scripts-historical-judge

#!/usr/bin/env python3 """Historical Judge - Compares against historical classification patterns."""

from typing import Optional from .base import BaseJudge, JudgeDecision

class HistoricalJudge(BaseJudge): """Compares against historical classifications of similar documents."""

name = "historical"
has_veto_authority = False
weight = 0.7

def __init__(self, learner=None):
    super().__init__()
    self.learner = learner

def evaluate(self, document, votes, consensus) -> JudgeDecision:
    if not self.learner:
        return JudgeDecision(
            judge=self.name,
            approved=True,
            reason="No learning system available",
            confidence=0.5,
            metadata={'no_learner': True}
        )

    doc_path = str(getattr(document, 'path', ''))
    classification = consensus.classification if consensus.classification else ""

    try:
        similar = self.learner.find_similar_by_path(doc_path, limit=5)

        if similar:
            # Check if similar documents have different types
            type_counts = {}
            for doc in similar:
                actual = doc.get('actual_type')
                if actual:
                    type_counts[actual] = type_counts.get(actual, 0) + 1

            if type_counts:
                most_common = max(type_counts, key=type_counts.get)
                if most_common != classification:
                    return JudgeDecision(
                        judge=self.name,
                        approved=False,
                        reason=f"Similar documents classified as '{most_common}' not '{classification}'",
                        confidence=0.6,
                        metadata={'historical_type': most_common, 'current': classification, 'count': type_counts[most_common]}
                    )

                return JudgeDecision(
                    judge=self.name,
                    approved=True,
                    reason=f"Consistent with historical pattern ({most_common})",
                    confidence=0.75,
                    metadata={'matches': type_counts}
                )

    except Exception as e:
        return JudgeDecision(
            judge=self.name,
            approved=True,
            reason=f"Historical check failed: {e}",
            confidence=0.5,
            metadata={'error': str(e)}
        )

    return JudgeDecision(
        judge=self.name,
        approved=True,
        reason="No conflicting historical patterns",
        confidence=0.6,
        metadata={'no_conflicts': True}
    )