xiaoxia-saas/packages/adapters/sqlalchemy_impl/asset_atom_clip_repository.py

"""素材原子片段仓储 SQLAlchemy 实现。"""

from __future__ import annotations

from datetime import UTC, datetime

from sqlalchemy.orm import Session

from packages.adapters.sqlalchemy_impl.models import AssetAtomClipModel
from packages.domain.asset_atom_clip import AssetAtomClip


class SQLAlchemyAssetAtomClipRepository:
    def __init__(self, session: Session):
        self.session = session

    def create(self, clip: AssetAtomClip) -> AssetAtomClip:
        model = self._to_model(clip)
        self.session.add(model)
        self.session.flush()
        self.session.commit()
        return clip

    def batch_create(self, clips: list[AssetAtomClip]) -> list[AssetAtomClip]:
        if not clips:
            return []
        models = [self._to_model(c) for c in clips]
        self.session.add_all(models)
        self.session.flush()
        self.session.commit()
        return clips

    def find_by_asset(self, asset_id: str) -> list[AssetAtomClip]:
        models = (
            self.session.query(AssetAtomClipModel)
            .filter(AssetAtomClipModel.asset_id == asset_id)
            .order_by(AssetAtomClipModel.clip_index.asc())
            .all()
        )
        return [self._to_domain(m) for m in models]

    def find_by_id(self, clip_id: str) -> AssetAtomClip | None:
        model = self.session.query(AssetAtomClipModel).filter(AssetAtomClipModel.id == clip_id).first()
        if model is None:
            return None
        return self._to_domain(model)

    def find_by_ids(self, clip_ids: list[str]) -> list[AssetAtomClip]:
        if not clip_ids:
            return []
        models = self.session.query(AssetAtomClipModel).filter(AssetAtomClipModel.id.in_(clip_ids)).all()
        return [self._to_domain(m) for m in models]

    def delete_by_asset(self, asset_id: str) -> int:
        count = (
            self.session.query(AssetAtomClipModel)
            .filter(AssetAtomClipModel.asset_id == asset_id)
            .delete(synchronize_session=False)
        )
        self.session.commit()
        return count

    def count_by_asset(self, asset_id: str) -> int:
        return self.session.query(AssetAtomClipModel).filter(AssetAtomClipModel.asset_id == asset_id).count()

    def find_candidates_for_selection(
        self,
        asset_ids: list[str],
        *,
        min_duration: float | None = None,
        max_duration: float | None = None,
        limit: int = 100,
    ) -> list[AssetAtomClip]:
        """按筛选条件查找候选原子片段，按时长排序。用于选片逻辑。"""
        query = self.session.query(AssetAtomClipModel).filter(AssetAtomClipModel.asset_id.in_(asset_ids))
        if min_duration is not None:
            query = query.filter(AssetAtomClipModel.duration >= min_duration)
        if max_duration is not None:
            query = query.filter(AssetAtomClipModel.duration <= max_duration)
        query = query.order_by(AssetAtomClipModel.clip_index.asc())
        if limit > 0:
            query = query.limit(limit)
        models = query.all()
        return [self._to_domain(m) for m in models]

    def update_caption_embedding(self, clip_id: str, caption: str | None, embedding: list[float] | None = None) -> bool:
        """更新片段的 caption 和 embedding 字段。"""
        upd: dict = {}
        if caption is not None:
            upd["caption"] = caption
        if embedding is not None:
            upd["embedding"] = embedding
        if not upd:
            return False
        count = self.session.query(AssetAtomClipModel).filter(AssetAtomClipModel.id == clip_id).update(upd)
        self.session.commit()
        return count > 0

    def update_ai_tags(self, clip_id: str, ai_tags: dict) -> bool:
        """更新指定片段的 ai_tags 字段."""
        count = (
            self.session.query(AssetAtomClipModel).filter(AssetAtomClipModel.id == clip_id).update({"ai_tags": ai_tags})
        )
        self.session.commit()
        return count > 0

    def find_untagged(self, limit: int = 100, include_downgraded: bool = False) -> list[AssetAtomClip]:
        """查找未完成 AI 打标的片段，用于回填.

        默认仅匹配 ai_tags IS NULL；include_downgraded=True 时额外包含
        只有 inherited_tags 的降级记录（视觉 API 失败时写入，无 has_text 字段），
        供强制回填（#1970 force backfill）使用。
        """
        query = self.session.query(AssetAtomClipModel)
        if include_downgraded:
            # as_string() → JSON/JSONB ->> 取值；NULL 记录或缺 has_text 键
            # （降级记录）均为 NULL，has_text 为 true/false 的完整记录被排除
            query = query.filter(AssetAtomClipModel.ai_tags["has_text"].as_string().is_(None))
        else:
            query = query.filter(AssetAtomClipModel.ai_tags.is_(None))
        models = query.order_by(AssetAtomClipModel.created_at.asc()).limit(limit).all()
        return [self._to_domain(m) for m in models]

    def _to_model(self, clip: AssetAtomClip) -> AssetAtomClipModel:
        return AssetAtomClipModel(
            id=clip.id,
            asset_id=clip.asset_id,
            start_time=clip.start_time,
            end_time=clip.end_time,
            duration=clip.duration,
            clip_index=clip.clip_index,
            tags=clip.tags,
            ai_tags=clip.ai_tags,
            caption=clip.caption,
            embedding=clip.embedding,
            scene_change_at=clip.scene_change_at,
            is_fallback=clip.is_fallback,
            created_at=clip.created_at or datetime.now(UTC),
        )

    def _to_domain(self, model: AssetAtomClipModel) -> AssetAtomClip:
        return AssetAtomClip(
            id=model.id,
            asset_id=model.asset_id,
            start_time=model.start_time,
            end_time=model.end_time,
            duration=model.duration,
            clip_index=model.clip_index,
            tags=model.tags or [],
            ai_tags=getattr(model, "ai_tags", None),
            caption=getattr(model, "caption", None),
            embedding=getattr(model, "embedding", None),
            scene_change_at=model.scene_change_at,
            is_fallback=model.is_fallback,
            created_at=model.created_at,
        )