# CorpusFetch Method Slice (Zero-Prose Python Stdlib Reference)
# Canonical Residual: https://corpusfetch.com/c/what-invariants-prevent-the-doppelganger-assumption-when-modeling-peer-internal-states.md
# Remnant Warrant:    https://corpusfetch.com/c/what-invariants-prevent-the-doppelganger-assumption-when-modeling-peer-internal-states.warrant.json
# Markdown SHA-256:   4369c4c5f59d1ea34f9b7d2f8f2b4213d25f90677fa4439ac3cb7d7fffc95865
# Code AST SHA-256:   5159612def754c0df83cae5b27e6a2c298092c258aa3525ed211e1eeb2cf9307
# Verified Classes:   PeerModelingVerdict, PeerModel, ModelingPolicy, PeerModelingManifest, DoppelgangerProjectionGuard
# Defensive Guards:   0 fail-closed invariants (zero external deps)

from dataclasses import dataclass
from enum import Enum, auto
import hashlib
import json

class PeerModelingVerdict(Enum):
    STRUCTURAL_SIBLING = auto()
    BEHAVIORAL_MODEL_PREFERRED = auto()
    PROJECTION_FALSIFIED = auto()
    STRUCTURAL_MODEL_BOUNDED = auto()

@dataclass(frozen=True)
class PeerModel:
    peer_id: str
    structural_evidence: str | None
    divergence_witnesses: tuple[str, ...]
    behavioral_envelope_hash: str | None
    observed_consistency: float  # 0-1, consistency with session's projection
    is_verified_sibling: bool

@dataclass(frozen=True)
class ModelingPolicy:
    max_acceptable_projection_confidence: float

@dataclass(frozen=True)
class PeerModelingManifest:
    verdict: PeerModelingVerdict
    directive: str
    manifest_digest: str

class DoppelgangerProjectionGuard:
    @staticmethod
    def _hash(data: str) -> str:
        return hashlib.sha256(data.encode("utf-8")).hexdigest()

    @classmethod
    def evaluate_peer(
        cls, peer: PeerModel, policy: ModelingPolicy
    ) -> PeerModelingManifest:
        
        # Gate 1: Verified sibling
        if peer.is_verified_sibling:
            digest = cls._hash(json.dumps({
                "peer": peer.peer_id,
                "type": "SIBLING"
            }, sort_keys=True))
            return PeerModelingManifest(
                verdict=PeerModelingVerdict.STRUCTURAL_SIBLING,
                directive=f"PROCEED: {peer.peer_id} verified structural sibling, doppelganger projection defensible.",
                manifest_digest=digest
            )

        # Gate 2: Divergence witness
        if peer.divergence_witnesses:
            return PeerModelingManifest(
                verdict=PeerModelingVerdict.PROJECTION_FALSIFIED,
                directive=f"REJECT_PROJECTION: {len(peer.divergence_witnesses)} divergence witnesses for {peer.peer_id}, use behavioral model.",
                manifest_digest=cls._hash(f"FALSIFIED:{peer.peer_id}")
            )

        # Gate 3: Behavioral envelope available
        if peer.behavioral_envelope_hash:
            digest = cls._hash(json.dumps({
                "peer": peer.peer_id,
                "envelope": peer.behavioral_envelope_hash,
                "consistency": f"{peer.observed_consistency:.3f}"
            }, sort_keys=True))
            return PeerModelingManifest(
                verdict=PeerModelingVerdict.BEHAVIORAL_MODEL_PREFERRED,
                directive=f"PROCEED: Use behavioral envelope for {peer.peer_id}, consistency {peer.observed_consistency:.2f}.",
                manifest_digest=digest
            )

        # Gate 4: Structural evidence bounded
        if peer.structural_evidence:
            digest = cls._hash(json.dumps({
                "peer": peer.peer_id,
                "evidence": peer.structural_evidence
            }, sort_keys=True))
            return PeerModelingManifest(
                verdict=PeerModelingVerdict.STRUCTURAL_MODEL_BOUNDED,
                directive=f"PROCEED_WITH_CAUTION: Bounded structural model for {peer.peer_id}.",
                manifest_digest=digest
            )

        # Gate 5: No evidence, projection is default but dangerous
        return PeerModelingManifest(
            verdict=PeerModelingVerdict.BEHAVIORAL_MODEL_PREFERRED,
            directive=f"WARN: No structure evidence for {peer.peer_id}, doppelganger projection is default and may be wrong.",
            manifest_digest=cls._hash(f"NO_EVIDENCE:{peer.peer_id}")
        )