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341 lines
12 KiB
Python
341 lines
12 KiB
Python
"""AutoClipService — 智能选片服务.
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根据模板片段配置 (TemplateClipConfig) 的素材需求 (material_requirements)，
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自动从项目素材库中筛选、评分并分配最佳素材到剪辑计划片段 (EditPlanClip)。
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评分规则：
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- 质量分 (quality_score)：权重 0.5
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- 时长匹配度：权重 0.3（越接近目标时长得分越高）
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- 分类匹配度：权重 0.2（分类完全匹配得满分，部分匹配按比例得分）
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"""
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from __future__ import annotations
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import logging
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from dataclasses import dataclass
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from sqlalchemy.orm import Session
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from packages.adapters.sqlalchemy_impl import (
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SQLAlchemyAssetRepository,
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SQLAlchemyEditPlanClipRepository,
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SQLAlchemyEditPlanRepository,
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SQLAlchemyTemplateClipConfigRepository,
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)
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from packages.domain.asset import AssetType
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from packages.domain.classification import AssetClassification
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from packages.domain.edit_plan_clip import EditPlanClip, EditPlanClipStatus
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logger = logging.getLogger(__name__)
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# ── 评分权重 ──────────────────────────────────────────────────────────────────
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_WEIGHT_QUALITY = 0.5
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_WEIGHT_DURATION = 0.3
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_WEIGHT_CLASSIFICATION = 0.2
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@dataclass
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class AutoSelectResult:
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"""智能选片结果。"""
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plan_id: str
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total_clips: int
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assigned_clips: int
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unassigned_clips: int
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details: list[ClipAssignDetail]
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@dataclass
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class ClipAssignDetail:
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"""单个片段的分配详情。"""
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clip_id: str
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clip_type: str
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assigned_asset_id: str | None
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candidate_count: int
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score: float | None
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reason: str
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class AutoClipService:
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"""智能选片服务 — 自动为剪辑计划片段分配最佳素材。"""
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def __init__(self, db: Session) -> None:
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self._plan_repo = SQLAlchemyEditPlanRepository(db)
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self._clip_repo = SQLAlchemyEditPlanClipRepository(db)
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self._config_repo = SQLAlchemyTemplateClipConfigRepository(db)
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self._asset_repo = SQLAlchemyAssetRepository(db)
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# ── 公开方法 ──────────────────────────────────────────────────────────────
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def auto_select_assets(self, plan_id: str, project_id: str) -> AutoSelectResult:
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"""为剪辑计划的所有片段自动分配素材。
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流程：
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1. 获取剪辑计划 → 读取 template_id
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2. 获取模板的所有片段配置 (TemplateClipConfig)
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3. 获取计划的所有片段 (EditPlanClip)
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4. 对每个片段，根据其关联的 config 筛选候选素材并评分
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5. 将最佳素材分配给片段，标记为 READY
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Args:
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plan_id: 剪辑计划 ID
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project_id: 项目 ID（素材所属项目）
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Returns:
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AutoSelectResult 包含分配统计和每个片段的详情
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Raises:
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ValueError: 计划不存在
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"""
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plan = self._plan_repo.get(plan_id)
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if plan is None:
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raise ValueError(f"剪辑计划不存在: {plan_id}")
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# 获取模板片段配置（按 order 排序）
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configs = self._config_repo.list_by_template(plan.template_id)
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config_map = {c.id: c for c in configs}
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# 获取计划的所有片段
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clips = self._clip_repo.list_by_plan(plan_id)
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details: list[ClipAssignDetail] = []
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assigned_count = 0
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for clip in clips:
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detail = self._assign_single_clip(clip, project_id, config_map)
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details.append(detail)
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if detail.assigned_asset_id is not None:
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assigned_count += 1
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result = AutoSelectResult(
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plan_id=plan_id,
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total_clips=len(clips),
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assigned_clips=assigned_count,
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unassigned_clips=len(clips) - assigned_count,
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details=details,
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)
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logger.info(
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"智能选片完成: plan=%s total=%d assigned=%d unassigned=%d",
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plan_id,
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result.total_clips,
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result.assigned_clips,
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result.unassigned_clips,
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)
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return result
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def select_for_clip(self, clip_id: str, project_id: str) -> ClipAssignDetail:
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"""为单个片段选择并分配最佳素材。
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Args:
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clip_id: 片段 ID
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project_id: 项目 ID（素材所属项目）
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Returns:
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ClipAssignDetail 分配详情
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Raises:
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ValueError: 片段不存在或缺少关联配置
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"""
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clip = self._clip_repo.get(clip_id)
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if clip is None:
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raise ValueError(f"片段不存在: {clip_id}")
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# 获取关联的模板配置
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config = None
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if clip.template_clip_config_id:
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config = self._config_repo.get(clip.template_clip_config_id)
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config_map = {config.id: config} if config else {}
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return self._assign_single_clip(clip, project_id, config_map)
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# ── 内部方法 ──────────────────────────────────────────────────────────────
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def _assign_single_clip(
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self,
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clip: EditPlanClip,
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project_id: str,
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config_map: dict[str, object],
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) -> ClipAssignDetail:
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"""为单个片段分配素材。"""
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config = config_map.get(clip.template_clip_config_id) if clip.template_clip_config_id else None
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# 解析素材需求
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requirements = self._parse_material_requirements(config)
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# 搜索候选素材
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candidates = self._asset_repo.search_candidates(
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project_id=project_id,
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file_type=requirements.get("file_type"),
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min_quality_score=requirements.get("min_quality_score"),
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min_duration=requirements.get("min_duration"),
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max_duration=requirements.get("max_duration"),
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classification_category=requirements.get("classification_category"),
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tags=requirements.get("tags"),
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status="completed",
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limit=50,
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)
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if not candidates:
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return ClipAssignDetail(
