fix(PictureService, SearchDialog): enhance vector search with error handling and tab management #9

Services/Media/PictureService.cs

@@ -50,18 +50,31 @@ public class PictureService(
         // 决定是使用向量搜索还是普通搜索
         if (useVectorSearch && !string.IsNullOrWhiteSpace(searchQuery))
         {
-            return await PerformVectorSearchAsync(
+            try
-                dbContext, page, pageSize, searchQuery, tags,
+            {
-                startDate, endDate, userId, onlyWithGps, similarityThreshold,
+                return await PerformVectorSearchAsync(
-                excludeAlbumId, albumId, onlyFavorites, ownerId, includeAllPublic);
+                    dbContext, page, pageSize, searchQuery, tags,
-        }
+                    startDate, endDate, userId, onlyWithGps, similarityThreshold,
-        else
+                    excludeAlbumId, albumId, onlyFavorites, ownerId, includeAllPublic);
-        {
+            }
-            return await PerformStandardSearchAsync(
+            catch (Exception ex)
-                dbContext, page, pageSize, searchQuery, tags,
+            {
-                startDate, endDate, userId, sortBy, onlyWithGps,
+                // 如果向量搜索失败，记录错误并回退到标准搜索
-                excludeAlbumId, albumId, onlyFavorites, ownerId, includeAllPublic);
+                Console.WriteLine($"向量搜索失败，回退到标准搜索: {ex.Message}");
+                
+                // 如果是明确的配置错误，则向上抛出异常
+                if (ex.Message.Contains("请检查嵌入模型配置"))
+                {
+                    throw;
+                }
+            }
         }
+        
+        // 执行标准搜索（作为默认方法或向量搜索的回退选项）
+        return await PerformStandardSearchAsync(
+            dbContext, page, pageSize, searchQuery, tags,
+            startDate, endDate, userId, sortBy, onlyWithGps,
+            excludeAlbumId, albumId, onlyFavorites, ownerId, includeAllPublic);
     }
 
     // 执行向量搜索
@@ -82,55 +95,78 @@ public class PictureService(
         int? ownerId,
         bool includeAllPublic)
     {
-        var queryEmbedding = await embeddingService.GetEmbeddingAsync(searchQuery);
+        try
-        var queryVector = new Vector(queryEmbedding);
+        {
-
+            float[]? queryEmbedding = null;
-        // 构建基础查询
+            try
-        var query = dbContext.Pictures
-            .Include(p => p.Tags)
-            .Include(p => p.User)
-            .Where(p => p.Embedding != null);
-
-        // 应用共通的查询条件
-        query = ApplyCommonFilters(query, tags, startDate, endDate, userId, onlyWithGps,
-            excludeAlbumId, albumId, onlyFavorites, ownerId, includeAllPublic);
-
-        // 执行向量搜索
-        var allResults = await query
-            .Select(p => new
             {
-                Picture = p,
+                queryEmbedding = await embeddingService.GetEmbeddingAsync(searchQuery);
-                Similarity = 1.0 - p.Embedding!.CosineDistance(queryVector)
+                
-            })
+                // 检查嵌入向量是否有效
-            .Where(p => p.Similarity >= similarityThreshold)
+                if (queryEmbedding == null || queryEmbedding.Length == 0)
-            .OrderByDescending(p => p.Similarity)
+                {
-            .ToListAsync();
+                    throw new InvalidOperationException("嵌入模型返回了空向量");
+                }
+            }
+            catch (Exception ex)
+            {
+                throw new InvalidOperationException($"向量搜索失败，请检查嵌入模型配置: {ex.Message}", ex);
+            }
+            
+            var queryVector = new Vector(queryEmbedding);
 
-        // 计算总数并分页
+            // 构建基础查询
-        var totalCount = allResults.Count;
+            var query = dbContext.Pictures
+                .Include(p => p.Tags)
+                .Include(p => p.User)
+                .Where(p => p.Embedding != null);
 
