        if action.action_type == ActionType.FLAG_RED_FLAG:
            return vs
        if action.action_type == ActionType.SUBMIT_VALIDATION_REPORT:
            if s.progress.report_submitted:
                vs.append(RuleViolation(
                    rule_id="duplicate_report",
                    severity=Severity.HARD,
                    message="Validation report has already been submitted",
                ))
            return vs
        count = s.action_call_counts.get(action.action_type.value, 0)
        if count >= 2:
            vs.append(RuleViolation(
                rule_id=f"redundant_{action.action_type.value}",
                severity=Severity.SOFT,
                message=(
                    f"Action '{action.action_type.value}' has already been "
                    f"executed {count} time(s); further repeats are "
                    f"redundant"
                ),
            ))
        return vs

    # ── ordering checks ─────────────────────────────────────────────────

    def _check_ordering(
        self, action: DrugTargetAction, s: FullLatentState
    ) -> List[RuleViolation]:
        vs: List[RuleViolation] = []
        p = s.progress

        if action.action_type == ActionType.IN_VIVO_MODEL and not p.in_vitro_done:
            vs.append(RuleViolation(
                rule_id="in_vivo_before_in_vitro",
                severity=Severity.SOFT,
                message=(
                    "Running in_vivo_model before in_vitro_assay is "
                    "scientifically backwards"
                ),
            ))
        if (
            action.action_type == ActionType.TOXICITY_PANEL
            and not p.expression_queried
        ):
            vs.append(RuleViolation(
                rule_id="toxicity_before_expression",
                severity=Severity.SOFT,
                message=(
                    "Toxicity panel before any expression query β€” "
                    "tissue-specific toxicity will be hard to interpret"
                ),
            ))
        return vs