1

kb/consts/status.go

@@ -2,10 +2,12 @@ package consts
 
 // 文档状态
 const (
-	DocumentStatusPending = 0 // 待处理
-	DocumentStatusParsing = 1 // 处理中
-	DocumentStatusDone    = 2 // 完成
-	DocumentStatusFailed  = 3 // 失败
+	DocumentStatusPending    = 0 // 待处理
+	DocumentStatusParsing    = 1 // 解析中（读取文件 + 分块）
+	DocumentStatusEmbedding  = 2 // 向量生成中
+	DocumentStatusKgBuilding = 3 // 知识图谱构建中
+	DocumentStatusDone       = 4 // 已完成
+	DocumentStatusFailed     = 5 // 失败
 )
 
 // 解析任务状态

kb/service/chunk_service.go

@@ -409,7 +409,6 @@ func (s *chunkService) InsertAll(ctx context.Context, datasetId, documentId int6
 	}
 	return dao.Document.UpdateFields(ctx, documentId, g.Map{
 		"chunk_count": len(chunks),
-		"status":      consts.DocumentStatusDone,
 	})
 }
 

kb/service/kg_entity_service.go

@@ -35,23 +35,24 @@ type kgExtractResult struct {
 }
 
 // ExtractDocument 对文档全部新分块做 LLM 抽取（挂在解析流水线分块落库之后）。
-// 每个分块一次调用，任何失败只记日志，不阻断解析流水线；未配置默认对话模型时直接跳过。
-func (s *kgEntityService) ExtractDocument(ctx context.Context, datasetId, documentId int64) error {
+// 每个分块一次调用，任何失败只记日志，不阻断解析流水线；返回未成功抽取的分块数，供调用方标记图谱未构建。
+func (s *kgEntityService) ExtractDocument(ctx context.Context, datasetId, documentId int64) (int, error) {
 	chunks, _, err := dao.Chunk.ListByDocument(ctx, documentId, 1, 100000)
 	if err != nil {
-		return err
+		return 0, err
 	}
 	model, err := s.buildModel(ctx)
 	if err != nil {
-		g.Log().Infof(ctx, "kg extract skipped: %v", err)
-		return nil
+		return 0, err
 	}
+	failed := 0
 	for _, c := range chunks {
 		if err := s.extractChunk(ctx, model, datasetId, c); err != nil {
+			failed++
 			g.Log().Warningf(ctx, "kg extract chunk %d failed: %v", c.Id, err)
 		}
 	}
-	return nil
+	return failed, nil
 }
 
 func (s *kgEntityService) buildModel(ctx context.Context) (*OpenAIChatModel, error) {

kb/service/parse_task_service.go

@@ -2,6 +2,7 @@ package service
 
 import (
 	"context"
+	"fmt"
 	"path/filepath"
 	"time"
 
