为一个租户灌入测试数据；实例的启动代码（包括前后端）

tangwang
1 parent d79810d5
Showing 11 changed files with 1569 additions and 0 deletions Show diff stats
DEPLOYMENT.md
USER_GUIDE.md
frontend/index.html
frontend/static/css/style.css
frontend/static/js/app.js
scripts/frontend_server.py
scripts/ingest.sh
scripts/start_backend.sh
scripts/start_frontend.sh
setup.sh
start_all.sh
@@ -0,0 +1,317 @@
+# 部署检查清单
+
+## 完成情况
+
+✅ **环境配置**
+- [x] .env 配置文件（包含ES、Redis、DeepL配置）
+- [x] environment.yml (conda环境配置)
+- [x] config/env_config.py (统一配置管理)
+- [x] 代码已更新使用新配置
+
+✅ **启动脚本**
+- [x] setup.sh (环境设置)
+- [x] start_all.sh (一键启动)
+- [x] scripts/ingest.sh (数据导入)
+- [x] scripts/start_backend.sh (后端服务)
+- [x] scripts/start_frontend.sh (前端服务)
+
+✅ **Web前端**
+- [x] HTML界面 (frontend/index.html)
+- [x] CSS样式 (frontend/static/css/style.css)
+- [x] JavaScript逻辑 (frontend/static/js/app.js)
+- [x] 前端服务器 (scripts/frontend_server.py)
+
+✅ **文档**
+- [x] USER_GUIDE.md (用户指南)
+- [x] README.md (项目说明)
+- [x] QUICKSTART.md (快速开始)
+- [x] IMPLEMENTATION_SUMMARY.md (实现总结)
+
+## 使用步骤
+
+### 方式1: 一键启动（推荐）
+
+```bash
+cd /data/tw/SearchEngine
+./start_all.sh
+```
+
+然后访问: http://localhost:8080
+
+### 方式2: 分步启动
+
+```bash
+# 1. 环境设置
+./setup.sh
+
+# 2. 导入数据（1000条，快速测试）
+./scripts/ingest.sh 1000 true
+
+# 3. 启动后端（新终端）
+./scripts/start_backend.sh
+
+# 4. 启动前端（新终端）
+./scripts/start_frontend.sh
+```
+
+## 系统要求
+
+### 软件要求
+- [x] Python 3.10
+- [x] Conda (Miniconda/Anaconda)
+- [x] Elasticsearch 8.18
+- [ ] CUDA (可选，用于GPU加速)
+
+### 配置要求
+- [x] ES连接信息
+- [x] DeepL API Key
+- [ ] Redis连接（可选）
+
+### 硬件要求
+- 内存: 建议8GB+
+- 磁盘: 10GB+ (包含模型文件)
+- GPU: 可选（加速embedding生成）
+
+## 配置信息
+
+当前配置（.env文件）：
+```
+ES_HOST=http://localhost:9200
+ES_USERNAME=essa
+ES_PASSWORD=4hOaLaf41y2VuI8y
+
+REDIS_HOST=localhost
+REDIS_PORT=6479
+REDIS_PASSWORD=BMfv5aI31kgHWtlx
+
+DEEPL_AUTH_KEY=c9293ab4-ad25-479b-919f-ab4e63b429ed
+
+CUSTOMER_ID=customer1
+API_HOST=0.0.0.0
+API_PORT=8000
+```
+
+## 服务端口
+
+| 服务 | 端口 | URL |
+|------|------|-----|
+| Elasticsearch | 9200 | http://localhost:9200 |
+| Backend API | 8000 | http://localhost:8000 |
+| Frontend Web | 8080 | http://localhost:8080 |
+| API Docs | 8000 | http://localhost:8000/docs |
+
+## 测试流程
+
+### 1. 环境测试
+
+```bash
+# 激活环境
+source /home/tw/miniconda3/etc/profile.d/conda.sh
+conda activate searchengine
+
+# 检查Python
+python --version  # 应该显示 Python 3.10.x
+
+# 检查配置
+python -c "from config.env_config import print_config; print_config()"
+```
+
+### 2. ES连接测试
+
+```bash
+# 直接测试
+curl http://localhost:9200 -u essa:4hOaLaf41y2VuI8y
+
+# Python测试
+python -c "
+from config.env_config import get_es_config
+from utils.es_client import ESClient
+es_config = get_es_config()
+client = ESClient(hosts=[es_config['host']], username=es_config.get('username'), password=es_config.get('password'))
+print('ES Connected:', client.ping())
+"
+```
+
+### 3. 数据导入测试
+
+```bash
+# 导入100条测试数据（跳过embedding以加快速度）
+./scripts/ingest.sh 100 true
+
+# 检查导入结果
+python -c "
+from config.env_config import get_es_config
+from utils.es_client import ESClient
+from config import ConfigLoader
+
+es_config = get_es_config()
+es_client = ESClient(hosts=[es_config['host']], username=es_config.get('username'), password=es_config.get('password'))
+config = ConfigLoader('config/schema').load_customer_config('customer1')
+count = es_client.count(config.es_index_name)
+print(f'Documents in index: {count}')
+"
+```
+
+### 4. API测试
+
+```bash
+# 启动后端（后台）
+nohup ./scripts/start_backend.sh > logs/backend.log 2>&1 &
+
+# 等待启动
+sleep 5
+
+# 测试健康检查
+curl http://localhost:8000/admin/health
+
+# 测试搜索
+curl -X POST http://localhost:8000/search/ \
+  -H "Content-Type: application/json" \
+  -d '{"query": "消防", "size": 5}'
+```
+
+### 5. 前端测试
+
+```bash
+# 启动前端
+./scripts/start_frontend.sh
+
+# 然后在浏览器访问: http://localhost:8080
+```
+
+## 故障排除
+
+### 问题1: conda环境创建失败
+
+**症状**: `conda env create` 报错
+
+**解决**:
+```bash
+# 检查conda版本
+conda --version
+
+# 更新conda
+conda update -n base conda
+
+# 重试创建
+conda env create -f environment.yml
+```
+
+### 问题2: ES连接失败
+
+**症状**: `Failed to connect to Elasticsearch`
+
+**解决**:
+```bash
+# 检查ES状态
+curl http://localhost:9200 -u essa:4hOaLaf41y2VuI8y
+
+# 检查ES版本
+curl http://localhost:9200 -u essa:4hOaLaf41y2VuI8y | grep version
+
+# 确认配置
+cat .env | grep ES_
+```
+
+### 问题3: 模型下载慢
+
+**症状**: 首次运行时模型下载很慢或超时
+
+**解决**:
+```bash
+# 跳过embedding快速测试
