diff --git a/src/main/java/com/superbiz/agent/service/VectorIndexService.java b/src/main/java/com/superbiz/agent/service/VectorIndexService.java
index e2ae9b4..9100db5 100644
--- a/src/main/java/com/superbiz/agent/service/VectorIndexService.java
+++ b/src/main/java/com/superbiz/agent/service/VectorIndexService.java
@@ -268,6 +268,9 @@ public class VectorIndexService {
             metadata.put("title", chunk.getTitle());
         }
 
+        // 默认类别：上传文档
+        metadata.put("category", "upload");
+
         return metadata;
     }
 
@@ -336,23 +339,61 @@ public class VectorIndexService {
         if (dotIndex > 0) {
             extension = fileNameStr.substring(dotIndex);
         }
-        
+
         metadata.put("_source", normalizedPath);
         metadata.put("_extension", extension);
         metadata.put("_file_name", fileNameStr);
-        
+
+        // 提取类别（从文件路径中提取目录名）
+        String category = extractCategory(normalizedPath);
+        if (category != null && !category.isEmpty()) {
+            metadata.put("category", category);
+        }
+
         // 分片信息
         metadata.put("chunkIndex", chunk.getChunkIndex());
         metadata.put("totalChunks", totalChunks);
-        
+
         // 标题信息
         if (chunk.getTitle() != null && !chunk.getTitle().isEmpty()) {
             metadata.put("title", chunk.getTitle());
         }
-        
+
         return metadata;
     }
 
+    /**
+     * 从文件路径中提取类别
+     * 例如：aiops-docs/api/redis-api.md → "api"
+     */
+    private String extractCategory(String filePath) {
+        try {
+            // 标准化路径分隔符
+            String normalized = filePath.replace("\\", "/");
+
+            // 查找 aiops-docs/ 后的第一级目录
+            int docsIndex = normalized.indexOf("aiops-docs/");
+            if (docsIndex >= 0) {
+                String afterDocs = normalized.substring(docsIndex + "aiops-docs/".length());
+                int slashIndex = afterDocs.indexOf("/");
+                if (slashIndex > 0) {
+                    return afterDocs.substring(0, slashIndex);
+                }
+            }
+
+            // 如果没有 aiops-docs，返回第一级目录
+            int firstSlash = normalized.indexOf("/");
+            if (firstSlash > 0) {
+                return normalized.substring(0, firstSlash);
+            }
+
+            return null;
+        } catch (Exception e) {
+            logger.warn("提取类别失败，路径: {}", filePath, e);
+            return null;
+        }
+    }
+
     /**
      * 插入向量到 Milvus
      */
diff --git a/src/main/java/com/superbiz/agent/service/VectorSearchService.java b/src/main/java/com/superbiz/agent/service/VectorSearchService.java
index b0ce48a..e9baee7 100644
--- a/src/main/java/com/superbiz/agent/service/VectorSearchService.java
+++ b/src/main/java/com/superbiz/agent/service/VectorSearchService.java
@@ -34,29 +34,49 @@ public class VectorSearchService {
 
     /**
      * 搜索相似文档
-     * 
+     *
      * @param query 查询文本
      * @param topK 返回最相似的K个结果
      * @return 搜索结果列表
      */
     public List<SearchResult> searchSimilarDocuments(String query, int topK) {
+        return searchSimilarDocuments(query, topK, null);
+    }
+
+    /**
+     * 搜索相似文档（支持类别过滤）
+     *
+     * @param query 查询文本
+     * @param topK 返回最相似的K个结果
+     * @param category 类别过滤（可选，null 表示不过滤）
+     * @return 搜索结果列表
+     */
+    public List<SearchResult> searchSimilarDocuments(String query, int topK, String category) {
         try {
-            logger.info("开始搜索相似文档, 查询: {}, topK: {}", query, topK);
+            logger.info("开始搜索相似文档, 查询: {}, topK: {}, 类别: {}", query, topK, category);
 
             // 1. 将查询文本向量化
             List<Float> queryVector = embeddingService.generateQueryVector(query);
             logger.debug("查询向量生成成功, 维度: {}", queryVector.size());
 
             // 2. 构建搜索参数
-            SearchParam searchParam = SearchParam.newBuilder()
+            SearchParam.Builder searchParamBuilder = SearchParam.newBuilder()
                     .withCollectionName(MilvusConstants.MILVUS_COLLECTION_NAME)
                     .withVectorFieldName("vector")
                     .withVectors(Collections.singletonList(queryVector))
                     .withTopK(topK)
                     .withMetricType(io.milvus.param.MetricType.L2)
                     .withOutFields(List.of("id", "content", "metadata"))
-                    .withParams("{\"nprobe\":10}")
-                    .build();
+                    .withParams("{\"nprobe\":10}");
+
+            // 添加类别过滤
+            if (category != null && !category.trim().isEmpty()) {
+                String expr = String.format("metadata[\"category\"] == \"%s\"", category);
+                searchParamBuilder.withExpr(expr);
+                logger.info("添加类别过滤: {}", expr);
+            }
+
+            SearchParam searchParam = searchParamBuilder.build();
 
             // 3. 执行搜索
             R<SearchResults> searchResponse = milvusClient.search(searchParam);
@@ -74,13 +94,13 @@ public class VectorSearchService {
                 result.setId((String) wrapper.getIDScore(0).get(i).get("id"));
                 result.setContent((String) wrapper.getFieldData("content", 0).get(i));
                 result.setScore(wrapper.getIDScore(0).get(i).getScore());
-                
+
                 // 解析 metadata
                 Object metadataObj = wrapper.getFieldData("metadata", 0).get(i);
                 if (metadataObj != null) {
                     result.setMetadata(metadataObj.toString());
                 }
-                
+
                 results.add(result);
             }