diff --git a/backend/app/services/foreshadow_service.py b/backend/app/services/foreshadow_service.py index c9f346e..cb1e9d8 100644 --- a/backend/app/services/foreshadow_service.py +++ b/backend/app/services/foreshadow_service.py @@ -414,6 +414,17 @@ class ForeshadowService: fs_estimated_resolve = fs_data.get("estimated_resolve_chapter") fs_keyword = fs_data.get("keyword", "") + # 🔧 修复Bug#7：如果AI没有填写estimated_resolve_chapter，提供合理的默认值 + if fs_estimated_resolve is None and fs_type == "planted": + # 根据伏笔类型和长线属性计算默认回收章节 + if fs_is_long_term: + # 长线伏笔：当前章节 + 15章 + fs_estimated_resolve = chapter.chapter_number + 15 + else: + # 短线伏笔：当前章节 + 5章 + fs_estimated_resolve = chapter.chapter_number + 5 + logger.info(f"⚠️ AI未填写estimated_resolve_chapter，使用默认值: 第{fs_estimated_resolve}章") + # 确定状态 status = "planted" if (fs_type == "planted" and data.auto_set_planted) else "pending" if fs_type == "resolved": @@ -430,7 +441,7 @@ class ForeshadowService: existing_foreshadow.is_long_term = fs_is_long_term existing_foreshadow.related_characters = fs_related_characters if fs_related_characters else None existing_foreshadow.hint_text = fs_keyword if fs_keyword else None - if fs_estimated_resolve and status == "planted": + if fs_estimated_resolve: existing_foreshadow.target_resolve_chapter_number = fs_estimated_resolve await db.flush() new_foreshadows.append(existing_foreshadow.to_dict()) @@ -448,7 +459,7 @@ class ForeshadowService: plant_chapter_id=chapter.id if status == "planted" else None, plant_chapter_number=chapter.chapter_number if status == "planted" else None, planted_at=datetime.now() if status == "planted" else None, - target_resolve_chapter_number=fs_estimated_resolve if (status == "planted" and fs_estimated_resolve) else None, + target_resolve_chapter_number=fs_estimated_resolve if fs_estimated_resolve else None, status=status, is_long_term=fs_is_long_term, importance=min(fs_strength / 10.0, 1.0), @@ -1020,7 +1031,6 @@ class ForeshadowService: 清理统计信息 """ try: - # 查找该章节分析产生的伏笔 query = select(Foreshadow).where( and_( Foreshadow.project_id == project_id, @@ -1028,7 +1038,10 @@ class ForeshadowService: or_( Foreshadow.source_memory_id.like(f"analysis_%_{chapter_id}%"), Foreshadow.source_memory_id.like(f"auto_analysis_{chapter_id}%"), - Foreshadow.plant_chapter_id == chapter_id + and_( + Foreshadow.plant_chapter_id == chapter_id, + Foreshadow.status.in_(["pending", "planted"]) + ) ) ) ) @@ -1222,21 +1235,58 @@ class ForeshadowService: elif existing: logger.warning(f"⚠️ 伏笔状态不是planted，跳过回收: {existing.title} (status: {existing.status})") else: - # 没有找到匹配的伏笔，记录警告 fs_title = fs_data.get("title", fs_data.get("content", "")[:30]) - logger.warning(f"⚠️ 未能匹配到伏笔进行回收: {fs_title}") - stats["errors"].append(f"未找到匹配的伏笔: {fs_title}") + logger.warning(f"⚠️ 未能匹配到已埋入伏笔，创建新的回收记录: {fs_title}") + reference_chapter = fs_data.get("reference_chapter") + new_resolved_foreshadow = Foreshadow( + id=str(uuid.uuid4()), + project_id=project_id, + title=fs_title, + content=fs_data.get("content", ""), + resolution_text=fs_data.get("content", ""), + source_type="analysis", + source_memory_id=f"auto_analysis_{chapter_id}_{fs_title[:30]}", + plant_chapter_number=reference_chapter if reference_chapter else