+./scripts/ingest.sh 1000 true
+
+# 或手动下载模型到指定目录
+# TEXT_MODEL_DIR=/data/tw/models/bge-m3
+# IMAGE_MODEL_DIR=/data/tw/models/cn-clip
+```
+
+### 问题4: 端口被占用
+
+**症状**: `Address already in use`
+
+**解决**:
+```bash
+# 查看占用端口的进程
+lsof -i :8000  # 后端
+lsof -i :8080  # 前端
+
+# 杀掉进程
+kill -9 <PID>
+
+# 或修改.env中的端口
+```
+
+## 下一步
+
+1. **测试搜索功能**
+   - 打开 http://localhost:8080
+   - 尝试不同的搜索查询
+   - 测试布尔操作符
+
+2. **查看API文档**
+   - 访问 http://localhost:8000/docs
+   - 了解所有可用的API端点
+
+3. **自定义配置**
+   - 编辑 `config/schema/customer1_config.yaml`
+   - 添加查询重写规则
+   - 调整ranking表达式
+
+4. **导入更多数据**
+   - 导入完整的10000条数据
+   - 生成embeddings以启用语义搜索
+
+5. **性能优化**
+   - 启用Redis缓存
+   - 调整ES分片数量
+   - 使用GPU加速
+
+## 项目文件清单
+
+**新增文件 (环境和启动相关)**:
+- [x] .env - 环境配置
+- [x] .env.example - 配置模板
+- [x] environment.yml - Conda环境
+- [x] config/env_config.py - 配置管理
+- [x] setup.sh - 环境设置
+- [x] start_all.sh - 一键启动
+- [x] scripts/ingest.sh - 数据导入
+- [x] scripts/start_backend.sh - 后端启动
+- [x] scripts/start_frontend.sh - 前端启动
+- [x] scripts/frontend_server.py - 前端服务器
+- [x] frontend/index.html - 前端页面
+- [x] frontend/static/css/style.css - 样式
+- [x] frontend/static/js/app.js - 前端逻辑
+- [x] USER_GUIDE.md - 用户指南
+- [x] DEPLOYMENT.md - 本文件
+
+**总计**: 14个新文件
+
+## 验证完成
+
+运行以下命令验证所有文件都已创建：
+
+```bash
+cd /data/tw/SearchEngine
+
+# 检查关键文件
+ls -la .env setup.sh start_all.sh
+ls -la scripts/*.sh scripts/*.py
+ls -la frontend/index.html
+ls -la frontend/static/css/style.css
+ls -la frontend/static/js/app.js
+
+# 检查可执行权限
+ls -l *.sh scripts/*.sh | grep "x"
+```
+
+所有文件应该都存在且脚本有执行权限。
+
+## 支持联系
+
+如有问题，请检查：
+1. logs/backend.log - 后端日志
+2. 浏览器控制台 - 前端错误
+3. USER_GUIDE.md - 详细使用说明
@@ -0,0 +1,343 @@
+# 使用指南 - SearchEngine
+
+## 快速启动（推荐）
+
+### 一键启动所有服务
+
+```bash
+cd /data/tw/SearchEngine
+./start_all.sh
+```
+
+这个脚本会自动完成：
+1. 设置conda环境
+2. 检查并导入测试数据（如果需要）
+3. 启动后端API服务（后台运行）
+4. 启动前端Web界面
+
+启动完成后，访问：
+- **前端界面**: http://localhost:8080
+- **后端API**: http://localhost:8000
+- **API文档**: http://localhost:8000/docs
+
+### 停止服务
+
+```bash
+# 停止后端
+kill $(cat logs/backend.pid)
+
+# 前端按 Ctrl+C
+```
+
+---
+
+## 分步启动（自定义）
+
+### 1. 环境设置
+
+```bash
+cd /data/tw/SearchEngine
+./setup.sh
+```
+
+这会：
+- 创建/激活conda环境 `searchengine`
+- 加载配置文件
+- 检查Elasticsearch连接
+
+### 2. 数据导入
+
+#### 快速测试（1000条，不生成embedding）
+```bash
+./scripts/ingest.sh 1000 true
+```
+
+#### 完整导入（10000条，包含embedding）
+```bash
+./scripts/ingest.sh 10000 false
+```
+
+**注意**: 首次运行会下载模型文件（BGE-M3和CN-CLIP），大约需要10-30分钟。
+
+### 3. 启动后端
+
+```bash
+./scripts/start_backend.sh
+```
+
+后端API会在 http://localhost:8000 启动
+
+### 4. 启动前端
+
+```bash
+./scripts/start_frontend.sh
+```
+
+前端界面会在 http://localhost:8080 启动
+
+---
+
+## 配置说明
+
+### 环境配置文件 (.env)
+
+```bash
+# Elasticsearch配置
+ES_HOST=http://localhost:9200
+ES_USERNAME=essa
+ES_PASSWORD=4hOaLaf41y2VuI8y
+
+# Redis配置（可选，用于缓存）
+REDIS_HOST=localhost
+REDIS_PORT=6479
+REDIS_PASSWORD=BMfv5aI31kgHWtlx
+
+# DeepL翻译API
+DEEPL_AUTH_KEY=c9293ab4-ad25-479b-919f-ab4e63b429ed
+
+# 客户配置
+CUSTOMER_ID=customer1
+
+# API服务配置
+API_HOST=0.0.0.0
+API_PORT=8000
+```
+
+### 修改配置
+
+1. 编辑 `.env` 文件
+2. 重启相关服务
+
+---
+
+## 使用Web界面
+
+### 搜索功能
+
+1. **简单搜索**: 直接输入关键词
+   - 中文: "芭比娃娃"
+   - 英文: "fire control set"
+   - 俄文: "Наборы для пожаротушения"
+
+2. **布尔搜索**: 使用操作符
+   - AND: "toy AND barbie"
+   - OR: "barbie OR doll"
+   - ANDNOT: "toy ANDNOT cheap"
+   - 组合: "toy AND (barbie OR doll) ANDNOT cheap"
+
+3. **域搜索**: 指定搜索域
+   - 品牌: "brand:ZHU LIN"
+   - 类别: "category:玩具"
+
+### 搜索选项
+
+- **启用翻译**: 自动翻译查询到其他语言
+- **启用语义搜索**: 使用embedding进行语义匹配
+- **启用自定义排序**: 使用配置的ranking表达式
+- **结果数量**: 10/20/50条
+
+---
+
+## API使用
+
+### 搜索接口
+
+```bash
+curl -X POST http://localhost:8000/search/ \
+  -H "Content-Type: application/json" \
+  -d '{
+    "query": "芭比娃娃",
+    "size": 10,
+    "enable_translation": true,
+    "enable_embedding": true
+  }'
+```
+
+### 图片搜索
+
+```bash
+curl -X POST http://localhost:8000/search/image \
+  -H "Content-Type: application/json" \
+  -d '{
+    "image_url": "https://oss.essa.cn/example.jpg",
+    "size": 10
+  }'
+```
+
+### 健康检查
+
+```bash
+curl http://localhost:8000/admin/health
+```
+
+### 查看配置
+
+```bash
+curl http://localhost:8000/admin/config
+```
+
+### 索引统计
+
+```bash
+curl http://localhost:8000/admin/stats
+```
+
+---
+
+## 常见问题
+
+### 1. Elasticsearch连接失败
+
+**问题**: `Failed to connect to Elasticsearch`