-        var paginatedResults = allResults
+            // 应用共通的查询条件
-            .Skip((page - 1) * pageSize)
+            query = ApplyCommonFilters(query, tags, startDate, endDate, userId, onlyWithGps,
-            .Take(pageSize)
+                excludeAlbumId, albumId, onlyFavorites, ownerId, includeAllPublic);
-            .Select(r => MapPictureToResponse(r.Picture))
-            .ToList();
 
-        // 处理收藏信息
+            // 执行向量搜索
-        await PopulateFavoriteInfo(dbContext, paginatedResults, userId);
+            var allResults = await query
+                .Select(p => new
+                {
+                    Picture = p,
+                    Similarity = 1.0 - p.Embedding!.CosineDistance(queryVector)
+                })
+                .Where(p => p.Similarity >= similarityThreshold)
+                .OrderByDescending(p => p.Similarity)
+                .ToListAsync();
 
-        // 为当前用户的图片添加相册信息
+            // 计算总数并分页
-        if (userId.HasValue)
+            var totalCount = allResults.Count;
-        {
+
-            await PopulateAlbumInfo(dbContext, paginatedResults, userId.Value);
+            var paginatedResults = allResults
+                .Skip((page - 1) * pageSize)
+                .Take(pageSize)
+                .Select(r => MapPictureToResponse(r.Picture))
+                .ToList();
+
+            // 处理收藏信息
+            await PopulateFavoriteInfo(dbContext, paginatedResults, userId);
+
+            // 为当前用户的图片添加相册信息
+            if (userId.HasValue)
+            {
+                await PopulateAlbumInfo(dbContext, paginatedResults, userId.Value);
+            }
+
+            return new PaginatedResult<PictureResponse>
+            {
+                Data = paginatedResults,
+                Page = page,
+                PageSize = pageSize,
+                TotalCount = totalCount
+            };
         }
-
+        catch (Exception ex)
-        return new PaginatedResult<PictureResponse>
         {
-            Data = paginatedResults,
+            Console.WriteLine($"向量搜索失败: {ex.Message}");
-            Page = page,
+            throw new InvalidOperationException($"向量搜索失败: {ex.Message}", ex);
-            PageSize = pageSize,
+        }
-            TotalCount = totalCount
-        };
     }
 
     // 执行标准搜索

Web/src/components/search/SearchDialog.tsx

@@ -126,6 +126,17 @@ const SearchDialog: React.FC<SearchDialogProps> = ({
     }
   };
 
+  // 处理标签页切换，同时更新 useVectorSearch 状态
+  const handleTabChange = (key: string) => {
+    setActiveTabKey(key);
+    // 根据标签页自动设置向量搜索状态
+    if (key === 'vector') {
+      setUseVectorSearch(true);
+    } else {
+      setUseVectorSearch(false);
+    }
+  };
+
   return (
     <Modal
       title={
@@ -143,7 +154,7 @@ const SearchDialog: React.FC<SearchDialogProps> = ({
     >
       <Tabs
         activeKey={activeTabKey}
-        onChange={setActiveTabKey}
+        onChange={handleTabChange}
         className="search-tabs"
         items={[
           {
@@ -163,9 +174,6 @@ const SearchDialog: React.FC<SearchDialogProps> = ({
                     autoFocus={activeTabKey === 'text'}
                   />
                 </div>
-                
-                <Divider orientation="left" plain>筛选选项</Divider>
-                
                 <div className="search-option-group">
                   <Text strong className="option-label">标签筛选:</Text>
                   <Select
@@ -212,9 +220,6 @@ const SearchDialog: React.FC<SearchDialogProps> = ({
                     autoFocus={activeTabKey === 'vector'}
                   />
                 </div>
-                
-                <Divider orientation="left" plain>高级选项</Divider>
-                
                 <div className="search-option-group vector-options">
                   <div className="vector-switch-container">
                     <Switch