diff --git a/src/views/warehouse/WmsImportResult/index.vue b/src/views/warehouse/WmsImportResult/index.vue
index 85440a1..b92753f 100644
--- a/src/views/warehouse/WmsImportResult/index.vue
+++ b/src/views/warehouse/WmsImportResult/index.vue
@@ -102,25 +102,15 @@
 </template>
 
 <script setup name="WmsImportResult">
-import { ref, reactive, toRefs, getCurrentInstance, shallowRef } from 'vue'
-import { listWmsImportResult, getWmsImportResult, delWmsImportResult, addWmsImportResult, updateWmsImportResult } from "@/api/warehouse/WmsImportResult"
+import { ref, reactive, shallowRef } from 'vue'
 import { API_CONFIG } from "@/config/api"
 import ParetoAnalysis from './ParetoAnalysis.vue'
 import EmptyContent from './EmptyContent.vue'
 
-const { proxy } = getCurrentInstance()
-
-const WmsImportResultList = ref([])
-const open = ref(false)
-const loading = ref(true)
 const showSearch = ref(true)
-const ids = ref([])
 const single = ref(true)
 const multiple = ref(true)
-const total = ref(0)
-const title = ref("")
 const message = ref("")
-const selectedTimeRange = ref("近1年")
 const timeRangeOptions = ref([
   { value: "近1年", label: "近1年" },
   { value: "近2年", label: "近2年" },
@@ -134,9 +124,6 @@ const dateRange = ref({
   start_date: '',
   end_date: ''
 })
-const aiDialogVisible = ref(false)
-const aiAnalysisResult = ref("")
-const aiAnalysisLoading = ref(false)
 
 // 当前显示的组件
 const currentComponent = shallowRef(EmptyContent)
@@ -159,9 +146,6 @@ const data = reactive({
   }
 })
 
-const { queryParams, form, rules } = toRefs(data)
-
-
 function handlePareto() {
   // 根据选择的时间范围计算开始和结束日期
   const endDate = new Date();
@@ -186,7 +170,7 @@ function handlePareto() {
   const startDateStr = formatDate(startDate);
   const endDateStr = formatDate(endDate);
   
-  console.log(startDateStr, endDateStr);
+  // console.log(startDateStr, endDateStr);
   // 调用质检API并显示结果
   fetch(`${API_CONFIG.BASE_URL}${API_CONFIG.ENDPOINTS.PARETO_ANALYSIS}?start_date=${startDateStr}&end_date=${endDateStr}`)
     .then(response => response.json())
@@ -214,84 +198,6 @@ function handleAIAnalysisComplete(result) {
   message.value = result;
 }
 
-// getList()
-// 根据缺陷百分比设置进度条颜色
-function getProgressColor(percentage) {
-  if (percentage >= 30) return '#f56c6c'; // 红色 - 高缺陷率
-  if (percentage >= 15) return '#e6a23c'; // 橙色 - 中等缺陷率
-  if (percentage >= 5) return '#409eff';   // 蓝色 - 低缺陷率
-  return '#67c23a'; // 绿色 - 很低缺陷率
-}
-
-// AI分析功能
-async function handleAIAnalysis() {
-  if (paretoData.value.length === 0) {
-    message.value = '请先获取帕累托分析数据'
-    return
-  }
-
-  aiAnalysisLoading.value = true
-  aiDialogVisible.value = true
-  aiAnalysisResult.value = '正在分析中，请稍候...'
-
-  try {
-    // 准备分析提示词
-    const prompt = `请分析以下帕累托分析数据，提供专业的质量控制见解：
-
-  数据范围: ${dateRange.value.start_date} 至 ${dateRange.value.end_date}
-  检测项目总数: ${paretoData.value.length}
-
-  详细数据:
-  ${paretoData.value.map(item => 
-    `- ${item.item_name}: 缺陷数 ${item.defect_count}, 缺陷占比 ${item.defect_percentage}%, 累计占比 ${item.cumulative_percentage}%`
-  ).join('\n')}
-
-  请从以下角度进行分析：
-  1. 主要缺陷项及其影响程度
-  2. 帕累托原理(80/20法则)在此数据中的体现
-  3. 针对高缺陷率项的改进建议
-  4. 质量控制重点优化方向`
-
-    // 调用DeepSeek API进行分析
-    const response = await fetch('https://api.deepseek.com/v1/chat/completions', {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-        'Authorization': `Bearer sk-4fa66e674e57479d961e4ad2036cbc52`
-      },
-      body: JSON.stringify({
-        model: 'deepseek-chat',
-        messages: [
-          {
-            role: 'system',
-            content: '你是一位专业的质量控制专家，擅长分析缺陷数据并提供专业的改进建议。'
-          },
-          {
-            role: 'user',
-            content: prompt
-          }
-        ],
-        temperature: 0.7,
-        max_tokens: 1500
-      })
-    })
-
-    if (!response.ok) {
-      throw new Error(`API调用失败: ${response.status}`)
-    }
-
-    const data = await response.json()
-    const analysisResult = data.choices[0].message.content
-    aiAnalysisResult.value = analysisResult
-    // 同时将分析结果输出到消息显示文本框
-    message.value = analysisResult
-  } catch (error) {
-    console.error('AI分析失败:', error)
-    aiAnalysisResult.value = `AI分析失败: ${error.message}\n\n请检查网络连接或稍后再试。`
-  } finally {
-    aiAnalysisLoading.value = false
-  }
-}
 
 </script>