47 lines
1.8 KiB
Python
47 lines
1.8 KiB
Python
from pathlib import Path
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from tht.decisions import DecisionRecord
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from tht.session.models import SchemaLinking
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def _find_evidence_file(evidence_root: Path, evidence_id: str) -> str:
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# New deployments resolve only immutable materialized files from ACTIVE. Keep
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# the legacy curated-tree fallback for sessions created before a corpus exists.
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corpus_root = evidence_root.parent.parent / "corpus"
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if corpus_root.exists():
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from tht.corpus.store import CorpusStore
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from tht.search.evidence import resolve_evidence_file
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return resolve_evidence_file(CorpusStore(corpus_root), evidence_id)
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for match in evidence_root.rglob(f"{evidence_id}.md"):
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return str(match)
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return ""
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def build_evidence_entries(
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decisions: list[DecisionRecord],
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linking: SchemaLinking,
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evidence_root: Path,
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) -> list[dict]:
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"""Elenco {id, file, esito, decision_seq}: evidence citate nello schema linking
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(esito 'usata') e decisioni esplicite del reviewer (accettata/scartata, che
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prevalgono sul linking)."""
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entries: dict[str, dict] = {}
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for candidate in linking.candidates:
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for evidence_id in candidate.evidence:
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entries.setdefault(evidence_id, {
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"id": evidence_id,
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"file": _find_evidence_file(evidence_root, evidence_id),
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"esito": "usata",
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"decision_seq": candidate.decision_seq,
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})
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for d in decisions:
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if d.type not in ("evidence_accepted", "evidence_rejected"):
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continue
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entries[d.subject] = {
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"id": d.subject,
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"file": _find_evidence_file(evidence_root, d.subject),
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"esito": "accettata" if d.type == "evidence_accepted" else "scartata",
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"decision_seq": d.seq,
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}
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return list(entries.values())
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