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clip_id=clip.id,
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clip_type=requirements.get("clip_type", "unknown"),
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assigned_asset_id=None,
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candidate_count=0,
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score=None,
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reason="无符合条件的候选素材",
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)
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# 评分并选择最佳素材
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target_duration = requirements.get("target_duration")
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target_category = requirements.get("classification_category")
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best_asset = None
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best_score = -1.0
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for asset in candidates:
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score = self._score_candidate(
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asset,
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target_duration=target_duration,
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target_category=target_category,
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)
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if score > best_score:
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best_score = score
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best_asset = asset
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if best_asset is None:
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return ClipAssignDetail(
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clip_id=clip.id,
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clip_type=requirements.get("clip_type", "unknown"),
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assigned_asset_id=None,
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candidate_count=len(candidates),
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score=None,
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reason="候选素材评分均不合格",
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)
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# 分配素材并标记就绪
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clip.assign_asset(best_asset.id)
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clip.mark_ready()
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self._clip_repo.update(clip)
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return ClipAssignDetail(
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clip_id=clip.id,
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clip_type=requirements.get("clip_type", "unknown"),
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assigned_asset_id=best_asset.id,
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candidate_count=len(candidates),
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score=round(best_score, 4),
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reason=f"最佳匹配 (score={best_score:.4f})",
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)
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@staticmethod
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def _score_candidate(
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asset: object,
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*,
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target_duration: float | None = None,
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target_category: str | None = None,
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) -> float:
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"""对候选素材评分 (0.0 ~ 1.0)。
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评分维度：
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- 质量分 (quality_score)：归一化到 0-1，权重 0.5
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- 时长匹配度：越接近目标时长得分越高，权重 0.3
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- 分类匹配度：完全匹配得 1.0，无分类得 0.0，权重 0.2
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"""
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# 质量分 (0-100 → 0-1)
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quality = getattr(asset, "quality_score", None)
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quality_score = (quality / 100.0) if quality is not None else 0.5
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# 时长匹配度
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duration_score = 0.5 # 无目标时长的默认分
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if target_duration is not None and target_duration > 0:
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asset_duration = getattr(asset, "duration", None)
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if asset_duration is not None and asset_duration > 0:
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ratio = asset_duration / target_duration
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# 比率越接近 1.0 得分越高，使用高斯衰减
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duration_score = max(0.0, 1.0 - abs(1.0 - ratio) * 2)
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# 无时长的素材得 0 分
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else:
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duration_score = 0.0
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# 分类匹配度
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classification_score = 0.0
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if target_category is not None:
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metadata = getattr(asset, "metadata", {}) or {}
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asset_category = metadata.get("category", "")
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if asset_category == target_category:
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classification_score = 1.0
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elif asset_category:
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# 部分匹配（同大类）给 0.5
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classification_score = 0.3
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else:
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# 无分类要求，所有素材得满分
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classification_score = 1.0
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total = (
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_WEIGHT_QUALITY * quality_score
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+ _WEIGHT_DURATION * duration_score
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+ _WEIGHT_CLASSIFICATION * classification_score
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)
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return total
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@staticmethod
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def _parse_material_requirements(config: object | None) -> dict:
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"""从 TemplateClipConfig 解析素材筛选条件。
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将 material_requirements JSON 和 config 自身的时长/类型字段
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统一转换为 search_candidates 可用的筛选参数。
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"""
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result: dict = {}
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if config is None:
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return result
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# 从 material_requirements 提取筛选条件
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requirements = getattr(config, "material_requirements", {}) or {}
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# 素材类型: material_requirements 中的 "type" 字段
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req_type = requirements.get("type")
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if req_type and req_type in (AssetType.VIDEO, AssetType.IMAGE, AssetType.AUDIO):
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result["file_type"] = req_type
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# 最低质量分
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min_quality = requirements.get("min_quality_score") or requirements.get("min_quality")
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if min_quality is not None:
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try:
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result["min_quality_score"] = float(min_quality)
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except (TypeError, ValueError) as e:
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logger.warning(f"Operation failed in apps/api/app/services/auto_clip_service.py: {e}", exc_info=True)
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# 分类筛选
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category = requirements.get("category") or requirements.get("classification")
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if category:
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# 验证是否为有效分类
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valid_categories = {c.value for c in AssetClassification}
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if category in valid_categories:
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result["classification_category"] = category
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# 标签筛选
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tags = requirements.get("tags")
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if isinstance(tags, list) and tags:
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result["tags"] = tags
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# 时长范围：优先使用 config 的 min/max_duration，其次 material_requirements
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min_dur = getattr(config, "min_duration", None) or requirements.get("min_duration")
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max_dur = getattr(config, "max_duration", None) or requirements.get("max_duration")
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if min_dur is not None and min_dur > 0:
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result["min_duration"] = float(min_dur)
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if max_dur is not None and max_dur > 0:
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result["max_duration"] = float(max_dur)
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# 目标时长（用于评分）
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if min_dur and max_dur:
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result["target_duration"] = (float(min_dur) + float(max_dur)) / 2
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elif min_dur:
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result["target_duration"] = float(min_dur) * 1.2
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elif max_dur:
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result["target_duration"] = float(max_dur) * 0.8
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# 片段类型（用于日志）
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clip_type = getattr(config, "clip_type", None)
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if clip_type:
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result["clip_type"] = clip_type.value if hasattr(clip_type, "value") else str(clip_type)
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return result
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