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- 新增 AutoClipService：自动为剪辑计划片段分配最佳素材 - 评分算法：质量分(0.5) + 时长匹配(0.3) + 分类匹配(0.2) - 支持按 file_type/quality_score/duration/classification/tags 筛选 - AssetRepository 新增 search_candidates() 方法（抽象+SQLAlchemy实现） - 18 个单元测试全部通过
211 lines
7.8 KiB
Python
211 lines
7.8 KiB
Python
import json
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from datetime import datetime, timezone
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from sqlalchemy.orm import Session
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from packages.adapters.sqlalchemy_impl.models import AssetModel
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from packages.domain import Asset, AssetStatus, ClassificationStatus
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class SQLAlchemyAssetRepository:
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def __init__(self, session: Session):
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self.session = session
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def find_by_library(
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self,
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library_id: str,
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skip: int = 0,
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limit: int = 100,
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) -> list[Asset]:
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models = (
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self.session.query(AssetModel)
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.filter(AssetModel.asset_library_id == library_id)
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.offset(skip)
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.limit(limit)
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.all()
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)
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return [self._to_domain(model) for model in models]
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def find_by_project(
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self,
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project_id: str,
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skip: int = 0,
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limit: int = 100,
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) -> list[Asset]:
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models = (
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self.session.query(AssetModel).filter(AssetModel.project_id == project_id).offset(skip).limit(limit).all()
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)
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return [self._to_domain(model) for model in models]
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def find_by_id(self, asset_id: str) -> Asset | None:
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model = self.session.query(AssetModel).filter(AssetModel.id == asset_id).first()
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if model is None:
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return None
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return self._to_domain(model)
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def get(self, asset_id: str) -> Asset | None:
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return self.find_by_id(asset_id)
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def create(self, asset: Asset) -> Asset:
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now = datetime.now(timezone.utc)
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model = AssetModel(
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id=asset.id,
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project_id=asset.project_id,
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asset_library_id=asset.library_id,
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name=asset.name,
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file_type=(asset.mime_type.split("/")[0] if "/" in asset.mime_type else asset.mime_type),
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file_size=asset.file_size,
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file_url=asset.storage_key,
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thumbnail_url=asset.thumbnail_url,
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duration=asset.duration,
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width=asset.width,
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height=asset.height,
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fps=asset.fps,
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codec=asset.codec,
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status=asset.status.value,
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classification_status=asset.classification_status.value,
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classification_result=(json.dumps(asset.metadata) if asset.metadata else None),
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quality_score=asset.quality_score,
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uploaded_by_user_id=asset.uploaded_by_user_id or "system",
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created_at=asset.created_at,
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updated_at=now,
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)
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self.session.add(model)
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self.session.commit()
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return asset
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def update(self, asset: Asset) -> Asset:
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model = self.session.query(AssetModel).filter(AssetModel.id == asset.id).first()
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if model is None:
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raise ValueError(f"Asset {asset.id} not found")
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model.name = asset.name
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model.file_size = asset.file_size
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model.file_url = asset.storage_key
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model.thumbnail_url = asset.thumbnail_url
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model.duration = asset.duration
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model.width = asset.width
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model.height = asset.height
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model.fps = asset.fps
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model.codec = asset.codec
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model.status = asset.status.value
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model.classification_status = asset.classification_status.value
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model.classification_result = json.dumps(asset.metadata) if asset.metadata else None
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model.quality_score = asset.quality_score
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model.uploaded_by_user_id = asset.uploaded_by_user_id or model.uploaded_by_user_id
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model.updated_at = datetime.now(timezone.utc)
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self.session.commit()
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return asset
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def delete(self, asset_id: str) -> bool:
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model = self.session.query(AssetModel).filter(AssetModel.id == asset_id).first()
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if model:
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self.session.delete(model)
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self.session.commit()
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return True
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return False
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def count_by_project(self, project_id: str) -> int:
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return self.session.query(AssetModel).filter(AssetModel.project_id == project_id).count()
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def count_by_project_ids(self, project_ids: list[str]) -> int:
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if not project_ids:
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return 0
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return self.session.query(AssetModel).filter(AssetModel.project_id.in_(project_ids)).count()
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def sum_storage_by_project_ids(self, project_ids: list[str]) -> int:
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if not project_ids:
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return 0
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from sqlalchemy import func
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result = (
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self.session.query(func.coalesce(func.sum(AssetModel.file_size), 0))
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.filter(AssetModel.project_id.in_(project_ids))
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.scalar()
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)
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return int(result or 0)
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def search_candidates(
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self,
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project_id: str,
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*,
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file_type: str | None = None,
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min_quality_score: float | None = None,
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min_duration: float | None = None,
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max_duration: float | None = None,
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classification_category: str | None = None,
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tags: list[str] | None = None,
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status: str | None = None,
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limit: int = 50,
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) -> list[Asset]:
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"""按筛选条件搜索候选素材，按质量分降序排列。"""
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query = self.session.query(AssetModel).filter(
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AssetModel.project_id == project_id,
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)
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if file_type is not None:
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query = query.filter(AssetModel.file_type == file_type)
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if min_quality_score is not None:
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query = query.filter(AssetModel.quality_score >= min_quality_score)
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if min_duration is not None:
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query = query.filter(AssetModel.duration >= min_duration)
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if max_duration is not None:
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query = query.filter(AssetModel.duration <= max_duration)
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if status is not None:
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query = query.filter(AssetModel.status == status)
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if classification_category is not None:
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# classification_result 是 JSON Text，用 LIKE 匹配 category 字段
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query = query.filter(
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AssetModel.classification_result.like(
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f'%"{classification_category}"%'
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)
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)
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query = query.order_by(AssetModel.quality_score.desc().nullslast())
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if limit > 0:
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query = query.limit(limit)
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models = query.all()
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candidates = [self._to_domain(m) for m in models]
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# 内存中过滤 tags（tags 存在 metadata 中）
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if tags:
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tag_set = set(tags)
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candidates = [
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a for a in candidates
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if tag_set.issubset(set(a.metadata.get("tags", [])))
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]
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return candidates
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def _to_domain(self, model: AssetModel) -> Asset:
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metadata = {}
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if model.classification_result:
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try:
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metadata = json.loads(model.classification_result)
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except Exception:
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metadata = {}
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mime_type = model.file_type
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if "/" not in mime_type:
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mime_type = {
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"video": "video/mp4",
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"audio": "audio/mpeg",
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"image": "image/jpeg",
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}.get(mime_type, mime_type)
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return Asset(
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id=model.id,
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project_id=model.project_id,
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library_id=model.asset_library_id,
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name=model.name,
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storage_key=model.file_url,
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mime_type=mime_type,
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file_size=int(model.file_size or 0),
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thumbnail_url=model.thumbnail_url,
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duration=model.duration,
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width=int(model.width) if model.width is not None else None,
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height=int(model.height) if model.height is not None else None,
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fps=model.fps,
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codec=model.codec,
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status=AssetStatus(model.status),
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classification_status=ClassificationStatus(model.classification_status),
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quality_score=model.quality_score,
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uploaded_by_user_id=model.uploaded_by_user_id,
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metadata=metadata,
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created_at=model.created_at,
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updated_at=model.updated_at,
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)
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