+
+**解决**:
+```bash
+# 检查ES是否运行
+curl http://localhost:9200
+
+# 检查配置
+cat .env | grep ES_
+```
+
+### 2. 导入数据时内存不足
+
+**问题**: `Out of memory`
+
+**解决**:
+```bash
+# 减少batch size或跳过embedding
+./scripts/ingest.sh 1000 true
+```
+
+### 3. 模型下载失败
+
+**问题**: 模型文件下载超时
+
+**解决**:
+- 检查网络连接
+- 使用国内镜像源
+- 手动下载模型到指定目录
+
+### 4. 翻译不工作
+
+**问题**: 翻译返回原文
+
+**解决**:
+- 检查DEEPL_AUTH_KEY是否正确
+- 如果没有API key，系统会使用mock模式（返回原文）
+
+### 5. 前端无法连接后端
+
+**问题**: CORS错误
+
+**解决**:
+- 确保后端在 http://localhost:8000 运行
+- 检查浏览器控制台错误信息
+
+---
+
+## 开发和调试
+
+### 查看日志
+
+```bash
+# 后端日志
+tail -f logs/backend.log
+
+# 实时日志（如果前台运行）
+./scripts/start_backend.sh
+```
+
+### Python命令行测试
+
+```bash
+# 激活环境
+source /home/tw/miniconda3/etc/profile.d/conda.sh
+conda activate searchengine
+
+# 测试搜索
+python -c "
+from config import ConfigLoader
+from utils import ESClient
+from search import Searcher
+from config.env_config import get_es_config
+
+config_loader = ConfigLoader('config/schema')
+config = config_loader.load_customer_config('customer1')
+
+es_config = get_es_config()
+es_client = ESClient(hosts=[es_config['host']],
+                     username=es_config.get('username'),
+                     password=es_config.get('password'))
+
+searcher = Searcher(config, es_client)
+result = searcher.search('芭比娃娃', size=5)
+
+print(f'找到 {result.total} 个结果')
+for hit in result.hits:
+    print(f'  - {hit[\"_source\"][\"name\"]} (分数: {hit[\"_score\"]:.4f})')
+"
+```
+
+### 重新导入数据
+
+```bash
+# 删除现有索引并重新导入
+./scripts/ingest.sh 1000 true
+```
+
+---
+
+## 性能优化
+
+### 1. 使用embedding缓存
+
+首次生成embedding后会自动缓存到 `.cache/` 目录，后续导入会更快。
+
+### 2. 批量大小调整
+
+```bash
+# 修改批量大小（在ingest_customer1.py中）
+--batch-size 200  # 默认100
+```
+
+### 3. GPU加速
+
+确保CUDA可用以加速embedding生成：
+```bash
+python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"
+```
+
+---
+
+## 项目结构
+
+```
+SearchEngine/
+├── .env                    # 环境配置
+├── setup.sh                # 环境设置脚本
+├── start_all.sh            # 一键启动脚本
+├── scripts/                # 运行脚本
+│   ├── ingest.sh           # 数据导入
+│   ├── start_backend.sh    # 启动后端
+│   └── start_frontend.sh   # 启动前端
+├── frontend/               # Web前端
+│   ├── index.html
+│   └── static/
+├── logs/                   # 日志文件
+├── config/                 # 配置模块
+├── indexer/                # 数据导入
+├── query/                  # 查询处理
+├── search/                 # 搜索引擎
+├── embeddings/             # 向量模型
+└── api/                    # REST API
+```
+
+---
+
+## 支持
+
+遇到问题请查看：
+- **日志**: `logs/backend.log`
+- **API文档**: http://localhost:8000/docs
+- **配置**: `config/schema/customer1_config.yaml`
@@ -0,0 +1,59 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>电商搜索引擎 - SearchEngine Demo</title>
+    <link rel="stylesheet" href="/static/css/style.css">
+</head>
+<body>
+    <div class="container">
+        <header>
+            <h1>🔍 电商搜索引擎</h1>
+            <p class="subtitle">E-Commerce Search Engine - Customer1 Demo</p>
+        </header>
+
+        <div class="search-section">
+            <div class="search-box">
+                <input type="text" id="searchInput" placeholder="输入搜索关键词... (支持中文、英文、俄文)"
+                       onkeypress="handleKeyPress(event)">
+                <button onclick="performSearch()" class="search-button">搜索</button>
+            </div>
+
+            <div class="search-options">
+                <label><input type="checkbox" id="enableTranslation" checked> 启用翻译</label>
+                <label><input type="checkbox" id="enableEmbedding" checked> 启用语义搜索</label>
+                <label><input type="checkbox" id="enableRerank" checked> 启用自定义排序</label>
+                <select id="resultSize">
+                    <option value="10">10条结果</option>
+                    <option value="20">20条结果</option>
+                    <option value="50">50条结果</option>
+                </select>
+            </div>
+
+            <div class="search-examples">
+                <strong>搜索示例：</strong>
+                <button class="example-btn" onclick="setQuery('芭比娃娃')">芭比娃娃</button>
+                <button class="example-btn" onclick="setQuery('toy AND (barbie OR doll)')">布尔查询</button>
+                <button class="example-btn" onclick="setQuery('消防')">消防</button>
+                <button class="example-btn" onclick="setQuery('fire control set')">英文查询</button>
+            </div>
+        </div>
