M8：天工阁、叩心与辰正——受托任务后台并行、叩心四约束、时态感知投影
- 天工阁域 domains/tiangong：backstage_tasks（委托包+验收标准+结果证据）；有限分解（parent 链）与受控并行（各自后台 Run）；子任务全终态级联父任务进入待验收；按证据 accept/reject - kernel.start_backstage_run（kind=background_task）：loop 后台分支不占前台席位、与前台对话并行；断言放宽容纳无人物功能任务；结果只经回调回呈任务——无身份写入路径 - 叩心域 domains/kouxin：knocking_candidates（event/time_anchor/manual 触发 + 草稿 + 裁决快照）；四约束裁决（总开关→静默窗口【本地时区判定】→24h 频率→预算），dispatch 未过 429 且快照留痕；候选默认不自动发送；expire_stale 过期推进不触碰缘契 - 辰正 domains/zhengchen：temporal_context() 复用 time_sense 计算核（快照/农历/季节），产出【时态感知】投影段接入镜树生成 prompt（客观时间语境，不附情绪臆测——守一纪律） - 退役：modules/goal_orchestrator|planner|perception|big_cycle、application/planning、services/governance|goal_persist、candidates 表链（imports 候选抽取 API 面）、goals/plans/agent_roster/perception_channels/big_cycles/旧候选表（迁移 009）；前端 admin goals/plans/agents/perception/world 页与六组件；governance 只留 GenerationPreferences；admin 治理面收敛为司命+百工两枢；pivots 健康以域表计数重建 - 验收（test_m8_tiangong 五用例）：后台任务无身份写入（记忆/魂籍/缘契零新增）；后台与前台并行；分解级联；叩心四约束逐项；不回应不降低关系（缘契维度/状态/版本零变化） - 四套件：后端 345、前端 203、BFF 4、神识 5 包全绿（2 个预存环境失败不变）；迁移 009 净库干净
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@@ -16,15 +16,8 @@ from app.core.time import utc_now
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from app.db.session import AsyncSessionLocal
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from app.models.imports import CharacterImportJob, ImportItem
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from app.modules.imports import parse_import
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from app.repositories import candidates as candidates_repo
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from app.repositories import imports as imports_repo
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from app.repositories.json_utils import dumps, loads_dict
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from app.schemas.candidates import (
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BatchReviewRequest,
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BatchReviewResult,
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MemoryCandidateResponse,
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ProfileCandidateResponse,
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)
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from app.schemas.common import Page
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from app.schemas.imports import (
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CreateImportRequest,
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@@ -36,8 +29,6 @@ from app.services.characters import get_owned_character
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from app.services.serializers import (
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import_item_to_response,
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import_job_to_response,
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memory_candidate_to_response,
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profile_candidate_to_response,
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)
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_TEXT_MIME_FORMAT: dict[str, str] = {
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@@ -283,24 +274,6 @@ async def _reload_job(import_id: str) -> ImportJobResponse:
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return import_job_to_response(job)
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async def trigger_profile_extraction(
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character_id: str,
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import_id: str,
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owner_scope: str = settings.default_owner_scope,
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) -> ImportJobResponse:
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return await _trigger_extraction(
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character_id, import_id, "extracting_profile", "profile", owner_scope=owner_scope
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)
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async def trigger_memory_extraction(
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character_id: str,
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import_id: str,
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owner_scope: str = settings.default_owner_scope,
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) -> ImportJobResponse:
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return await _trigger_extraction(
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character_id, import_id, "extracting_memory", "memory", owner_scope=owner_scope
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)
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async def trigger_personality_extraction(
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@@ -317,148 +290,7 @@ async def trigger_personality_extraction(
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)
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async def _trigger_extraction(
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character_id: str,
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import_id: str,
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status: str,
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kind: str,
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owner_scope: str = settings.default_owner_scope,
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) -> ImportJobResponse:
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"""抽取触发已随旧管线退役：记忆候选由息壤归真管线生成（M3），画像/人格抽取随 M6。"""
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raise AppError(
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"not_implemented",
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"该抽取入口已退役：记忆候选经镜树归真生成（息壤 M3）；画像/人格抽取随 M6 灵核重建。",
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status_code=410,
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)
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async def list_profile_candidates(
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character_id: str,
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import_id: str,
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*,
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status: str | None = None,
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owner_scope: str = settings.default_owner_scope,
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) -> list[ProfileCandidateResponse]:
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async with AsyncSessionLocal() as session:
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character = await get_owned_character(session, character_id, owner_scope=owner_scope)
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await _get_owned_job(session, character.id, import_id)
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items = await candidates_repo.list_profile_candidates(
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session, character.id, import_job_id=import_id, status=status
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)
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return [profile_candidate_to_response(c) for c in items]
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async def list_memory_candidates(
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character_id: str,
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import_id: str,
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*,
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status: str | None = None,
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owner_scope: str = settings.default_owner_scope,
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) -> list[MemoryCandidateResponse]:
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async with AsyncSessionLocal() as session:
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character = await get_owned_character(session, character_id, owner_scope=owner_scope)