None, + actual_resolve_chapter_id=chapter_id, + actual_resolve_chapter_number=chapter_number, + resolved_at=datetime.now(), + status="resolved", + is_long_term=fs_data.get("is_long_term", False), + importance=min(fs_data.get("strength", 5) / 10.0, 1.0), + strength=fs_data.get("strength", 5), + subtlety=fs_data.get("subtlety", 5), + category=fs_data.get("category"), + related_characters=fs_data.get("related_characters"), + auto_remind=False, + include_in_context=True + ) + db.add(new_resolved_foreshadow) + await db.flush() + + stats["resolved_count"] += 1 + stats["created_count"] += 1 + stats["created_ids"].append(new_resolved_foreshadow.id) + logger.info(f"✅ 创建新的回收伏笔记录: {fs_title} (ID: {new_resolved_foreshadow.id})") elif fs_type == "planted": - # 【埋入伏笔】创建新的伏笔记录 fs_title = fs_data.get("title", "") if not fs_title: fs_title = fs_data.get("content", "")[:50] + "..." - # 生成唯一标识符，避免重复创建 - source_memory_id = f"auto_analysis_{chapter_id}_{fs_title[:30]}" + analysis_query = select(PlotAnalysis.id).where( + PlotAnalysis.chapter_id == chapter_id + ).order_by(PlotAnalysis.created_at.desc()).limit(1) + analysis_result = await db.execute(analysis_query) + analysis_id = analysis_result.scalar_one_or_none() - # 检查是否已存在 + if not analysis_id: + logger.warning(f"⚠️ 未找到章节 {chapter_id} 的分析记录，跳过伏笔创建") + continue + + fs_index = analysis_foreshadows.index(fs_data) + source_memory_id = f"analysis_{analysis_id}_{fs_index}" + + # 检查是否已存在（可能已经通过 sync_from_analysis 创建） existing_check = await db.execute( select(Foreshadow).where( and_( @@ -1248,15 +1298,26 @@ class ForeshadowService: existing_fs = existing_check.scalar_one_or_none() if existing_fs: - # 已存在，更新信息 + existing_fs.title = fs_title existing_fs.content = fs_data.get("content", existing_fs.content) existing_fs.strength = fs_data.get("strength", existing_fs.strength) existing_fs.subtlety = fs_data.get("subtlety", existing_fs.subtlety) existing_fs.hint_text = fs_data.get("keyword", existing_fs.hint_text) + existing_fs.target_resolve_chapter_number = fs_data.get("estimated_resolve_chapter", existing_fs.target_resolve_chapter_number) await db.flush() - logger.info(f"📝 更新已存在伏笔: {fs_title}") + logger.info(f"📝 更新已存在伏笔（避免重复）: {fs_title}") else: - # 创建新伏笔 + # 创建新伏笔（使用统一的标识符格式） + # 🔧 修复Bug#7：如果AI没有填写estimated_resolve_chapter，提供合理的默认值 + estimated_resolve = fs_data.get("estimated_resolve_chapter") + if estimated_resolve is None: + # 根据伏笔类型和长线属性计算默认回收章节 + if fs_data.get("is_long_term", False): + estimated_resolve = chapter_number + 15 + else: + estimated_resolve = chapter_number + 5 + logger.info(f"⚠️ AI未填写estimated_resolve_chapter，使用默认值: 第{estimated_resolve}章") + new_foreshadow = Foreshadow( id=str(uuid.uuid4()), project_id=project_id, @@ -1264,11 +1325,12 @@ class ForeshadowService: content=fs_data.get("content", ""), hint_text=fs_data.get("keyword"), source_type="analysis", - source_memory_id=source_memory_id, + source_memory_id=source_memory_id, # 使用统一格式 + source_analysis_id=analysis_id, # 关联分析ID plant_chapter_id=chapter_id, plant_chapter_number=chapter_number, planted_at=datetime.now(), - target_resolve_chapter_number=fs_data.get("estimated_resolve_chapter"), + target_resolve_chapter_number=estimated_resolve, status="planted", is_long_term=fs_data.get("is_long_term", False), importance=min(fs_data.get("strength", 5) / 10.0, 1.0),