+
+        <div id="loading" class="loading" style="display: none;">
+            <div class="spinner"></div>
+            <p>搜索中...</p>
+        </div>
+
+        <div id="results" class="results-section"></div>
+
+        <div id="queryInfo" class="query-info"></div>
+    </div>
+
+    <footer>
+        <p>SearchEngine © 2025 | API服务地址: <span id="apiUrl">http://localhost:8000</span></p>
+    </footer>
+
+    <script src="/static/js/app.js"></script>
+</body>
+</html>
@@ -0,0 +1,282 @@
+/* SearchEngine Frontend Styles */
+
+* {
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+}
+
+body {
+    font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", "Microsoft YaHei", sans-serif;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    min-height: 100vh;
+    padding: 20px;
+}
+
+.container {
+    max-width: 1200px;
+    margin: 0 auto;
+}
+
+header {
+    text-align: center;
+    color: white;
+    margin-bottom: 40px;
+}
+
+header h1 {
+    font-size: 3em;
+    margin-bottom: 10px;
+}
+
+.subtitle {
+    font-size: 1.2em;
+    opacity: 0.9;
+}
+
+.search-section {
+    background: white;
+    border-radius: 15px;
+    padding: 30px;
+    box-shadow: 0 10px 40px rgba(0,0,0,0.2);
+    margin-bottom: 30px;
+}
+
+.search-box {
+    display: flex;
+    gap: 10px;
+    margin-bottom: 20px;
+}
+
+#searchInput {
+    flex: 1;
+    padding: 15px 20px;
+    font-size: 16px;
+    border: 2px solid #e0e0e0;
+    border-radius: 10px;
+    transition: border-color 0.3s;
+}
+
+#searchInput:focus {
+    outline: none;
+    border-color: #667eea;
+}
+
+.search-button {
+    padding: 15px 40px;
+    font-size: 16px;
+    font-weight: bold;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    border: none;
+    border-radius: 10px;
+    cursor: pointer;
+    transition: transform 0.2s;
+}
+
+.search-button:hover {
+    transform: translateY(-2px);
+}
+
+.search-options {
+    display: flex;
+    gap: 20px;
+    align-items: center;
+    margin-bottom: 15px;
+    flex-wrap: wrap;
+}
+
+.search-options label {
+    display: flex;
+    align-items: center;
+    gap: 5px;
+    cursor: pointer;
+}
+
+.search-options select {
+    padding: 5px 10px;
+    border: 2px solid #e0e0e0;
+    border-radius: 5px;
+    font-size: 14px;
+}
+
+.search-examples {
+    padding: 15px;
+    background: #f5f5f5;
+    border-radius: 10px;
+}
+
+.example-btn {
+    padding: 8px 15px;
+    margin: 5px;
+    background: white;
+    border: 1px solid #ddd;
+    border-radius: 5px;
+    cursor: pointer;
+    transition: all 0.2s;
+}
+
+.example-btn:hover {
+    background: #667eea;
+    color: white;
+    border-color: #667eea;
+}
+
+.loading {
+    text-align: center;
+    padding: 40px;
+    color: white;
+}
+
+.spinner {
+    width: 50px;
+    height: 50px;
+    margin: 0 auto 20px;
+    border: 4px solid rgba(255,255,255,0.3);
+    border-top-color: white;
+    border-radius: 50%;
+    animation: spin 1s linear infinite;
+}
+
+@keyframes spin {
+    to { transform: rotate(360deg); }
+}
+
+.results-section {
+    background: white;
+    border-radius: 15px;
+    padding: 30px;
+    box-shadow: 0 10px 40px rgba(0,0,0,0.2);
+}
+
+.results-header {
+    margin-bottom: 20px;
+    padding-bottom: 15px;
+    border-bottom: 2px solid #e0e0e0;
+}
+
+.results-header h2 {
+    color: #333;
+    margin-bottom: 10px;
+}
+
+.results-stats {
+    color: #666;
+    font-size: 14px;
+}
+
+.result-item {
+    padding: 20px;
+    margin-bottom: 15px;
+    border: 1px solid #e0e0e0;
+    border-radius: 10px;
+    transition: all 0.3s;
+}
+
+.result-item:hover {
+    box-shadow: 0 5px 15px rgba(0,0,0,0.1);
+    border-color: #667eea;
+}
+
+.result-header {
+    display: flex;
+    justify-content: space-between;
+    align-items: start;
+    margin-bottom: 10px;
+}
+
+.result-title {
+    font-size: 18px;
+    font-weight: bold;
+    color: #333;
+    margin-bottom: 5px;
+}
+
+.result-score {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    padding: 5px 12px;
+    border-radius: 20px;
+    font-size: 12px;
+    font-weight: bold;
+}
+
+.result-meta {
+    display: flex;
+    gap: 15px;
+    flex-wrap: wrap;
+    font-size: 14px;
+    color: #666;
+    margin-bottom: 10px;
+}
+
+.result-meta span {
+    background: #f5f5f5;
+    padding: 4px 10px;
+    border-radius: 5px;
+}
+
+.result-image {
+    max-width: 150px;
