feat(governance): 新增 owner approved learning dry run
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@@ -70,6 +70,9 @@ from src.services.ai_agent_learning_writeback_approval_package import (
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from src.services.ai_agent_live_read_model_gate import (
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load_latest_ai_agent_live_read_model_gate,
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)
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from src.services.ai_agent_owner_approved_learning_dry_run import (
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load_latest_ai_agent_owner_approved_learning_dry_run,
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)
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from src.services.ai_agent_proactive_operations_contract import (
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load_latest_ai_agent_proactive_operations_contract,
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)
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@@ -723,6 +726,34 @@ async def get_agent_telegram_receipt_approval_package() -> dict[str, Any]:
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) from exc
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@router.get(
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"/agent-owner-approved-learning-dry-run",
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response_model=dict[str, Any],
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summary="取得 AI Agent owner-approved learning dry-run contract",
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description=(
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"讀取最新已提交的 owner-approved learning writeback dry-run 契約;"
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"此端點只回傳 dry-run preview、人工操作選項、驗證與 rollback 契約,"
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"不寫 KM、不更新 PlayBook trust、不寫 timeline、不寫 replay score、不發 Telegram、"
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"不啟動 runtime worker、不回傳未脫敏 payload。"
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),
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)
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async def get_agent_owner_approved_learning_dry_run() -> dict[str, Any]:
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"""Return the latest read-only AI Agent owner-approved learning dry-run contract."""
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try:
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return await asyncio.to_thread(load_latest_ai_agent_owner_approved_learning_dry_run)
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except FileNotFoundError as exc:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail=str(exc),
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) from exc
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except (json.JSONDecodeError, ValueError) as exc:
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logger.error("ai_agent_owner_approved_learning_dry_run_invalid", error=str(exc))
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail="AI Agent owner-approved learning dry-run 無效",
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) from exc
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@router.get(
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"/agent-proactive-operations-contract",
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response_model=dict[str, Any],
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@@ -0,0 +1,159 @@
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"""
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AI Agent owner-approved learning dry-run snapshot.
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Loads the latest committed P2-403F dry-run contract for owner-approved
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learning writeback previews. This module never writes KM, updates PlayBook
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trust, writes timeline learning, sends Telegram messages, or starts workers.
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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from typing import Any
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from src.services.snapshot_paths import default_evaluations_dir
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_DEFAULT_EVALUATIONS_DIR = default_evaluations_dir(Path(__file__))
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_SNAPSHOT_PATTERN = "ai_agent_owner_approved_learning_dry_run_*.json"
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_SCHEMA_VERSION = "ai_agent_owner_approved_learning_dry_run_v1"
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def load_latest_ai_agent_owner_approved_learning_dry_run(
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evaluations_dir: Path | None = None,
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) -> dict[str, Any]:
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"""Load the newest committed AI Agent owner-approved learning dry-run contract."""
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directory = evaluations_dir or _DEFAULT_EVALUATIONS_DIR
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candidates = sorted(directory.glob(_SNAPSHOT_PATTERN))
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if not candidates:
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raise FileNotFoundError(
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f"no AI Agent owner-approved learning dry-run snapshots found in {directory}"
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)
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latest = candidates[-1]
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with latest.open(encoding="utf-8") as handle:
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payload = json.load(handle)
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if not isinstance(payload, dict):
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raise ValueError(f"{latest}: expected JSON object")
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_require_schema(payload, str(latest))
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_require_read_only_boundaries(payload, str(latest))
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_require_preview_safety(payload, str(latest))
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_require_rollup_consistency(payload, str(latest))
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return payload
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def _require_schema(payload: dict[str, Any], label: str) -> None:
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actual = payload.get("schema_version")
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if actual != _SCHEMA_VERSION:
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raise ValueError(f"{label}: expected schema_version={_SCHEMA_VERSION}, got {actual!r}")
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status = payload.get("program_status") or {}
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if status.get("read_only_mode") is not True:
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raise ValueError(f"{label}: program_status.read_only_mode must be true")
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if status.get("runtime_authority") != "owner_approved_dry_run_only_no_learning_write":
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raise ValueError(f"{label}: runtime_authority must stay owner_approved_dry_run_only_no_learning_write")
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def _require_read_only_boundaries(payload: dict[str, Any], label: str) -> None:
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boundaries = payload.get("approval_boundaries") or {}
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enabled = sorted(key for key, value in boundaries.items() if value is not False)
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if enabled:
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raise ValueError(f"{label}: approval boundaries must remain false: {enabled}")
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truth = payload.get("dry_run_truth") or {}
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if truth.get("owner_approval_required") is not True:
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raise ValueError(f"{label}: owner approval must remain required")
