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https://github.com/Strategic-Automation/violin.git
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refactor(guard): decompose handle_review_batch into skill reservation and core execution helpers
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Violin
@@ -375,10 +375,124 @@ def handle_record_ptt(a, **kwargs):
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)
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def _handle_review_batch_skill_reservation(
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engagement: Path, pending: dict, a: dict, skill: str
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) -> tuple[dict, str | None]:
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"""Handle skill reservation and review readiness for batch reviews.
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Returns (updated_a, early_response_json_or_None).
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"""
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tasks = ptt.parse_ptt(engagement / "state" / "ptt.md")
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task_id = str(a.get("id") or "").strip()
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task = next((item for item in tasks if item.id == task_id), None)
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if task is None:
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raise ValueError(f"batch task {task_id!r} is missing from the PTT")
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hypothesis_id = str(a.get("hypothesis_id") or "").strip()
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phase = ptt.normalize_phase(task.phase)
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if requires_hypothesis(phase) and not hypothesis_id:
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raise ValueError(f"hypothesis_id is required for {phase.value} batch review")
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digest = "sha256:" + hashlib.sha256(f"policy:{skill}".encode()).hexdigest()
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reservation = prepare_delivery(
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engagement,
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session_id=state.resolve_session_id(engagement) or "review",
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skill=skill,
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bundle_digest=digest,
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phase="RETROSPECTIVE" if skill == "fp-check" else phase.value,
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)
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if reservation.owner:
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adapter_cls = _get_skill_view_adapter()
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viewed = adapter_cls().view(skill, task_id=task_id)
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completed = complete_delivery(engagement, reservation, viewed)
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return a, _json(
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"skill_prepared" if completed.status == "delivered" else "skill_unavailable",
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transition_applied=False,
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released=False,
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skill={
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"name": skill,
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"digest": digest,
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"content": viewed.content,
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"error": viewed.error,
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"delivery_id": reservation.id,
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},
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)
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if reservation.status == "preparing":
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return a, _json("skill_preparing", transition_applied=False, released=False)
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if skill == "fp-check" and a.get("finding"):
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finding_id = str((a.get("finding") or {}).get("finding_id") or "").upper()
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evidence = findings._batch_evidence(engagement, pending)
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evidence_digest = (
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"sha256:" + hashlib.sha256("\n".join(sorted(evidence)).encode()).hexdigest()
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)
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prepare_review_readiness(
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engagement,
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finding_id=finding_id,
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evidence_digest=evidence_digest,
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delivery_id=reservation.id,
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)
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return a, _json(
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"review_prepared",
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transition_applied=False,
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released=False,
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finding_id=finding_id,
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)
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updated_a = {**a, "note": _with_skill_token(str(a.get("note") or ""), skill, digest)}
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return updated_a, None
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def _execute_batch_review(engagement: Path, pending: dict, a: dict, skill: str) -> str:
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"""Validate and execute the core batch review transition."""
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context = _validate_review_batch(a, pending)
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finding_result = None
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finding = context["finding"]
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if finding is not None:
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finding_result = findings._create_from_pending_batch(
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engagement,
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pending=pending,
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title=str(finding.get("title") or ""),
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severity=str(finding.get("severity") or ""),
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description=str(finding.get("description") or ""),
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impact=str(finding.get("impact") or ""),
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remediation=str(finding.get("remediation") or ""),
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finding_id=str(finding.get("finding_id") or ""),
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hypothesis_id=str(finding.get("hypothesis_id") or ""),
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)
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if not context["already_recorded"]:
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review_note = f"{context['note']} {context['marker']}"
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ptt.update_task(
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context["ptt_path"], context["task_id"], context["status"], review_note
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)
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batch_evidence = findings._batch_evidence(engagement, pending)
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supplied_evidence = [str(item) for item in (a.get("evidence_paths") or [])]
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evidence_paths = sorted(set(supplied_evidence) | set(batch_evidence))
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semantic = state.record_semantic_review(
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engagement,
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task_id=context["task_id"],
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hypothesis_id=str(a.get("hypothesis_id") or ""),
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skill=skill or "review",
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technique=str(a.get("technique") or "batch-review"),
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outcome=str(a.get("outcome") or "progress"),
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evidence_paths=evidence_paths,
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next_action=str(a.get("next_action") or "review evidence"),
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next_technique=str(a.get("next_technique") or ""),
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research_attempted=bool(a.get("research_attempted")),
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)
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state.clear_pending_sync(engagement)
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return _json(
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"ok",
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batch_id=context["batch_id"],
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task_id=context["task_id"],
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task_status=context["status"],
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released=True,
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finding=finding_result,
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finding_path=finding_result.get("path") if finding_result else None,
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binding_task_id=None,
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semantic_progress=semantic,
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)
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@_serialise_errors
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def handle_review_batch(a, **kwargs):
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"""Review one completed batch, optionally record a finding, and release its lock."""