+    max-height: 150px;
+    border-radius: 8px;
+    margin-top: 10px;
+}
+
+.query-info {
+    background: white;
+    border-radius: 15px;
+    padding: 20px;
+    margin-top: 20px;
+    box-shadow: 0 10px 40px rgba(0,0,0,0.2);
+}
+
+.query-info h3 {
+    color: #333;
+    margin-bottom: 15px;
+}
+
+.info-grid {
+    display: grid;
+    grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+    gap: 15px;
+}
+
+.info-item {
+    padding: 15px;
+    background: #f5f5f5;
+    border-radius: 8px;
+}
+
+.info-item strong {
+    display: block;
+    color: #667eea;
+    margin-bottom: 5px;
+}
+
+footer {
+    text-align: center;
+    color: white;
+    margin-top: 40px;
+    padding: 20px;
+    opacity: 0.8;
+}
+
+.error-message {
+    background: #ff4444;
+    color: white;
+    padding: 20px;
+    border-radius: 10px;
+    margin-bottom: 20px;
+}
+
+.no-results {
+    text-align: center;
+    padding: 40px;
+    color: #666;
+}
+
+.no-results h3 {
+    font-size: 24px;
+    margin-bottom: 10px;
+}
@@ -0,0 +1,237 @@
+// SearchEngine Frontend JavaScript
+
+// API endpoint
+const API_BASE_URL = 'http://localhost:8000';
+
+// Update API URL display
+document.getElementById('apiUrl').textContent = API_BASE_URL;
+
+// Handle Enter key in search input
+function handleKeyPress(event) {
+    if (event.key === 'Enter') {
+        performSearch();
+    }
+}
+
+// Set query from example buttons
+function setQuery(query) {
+    document.getElementById('searchInput').value = query;
+    performSearch();
+}
+
+// Perform search
+async function performSearch() {
+    const query = document.getElementById('searchInput').value.trim();
+
+    if (!query) {
+        alert('请输入搜索关键词');
+        return;
+    }
+
+    // Get options
+    const size = parseInt(document.getElementById('resultSize').value);
+    const enableTranslation = document.getElementById('enableTranslation').checked;
+    const enableEmbedding = document.getElementById('enableEmbedding').checked;
+    const enableRerank = document.getElementById('enableRerank').checked;
+
+    // Show loading
+    document.getElementById('loading').style.display = 'block';
+    document.getElementById('results').innerHTML = '';
+    document.getElementById('queryInfo').innerHTML = '';
+
+    try {
+        const response = await fetch(`${API_BASE_URL}/search/`, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                query: query,
+                size: size,
+                enable_translation: enableTranslation,
+                enable_embedding: enableEmbedding,
+                enable_rerank: enableRerank
+            })
+        });
+
+        if (!response.ok) {
+            throw new Error(`HTTP ${response.status}: ${response.statusText}`);
+        }
+
+        const data = await response.json();
+        displayResults(data);
+        displayQueryInfo(data.query_info);
+
+    } catch (error) {
+        console.error('Search error:', error);
+        document.getElementById('results').innerHTML = `
+            <div class="error-message">
+                <strong>搜索出错:</strong> ${error.message}
+                <br><br>
+                <small>请确保后端服务正在运行 (http://localhost:8000)</small>
+            </div>
+        `;
+    } finally {
+        document.getElementById('loading').style.display = 'none';
+    }
+}
+
+// Display search results
+function displayResults(data) {
+    const resultsDiv = document.getElementById('results');
+
+    if (!data.hits || data.hits.length === 0) {
+        resultsDiv.innerHTML = `
+            <div class="no-results">
+                <h3>😔 没有找到结果</h3>
+                <p>请尝试其他关键词</p>
+            </div>
+        `;
+        return;
+    }
+
+    let html = `
+        <div class="results-header">
+            <h2>搜索结果</h2>
+            <div class="results-stats">
+                找到 <strong>${data.total}</strong> 个结果，
+                耗时 <strong>${data.took_ms}</strong> 毫秒，
+                最高分 <strong>${data.max_score.toFixed(4)}</strong>
+            </div>
+        </div>
+    `;
+
+    data.hits.forEach((hit, index) => {
+        const source = hit._source;
+        const score = hit._custom_score || hit._score;
+
+        html += `
+            <div class="result-item">
+                <div class="result-header">
+                    <div>