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if truth.get("dry_run_preview_allowed") is not True:
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raise ValueError(f"{label}: dry-run preview contract must remain allowed")
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false_flags = {
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"km_write_allowed",
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"playbook_trust_write_allowed",
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"timeline_learning_write_allowed",
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"agent_replay_score_write_allowed",
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"telegram_send_allowed",
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"runtime_worker_allowed",
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}
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unsafe = sorted(flag for flag in false_flags if truth.get(flag) is not False)
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if unsafe:
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raise ValueError(f"{label}: learning write flags must remain false: {unsafe}")
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zero_counts = {
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"owner_approval_received_count",
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"dry_run_preview_generated_count",
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}
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non_zero = sorted(key for key in zero_counts if truth.get(key) != 0)
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if non_zero:
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raise ValueError(f"{label}: owner approval and dry-run generated counts must remain zero: {non_zero}")
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def _require_preview_safety(payload: dict[str, Any], label: str) -> None:
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preview = payload.get("dry_run_preview") or {}
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required_inputs = set(preview.get("required_inputs") or [])
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required_minimum = {
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"owner_approval_id",
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"incident_id",
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"redacted_evidence_refs",
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"target_learning_surface",
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"rollback_plan_ref",
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"verification_plan_ref",
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}
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missing = sorted(required_minimum - required_inputs)
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if missing:
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raise ValueError(f"{label}: dry-run preview missing required inputs: {missing}")
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if not preview.get("preview_outputs"):
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raise ValueError(f"{label}: dry-run preview outputs must not be empty")
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actions = payload.get("operator_actions") or []
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action_types = {action.get("action_type") for action in actions}
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required_actions = {"review", "collect_evidence", "approve_dry_run", "reject_or_rework"}
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if not required_actions.issubset(action_types):
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raise ValueError(f"{label}: operator actions must cover {sorted(required_actions)}")
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verification = payload.get("verification_contract") or {}
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if verification.get("verification_required") is not True:
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raise ValueError(f"{label}: verification must be required")
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if verification.get("rollback_required") is not True:
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raise ValueError(f"{label}: rollback must be required")
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if not verification.get("verification_steps"):
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raise ValueError(f"{label}: verification steps must not be empty")
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redaction = payload.get("display_redaction_contract") or {}
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if redaction.get("redaction_required") is not True:
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raise ValueError(f"{label}: frontend redaction must be required")
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for flag in ("raw_payload_display_allowed", "private_reasoning_display_allowed", "secret_value_display_allowed"):
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if redaction.get(flag) is not False:
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raise ValueError(f"{label}: {flag} must remain false")
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def _require_rollup_consistency(payload: dict[str, Any], label: str) -> None:
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rollups = payload.get("rollups") or {}
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actions = payload.get("operator_actions") or []
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gates = payload.get("dry_run_gates") or []
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preview = payload.get("dry_run_preview") or {}
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truth = payload.get("dry_run_truth") or {}
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expected_counts = {
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"operator_action_count": len(actions),
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"dry_run_gate_count": len(gates),
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"blocked_write_action_count": len({gate.get("blocked_write_action") for gate in gates}),
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"required_input_count": len(preview.get("required_inputs") or []),
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"forbidden_input_count": len(preview.get("forbidden_inputs") or []),
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"preview_output_count": len(preview.get("preview_outputs") or []),
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}
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mismatched = {
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key: {"expected": expected, "actual": rollups.get(key)}
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for key, expected in expected_counts.items()
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if rollups.get(key) != expected
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}
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if mismatched:
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raise ValueError(f"{label}: rollup counts must match payload sections: {mismatched}")
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approval_required = sorted(
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gate.get("gate_id") for gate in gates if gate.get("status") == "approval_required"
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)
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if sorted(rollups.get("approval_required_gate_ids") or []) != approval_required:
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raise ValueError(f"{label}: rollups.approval_required_gate_ids mismatch")
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if rollups.get("live_write_count_total") != 0:
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raise ValueError(f"{label}: live write count must remain zero")
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if rollups.get("dry_run_preview_generated_count") != truth.get("dry_run_preview_generated_count"):
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raise ValueError(f"{label}: dry_run_preview_generated_count mismatch")
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