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eng_dir = str(a.get("eng_dir") or "").strip()
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if not eng_dir:
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raise ValueError("eng_dir is required")
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@@ -400,109 +514,12 @@ def handle_review_batch(a, **kwargs):
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)
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skill = str(a.get("skill") or "").strip()
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if skill:
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tasks = ptt.parse_ptt(engagement / "state" / "ptt.md")
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task_id = str(a.get("id") or "").strip()
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task = next((item for item in tasks if item.id == task_id), None)
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if task is None:
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raise ValueError(f"batch task {task_id!r} is missing from the PTT")
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hypothesis_id = str(a.get("hypothesis_id") or "").strip()
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phase = ptt.normalize_phase(task.phase)
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if requires_hypothesis(phase) and not hypothesis_id:
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raise ValueError(f"hypothesis_id is required for {phase.value} batch review")
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digest = "sha256:" + hashlib.sha256(f"policy:{skill}".encode()).hexdigest()
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reservation = prepare_delivery(
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engagement,
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session_id=state.resolve_session_id(engagement) or "review",
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skill=skill,
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bundle_digest=digest,
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phase="RETROSPECTIVE" if skill == "fp-check" else phase.value,
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a, early_response = _handle_review_batch_skill_reservation(
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engagement, pending, a, skill
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)
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if reservation.owner:
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adapter_cls = _get_skill_view_adapter()
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viewed = adapter_cls().view(skill, task_id=task_id)
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completed = complete_delivery(engagement, reservation, viewed)
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return _json(
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"skill_prepared"
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if completed.status == "delivered"
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else "skill_unavailable",
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transition_applied=False,
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released=False,
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skill={
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"name": skill,
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"digest": digest,
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"content": viewed.content,
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"error": viewed.error,
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"delivery_id": reservation.id,
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},
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)
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if reservation.status == "preparing":
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return _json("skill_preparing", transition_applied=False, released=False)
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if skill == "fp-check" and a.get("finding"):
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finding_id = str((a.get("finding") or {}).get("finding_id") or "").upper()
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evidence = findings._batch_evidence(engagement, pending)
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evidence_digest = (
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"sha256:" + hashlib.sha256("\n".join(sorted(evidence)).encode()).hexdigest()
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)
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prepare_review_readiness(
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engagement,
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finding_id=finding_id,
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evidence_digest=evidence_digest,
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delivery_id=reservation.id,
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)
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return _json(
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"review_prepared",
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transition_applied=False,
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released=False,
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finding_id=finding_id,
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)
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a = {**a, "note": _with_skill_token(str(a.get("note") or ""), skill, digest)}
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context = _validate_review_batch(a, pending)
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finding_result = None
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finding = context["finding"]
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if finding is not None:
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finding_result = findings._create_from_pending_batch(
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engagement,
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pending=pending,
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title=str(finding.get("title") or ""),
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severity=str(finding.get("severity") or ""),
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description=str(finding.get("description") or ""),
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impact=str(finding.get("impact") or ""),
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remediation=str(finding.get("remediation") or ""),
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finding_id=str(finding.get("finding_id") or ""),
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hypothesis_id=str(finding.get("hypothesis_id") or ""),
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)
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if not context["already_recorded"]:
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review_note = f"{context['note']} {context['marker']}"
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ptt.update_task(
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context["ptt_path"], context["task_id"], context["status"], review_note
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)
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batch_evidence = findings._batch_evidence(engagement, pending)
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supplied_evidence = [str(item) for item in (a.get("evidence_paths") or [])]
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evidence_paths = sorted(set(supplied_evidence) | set(batch_evidence))
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semantic = state.record_semantic_review(
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engagement,
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task_id=context["task_id"],
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hypothesis_id=str(a.get("hypothesis_id") or ""),
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skill=skill or "review",
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technique=str(a.get("technique") or "batch-review"),
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outcome=str(a.get("outcome") or "progress"),
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evidence_paths=evidence_paths,
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next_action=str(a.get("next_action") or "review evidence"),
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next_technique=str(a.get("next_technique") or ""),
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research_attempted=bool(a.get("research_attempted")),
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)
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state.clear_pending_sync(engagement)
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return _json(
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"ok",
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batch_id=context["batch_id"],
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task_id=context["task_id"],
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task_status=context["status"],
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released=True,
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finding=finding_result,
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finding_path=finding_result.get("path") if finding_result else None,
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binding_task_id=None,
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semantic_progress=semantic,
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)
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if early_response is not None:
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return early_response
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return _execute_batch_review(engagement, pending, a, skill)
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except (OSError, ValueError) as exc:
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return _json(
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"blocked",
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