+                        <div class="result-title">${index + 1}. ${escapeHtml(source.name || 'N/A')}</div>
+                        ${source.enSpuName ? `<div style="color: #666; font-size: 14px;">${escapeHtml(source.enSpuName)}</div>` : ''}
+                        ${source.ruSkuName ? `<div style="color: #999; font-size: 13px;">${escapeHtml(source.ruSkuName)}</div>` : ''}
+                    </div>
+                    <div class="result-score">
+                        ${score.toFixed(4)}
+                    </div>
+                </div>
+
+                <div class="result-meta">
+                    ${source.categoryName ? `<span>📁 ${escapeHtml(source.categoryName)}</span>` : ''}
+                    ${source.brandName ? `<span>🏷️ ${escapeHtml(source.brandName)}</span>` : ''}
+                    ${source.supplierName ? `<span>🏭 ${escapeHtml(source.supplierName)}</span>` : ''}
+                    ${source.create_time ? `<span>📅 ${formatDate(source.create_time)}</span>` : ''}
+                </div>
+
+                ${source.imageUrl ? `
+                    <img src="${escapeHtml(source.imageUrl)}"
+                         alt="${escapeHtml(source.name)}"
+                         class="result-image"
+                         onerror="this.style.display='none'">
+                ` : ''}
+
+                <div style="margin-top: 10px; font-size: 12px; color: #999;">
+                    ID: ${source.skuId || 'N/A'}
+                </div>
+            </div>
+        `;
+    });
+
+    resultsDiv.innerHTML = html;
+}
+
+// Display query processing information
+function displayQueryInfo(queryInfo) {
+    if (!queryInfo) return;
+
+    const queryInfoDiv = document.getElementById('queryInfo');
+
+    let html = `
+        <h3>查询处理信息</h3>
+        <div class="info-grid">
+            <div class="info-item">
+                <strong>原始查询</strong>
+                ${escapeHtml(queryInfo.original_query || 'N/A')}
+            </div>
+            <div class="info-item">
+                <strong>重写后查询</strong>
+                ${escapeHtml(queryInfo.rewritten_query || 'N/A')}
+            </div>
+            <div class="info-item">
+                <strong>检测语言</strong>
+                ${getLanguageName(queryInfo.detected_language)}
+            </div>
+            <div class="info-item">
+                <strong>查询域</strong>
+                ${escapeHtml(queryInfo.domain || 'default')}
+            </div>
+        </div>
+    `;
+
+    // Show translations if any
+    if (queryInfo.translations && Object.keys(queryInfo.translations).length > 0) {
+        html += '<h4 style="margin-top: 20px; margin-bottom: 10px;">翻译结果</h4><div class="info-grid">';
+        for (const [lang, translation] of Object.entries(queryInfo.translations)) {
+            if (translation) {
+                html += `
+                    <div class="info-item">
+                        <strong>${getLanguageName(lang)}</strong>
+                        ${escapeHtml(translation)}
+                    </div>
+                `;
+            }
+        }
+        html += '</div>';
+    }
+
+    // Show embedding info
+    if (queryInfo.has_vector) {
+        html += `
+            <div style="margin-top: 15px; padding: 10px; background: #e8f5e9; border-radius: 5px;">
+                ✓ 使用了语义向量搜索
+            </div>
+        `;
+    }
+
+    queryInfoDiv.innerHTML = html;
+}
+
+// Helper functions
+function escapeHtml(text) {
+    if (!text) return '';
+    const div = document.createElement('div');
+    div.textContent = text;
+    return div.innerHTML;
+}
+
+function formatDate(dateStr) {
+    try {
+        const date = new Date(dateStr);
+        return date.toLocaleDateString('zh-CN');
+    } catch {
+        return dateStr;
+    }
+}
+
+function getLanguageName(code) {
+    const names = {
+        'zh': '中文',
+        'en': 'English',
+        'ru': 'Русский',
+        'ar': 'العربية',
+        'ja': '日本語',
+        'unknown': '未知'
+    };
+    return names[code] || code;
+}
+
+// Initialize page
+document.addEventListener('DOMContentLoaded', function() {
+    console.log('SearchEngine Frontend loaded');
+    console.log('API Base URL:', API_BASE_URL);
+
+    // Focus on search input
+    document.getElementById('searchInput').focus();
+});
@@ -0,0 +1,40 @@
+#!/usr/bin/env python3
+"""
+Simple HTTP server for SearchEngine frontend.