@@ -117,15 +118,33 @@ func (s *parseTaskService) processOne(ctx context.Context) {
 			g.Log().Warningf(ctx, "save detected structure patterns failed: %v", err)
 		}
 	}
+	if err := dao.Document.UpdateFields(ctx, doc.Id, g.Map{"status": consts.DocumentStatusEmbedding}); err != nil {
+		s.fail(ctx, task, "更新文档状态失败: "+err.Error())
+		return
+	}
 	if err := ChunkService.InsertAll(ctx, task.DatasetId, doc.Id, chunks, embedder); err != nil {
 		s.fail(ctx, task, "写入分块失败: "+err.Error())
 		return
 	}
-	// 第 3.5 步：知识图谱抽取（失败不阻断流水线）
-	if err := KgEntityService.ExtractDocument(ctx, task.DatasetId, doc.Id); err != nil {
-		g.Log().Warningf(ctx, "kg extract skipped for doc %d: %v", doc.Id, err)
+	// 第 3.5 步：知识图谱抽取（失败不阻断流水线，但文档标记图谱未构建，避免误报已完成）
+	if err := dao.Document.UpdateFields(ctx, doc.Id, g.Map{"status": consts.DocumentStatusKgBuilding}); err != nil {
+		g.Log().Warningf(ctx, "mark kg building failed: %v", err)
 	}
-	if err := dao.ParseTask.UpdateStatus(ctx, task.Id, consts.TaskStatusDone, ""); err != nil {
+	kgFailed, kgErr := KgEntityService.ExtractDocument(ctx, task.DatasetId, doc.Id)
+	kgMsg := ""
+	switch {
+	case kgErr != nil:
+		kgMsg = "知识图谱未构建: " + kgErr.Error()
+	case kgFailed > 0:
+		kgMsg = fmt.Sprintf("知识图谱未构建：%d 个分块抽取失败", kgFailed)
+	}
+	if kgMsg != "" {
+		g.Log().Warningf(ctx, "kg extract incomplete for doc %d: %s", doc.Id, kgMsg)
+	}
+	if err := dao.Document.UpdateFields(ctx, doc.Id, g.Map{"status": consts.DocumentStatusDone, "error_msg": kgMsg}); err != nil {
+		g.Log().Warningf(ctx, "mark document done failed: %v", err)
+	}
+	if err := dao.ParseTask.UpdateStatus(ctx, task.Id, consts.TaskStatusDone, kgMsg); err != nil {
 		g.Log().Errorf(ctx, "mark task done failed: %v", err)
 	}
 }

ui-src/src/views/DatasetDetail.vue

@@ -23,6 +23,7 @@
           <el-tooltip :content="row.error_msg || ''" placement="top">
             <el-tag :type="statusType(row.status)">{{ statusText(row.status) }}</el-tag>
           </el-tooltip>
+          <el-tag v-if="row.status === 4 && row.error_msg" size="small" type="warning" style="margin-left: 4px">图谱未构建</el-tag>
         </template>
       </el-table-column>
       <el-table-column prop="chunk_count" label="分块数" width="90" />
@@ -30,7 +31,7 @@
       <el-table-column label="操作" width="240" fixed="right">
         <template #default="{ row }">
           <el-button link type="primary" @click="openChunks(row)">分块</el-button>
-          <el-button v-if="row.status === 3" link type="warning" @click="retry(row)">重试</el-button>
+          <el-button v-if="row.status === 5" link type="warning" @click="retry(row)">重试</el-button>
           <el-button link type="primary" @click="reembed(row)">重新向量化</el-button>
           <el-button link type="danger" @click="remove(row)">删除</el-button>
         </template>
@@ -126,8 +127,10 @@ let editingChunk = null
 const statusMap = {
   0: { text: '待处理', type: 'info' },
   1: { text: '解析中', type: 'warning' },
-  2: { text: '已完成', type: 'success' },
-  3: { text: '失败', type: 'danger' }
+  2: { text: '向量生成中', type: 'warning' },
+  3: { text: '图谱构建中', type: 'warning' },
+  4: { text: '已完成', type: 'success' },
+  5: { text: '失败', type: 'danger' }
 }
 
 function statusText(s) { return (statusMap[s] || {}).text || s }
@@ -172,7 +175,7 @@ async function startPolling() {
   stopPolling()
   pollTimer = setInterval(async () => {
     await load()
-    if (!documents.value.some(d => d.status === 0 || d.status === 1)) stopPolling()
+    if (!documents.value.some(d => d.status < 4)) stopPolling()
   }, 3000)
 }
 function stopPolling() {
@@ -189,7 +192,7 @@ onMounted(async () => {
     datasetName.value = cur ? cur.name : '数据集'
   } catch { /* 忽略 */ }
   await load()
-  if (documents.value.some(d => d.status === 0 || d.status === 1)) startPolling()
+  if (documents.value.some(d => d.status < 4)) startPolling()
 })
 onUnmounted(stopPolling)