tegwick
11585e6968
Five concern checks: Redundancy (embedding/word overlap), Coverage (FCA gap analysis), Coherence (graph connectivity), Consistency (cycle detection), Granularity (Shannon entropy). Orchestrator runs all or selected checks, CLI `markitect infospace check` command added. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
103 lines
3.6 KiB
Python
103 lines
3.6 KiB
Python
"""
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Unified orchestrator for all five collection-level checks.
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"""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Dict, List, Optional
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from markitect.infospace.models import EntityMeta
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from markitect.prompts.dependencies.models import DependencyGraph
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from .redundancy import RedundancyReport, check_redundancy
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from .coverage import CoverageReport, check_coverage
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from .coherence import CoherenceReport, check_coherence
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from .consistency import ConsistencyReport, check_consistency
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from .granularity import GranularityReport, check_granularity
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@dataclass
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class CheckReport:
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"""Unified report from all five collection-level checks."""
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redundancy: Optional[RedundancyReport] = None
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coverage: Optional[CoverageReport] = None
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coherence: Optional[CoherenceReport] = None
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consistency: Optional[ConsistencyReport] = None
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granularity: Optional[GranularityReport] = None
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def to_dict(self) -> Dict[str, Any]:
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d: Dict[str, Any] = {}
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if self.redundancy:
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d["redundancy"] = self.redundancy.to_dict()
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if self.coverage:
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d["coverage"] = self.coverage.to_dict()
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if self.coherence:
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d["coherence"] = self.coherence.to_dict()
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if self.consistency:
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d["consistency"] = self.consistency.to_dict()
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if self.granularity:
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d["granularity"] = self.granularity.to_dict()
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return d
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def metrics(self) -> Dict[str, float]:
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"""Extract key metrics for viability checking."""
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m: Dict[str, float] = {}
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if self.redundancy:
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m["redundancy_ratio"] = self.redundancy.redundancy_ratio
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if self.coverage:
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m["coverage_ratio"] = self.coverage.coverage_ratio
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if self.coherence:
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m["coherence_components"] = float(self.coherence.connected_components)
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m["modularity"] = self.coherence.modularity
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if self.consistency:
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m["consistency_cycles"] = float(self.consistency.cycle_count)
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if self.granularity:
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m["granularity_entropy"] = self.granularity.domain_entropy
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return m
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def run_all_checks(
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entities: List[EntityMeta],
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embeddings: Optional[Dict[str, list[float]]] = None,
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graph: Optional[DependencyGraph] = None,
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extra_attributes: Optional[Dict[str, set[str]]] = None,
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checks: Optional[List[str]] = None,
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) -> CheckReport:
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"""Run all (or selected) collection-level checks.
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Args:
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entities: Entity metadata list.
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embeddings: Pre-computed embedding vectors for C1.
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graph: Entity relationship graph for C3 and C4.
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extra_attributes: Extra FCA attributes for C2.
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checks: List of check names to run. If ``None``, runs all five.
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Valid names: ``redundancy``, ``coverage``, ``coherence``,
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``consistency``, ``granularity``.
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Returns:
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:class:`CheckReport` with results from each check.
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"""
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run_all = checks is None
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check_set = set(checks) if checks else set()
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report = CheckReport()
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if run_all or "redundancy" in check_set:
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report.redundancy = check_redundancy(entities, embeddings=embeddings)
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if run_all or "coverage" in check_set:
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report.coverage = check_coverage(entities, extra_attributes=extra_attributes)
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if run_all or "coherence" in check_set:
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report.coherence = check_coherence(graph=graph, entity_count=len(entities))
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if run_all or "consistency" in check_set:
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report.consistency = check_consistency(entities, graph=graph)
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if run_all or "granularity" in check_set:
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report.granularity = check_granularity(entities)
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return report
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