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await _get_owned_job(session, character.id, import_id)
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items = await candidates_repo.list_memory_candidates(
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session, character.id, import_job_id=import_id, status=status
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)
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return [memory_candidate_to_response(c) for c in items]
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# —— 候选审核应用（5c）——
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async def batch_review_profile_candidates(
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character_id: str,
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payload: BatchReviewRequest,
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owner_scope: str = settings.default_owner_scope,
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) -> BatchReviewResult:
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"""批量审核档案候选：approve 写入人物档案，reject 标记驳回，非 pending 跳过。"""
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async with AsyncSessionLocal() as session:
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character = await get_owned_character(session, character_id, owner_scope=owner_scope)
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profile = loads_dict(character.profile_json)
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applied = rejected = skipped = 0
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for decision in payload.decisions:
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candidate = await candidates_repo.get_profile_candidate(session, decision.candidate_id)
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if (
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candidate is None
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or candidate.character_id != character.id
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or candidate.status != "pending"
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):
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skipped += 1
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continue
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if decision.decision == "approve":
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profile[candidate.field] = candidate.value
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if candidate.field == "display_name":
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character.display_name = candidate.value
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candidate.status = "applied"
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applied += 1
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elif decision.decision == "reject":
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candidate.status = "rejected"
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rejected += 1
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else:
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skipped += 1
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continue
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candidate.reviewed_at = utc_now()
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character.profile_json = dumps(profile)
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await _audit(
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session,
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character.id,
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"import.profile_candidate_reviewed",
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character.id,
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f"applied={applied} rejected={rejected}",
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)
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await session.commit()
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return BatchReviewResult(applied=applied, rejected=rejected, skipped=skipped)
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async def batch_review_memory_candidates(
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character_id: str,
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payload: BatchReviewRequest,
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owner_scope: str = settings.default_owner_scope,
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) -> BatchReviewResult:
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"""批量审核记忆候选：approve 创建记忆，reject 标记驳回。"""
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async with AsyncSessionLocal() as session:
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character = await get_owned_character(session, character_id, owner_scope=owner_scope)
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applied = rejected = skipped = 0
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for decision in payload.decisions:
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candidate = await candidates_repo.get_memory_candidate(session, decision.candidate_id)
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if (
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candidate is None
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or candidate.character_id != character.id
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or candidate.status != "pending"
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):
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skipped += 1
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continue
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if decision.decision == "approve":
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session.add(
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Memory(
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character_id=character.id,
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type=candidate.type,
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title=candidate.title,
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content=candidate.content,
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source="user_explicit",
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confidence=candidate.confidence,
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importance=candidate.importance,
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sensitivity=candidate.sensitivity,
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evidence_ids_json=candidate.evidence_ids_json,
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status="active",
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)
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)
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candidate.status = "applied"
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applied += 1
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elif decision.decision == "reject":
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candidate.status = "rejected"
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rejected += 1
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else:
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skipped += 1
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continue
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candidate.reviewed_at = utc_now()
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await _audit(
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session,
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character.id,
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"import.memory_candidate_reviewed",
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character.id,
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f"applied={applied} rejected={rejected}",
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)
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await session.commit()
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return BatchReviewResult(applied=applied, rejected=rejected, skipped=skipped)
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