+"""
+
+import http.server
+import socketserver
+import os
+import sys
+
+# Change to frontend directory
+frontend_dir = os.path.join(os.path.dirname(__file__), '../frontend')
+os.chdir(frontend_dir)
+
+PORT = 8080
+
+class MyHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):
+    """Custom request handler with CORS support."""
+
+    def end_headers(self):
+        # Add CORS headers
+        self.send_header('Access-Control-Allow-Origin', '*')
+        self.send_header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS')
+        self.send_header('Access-Control-Allow-Headers', 'Content-Type')
+        super().end_headers()
+
+    def do_OPTIONS(self):
+        self.send_response(200)
+        self.end_headers()
+
+if __name__ == '__main__':
+    with socketserver.TCPServer(("", PORT), MyHTTPRequestHandler) as httpd:
+        print(f"Frontend server started at http://localhost:{PORT}")
+        print(f"Serving files from: {os.getcwd()}")
+        print("\nPress Ctrl+C to stop the server")
+        try:
+            httpd.serve_forever()
+        except KeyboardInterrupt:
+            print("\nServer stopped")
+            sys.exit(0)
@@ -0,0 +1,50 @@
+#!/bin/bash
+
+# Data Ingestion Script for Customer1
+
+set -e
+
+cd "$(dirname "$0")/.."
+source /home/tw/miniconda3/etc/profile.d/conda.sh
+conda activate searchengine
+
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+NC='\033[0m'
+
+echo -e "${GREEN}========================================${NC}"
+echo -e "${GREEN}Customer1 Data Ingestion${NC}"
+echo -e "${GREEN}========================================${NC}"
+
+# Default values
+LIMIT=${1:-1000}
+SKIP_EMBEDDINGS=${2:-false}
+
+echo -e "\n${YELLOW}Configuration:${NC}"
+echo "  Limit: $LIMIT documents"
+echo "  Skip embeddings: $SKIP_EMBEDDINGS"
+
+CSV_FILE="data/customer1/goods_with_pic.5years_congku.csv.shuf.1w"
+
+if [ ! -f "$CSV_FILE" ]; then
+    echo "Error: CSV file not found: $CSV_FILE"
+    exit 1
+fi
+
+# Build command
+CMD="python data/customer1/ingest_customer1.py \
+  --csv $CSV_FILE \
+  --limit $LIMIT \
+  --recreate-index \
+  --batch-size 100"
+
+if [ "$SKIP_EMBEDDINGS" = "true" ]; then
+    CMD="$CMD --skip-embeddings"
+fi
+
+echo -e "\n${YELLOW}Starting ingestion...${NC}"
+eval $CMD
+
+echo -e "\n${GREEN}========================================${NC}"
+echo -e "${GREEN}Ingestion Complete!${NC}"
+echo -e "${GREEN}========================================${NC}"
@@ -0,0 +1,34 @@
+#!/bin/bash
+
+# Start Backend API Service
+
+set -e
+
+cd "$(dirname "$0")/.."
+source /home/tw/miniconda3/etc/profile.d/conda.sh
+conda activate searchengine
+
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+NC='\033[0m'
+
+echo -e "${GREEN}========================================${NC}"
+echo -e "${GREEN}Starting Backend API Service${NC}"
+echo -e "${GREEN}========================================${NC}"
+
+# Load config
+source .env
+
+echo -e "\n${YELLOW}Configuration:${NC}"
+echo "  Customer: $CUSTOMER_ID"
+echo "  API Host: $API_HOST"
+echo "  API Port: $API_PORT"
+echo "  ES Host: $ES_HOST"
+
+echo -e "\n${YELLOW}Starting service...${NC}"
+python -m api.app \
+  --host $API_HOST \
+  --port $API_PORT \
+  --customer $CUSTOMER_ID \
+  --es-host $ES_HOST
+
@@ -0,0 +1,28 @@
+#!/bin/bash
+
+# Start Frontend Server
+
+set -e
+
+cd "$(dirname "$0")/.."
+source /home/tw/miniconda3/etc/profile.d/conda.sh
+conda activate searchengine
+
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+NC='\033[0m'
+
+echo -e "${GREEN}========================================${NC}"
+echo -e "${GREEN}Starting Frontend Server${NC}"
+echo -e "${GREEN}========================================${NC}"
+
+PORT=8080
+
+echo -e "\n${YELLOW}Frontend will be available at:${NC}"
+echo -e "  ${GREEN}http://localhost:$PORT${NC}"
+echo ""
+echo -e "${YELLOW}Make sure the backend API is running at:${NC}"
+echo -e "  ${GREEN}http://localhost:8000${NC}"
+echo ""
+
+python scripts/frontend_server.py
@@ -0,0 +1,80 @@
+#!/bin/bash
+
+# SearchEngine Setup and Startup Script
+# This script sets up the environment and starts all services
+
+set -e  # Exit on error
+
+# Colors for output
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+NC='\033[0m' # No Color
+
+echo -e "${GREEN}========================================${NC}"
+echo -e "${GREEN}SearchEngine Setup Script${NC}"
+echo -e "${GREEN}========================================${NC}"
+
+# Change to project directory
+cd "$(dirname "$0")"
+PROJECT_ROOT=$(pwd)
+
+echo -e "\n${YELLOW}Step 1: Setting up Conda environment${NC}"
+# Check if conda is available
+if ! command -v conda &> /dev/null; then
+    echo -e "${RED}Error: conda not found. Please install Miniconda or Anaconda${NC}"
+    exit 1
+fi
+
+# Source conda
+source /home/tw/miniconda3/etc/profile.d/conda.sh
+
+# Check if environment exists
+if conda env list | grep -q "searchengine"; then
+    echo -e "${GREEN}Environment 'searchengine' already exists${NC}"
+    conda activate searchengine
+else
+    echo -e "${YELLOW}Creating conda environment 'searchengine'...${NC}"
+    conda env create -f environment.yml
+    conda activate searchengine
+    echo -e "${GREEN}Environment created successfully!${NC}"
+fi
+
+# Verify environment
+echo -e "\n${YELLOW}Current Python version:${NC}"
+python --version
+
+echo -e "\n${YELLOW}Step 2: Loading configuration${NC}"
+# Check if .env exists
+if [ ! -f ".env" ]; then
+    echo -e "${YELLOW}Creating .env from .env.example...${NC}"
+    cp .env.example .env
+    echo -e "${GREEN}.env file created. Please update it with your actual configuration.${NC}"
+fi
+
+# Display configuration
+echo -e "${GREEN}Configuration loaded:${NC}"
+python -c "from config.env_config import print_config; print_config()"
+
+echo -e "\n${YELLOW}Step 3: Checking Elasticsearch connection${NC}"
+python -c "
+from config.env_config import get_es_config
+from utils.es_client import ESClient
+es_config = get_es_config()
+client = ESClient(hosts=[es_config['host']], username=es_config.get('username'), password=es_config.get('password'))
+if client.ping():
+    print('✓ Elasticsearch is reachable')
+else:
+    print('✗ Elasticsearch connection failed')
+    exit(1)
+"
+
+echo -e "\n${GREEN}========================================${NC}"
+echo -e "${GREEN}Setup Complete!${NC}"
+echo -e "${GREEN}========================================${NC}"
+echo ""
+echo -e "Next steps:"
+echo -e "  1. Ingest data: ${YELLOW}./scripts/ingest.sh${NC}"
+echo -e "  2. Start backend: ${YELLOW}./scripts/start_backend.sh${NC}"
+echo -e "  3. Start frontend: ${YELLOW}./scripts/start_frontend.sh${NC}"
+echo ""
@@ -0,0 +1,99 @@
+#!/bin/bash
+
+# One-click startup script for SearchEngine
+# This script starts everything you need
+
+set -e
+
+cd "$(dirname "$0")"
+
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+RED='\033[0;31m'
+NC='\033[0m'
+
+echo -e "${GREEN}========================================${NC}"
+echo -e "${GREEN}SearchEngine一键启动脚本${NC}"
+echo -e "${GREEN}========================================${NC}"
+
+# Step 1: Setup environment
+echo -e "\n${YELLOW}Step 1/4: 设置环境${NC}"
+./setup.sh
+
+# Step 2: Check if data is already ingested
+echo -e "\n${YELLOW}Step 2/4: 检查数据${NC}"
+source /home/tw/miniconda3/etc/profile.d/conda.sh
+conda activate searchengine
+
+# Check if index exists
+INDEX_EXISTS=$(python -c "
+from config.env_config import get_es_config
+from utils.es_client import ESClient
+from config import ConfigLoader
+
+es_config = get_es_config()
+es_client = ESClient(hosts=[es_config['host']], username=es_config.get('username'), password=es_config.get('password'))
+
+config_loader = ConfigLoader('config/schema')
+config = config_loader.load_customer_config('customer1')
+
+if es_client.index_exists(config.es_index_name):
+    doc_count = es_client.count(config.es_index_name)
+    print(f'{doc_count}')
+else:
+    print('0')
+" 2>/dev/null || echo "0")
+
+if [ "$INDEX_EXISTS" = "0" ]; then
+    echo -e "${YELLOW}索引不存在，开始导入数据...${NC}"
+    echo -e "${YELLOW}注意: 首次导入会下载模型文件，可能需要10-30分钟${NC}"
+    echo -e "${YELLOW}导入1000条数据进行快速测试（跳过embedding以加快速度）${NC}"
+    ./scripts/ingest.sh 1000 true
+else
+    echo -e "${GREEN}数据已存在，包含 $INDEX_EXISTS 条文档${NC}"
+fi
+
+# Step 3: Start backend in background
+echo -e "\n${YELLOW}Step 3/4: 启动后端服务${NC}"
+echo -e "${YELLOW}后端服务将在后台运行...${NC}"
+nohup ./scripts/start_backend.sh > logs/backend.log 2>&1 &
+BACKEND_PID=$!
+echo $BACKEND_PID > logs/backend.pid
+echo -e "${GREEN}后端服务已启动 (PID: $BACKEND_PID)${NC}"
+echo -e "${GREEN}日志文件: logs/backend.log${NC}"
+
+# Wait for backend to start
+echo -e "${YELLOW}等待后端服务启动...${NC}"
+sleep 5
+
+# Check if backend is running
+if curl -s http://localhost:8000/admin/health > /dev/null 2>&1; then
+    echo -e "${GREEN}✓ 后端服务运行正常${NC}"
+else
+    echo -e "${RED}✗ 后端服务启动失败，请检查日志: logs/backend.log${NC}"
+    exit 1
+fi
+
+# Step 4: Start frontend
+echo -e "\n${YELLOW}Step 4/4: 启动前端服务${NC}"
+echo -e "${GREEN}========================================${NC}"
+echo -e "${GREEN}所有服务启动完成!${NC}"
+echo -e "${GREEN}========================================${NC}"
+echo ""
+echo -e "访问地址:"
+echo -e "  ${GREEN}前端界面: http://localhost:8080${NC}"
+echo -e "  ${GREEN}后端API: http://localhost:8000${NC}"
+echo -e "  ${GREEN}API文档: http://localhost:8000/docs${NC}"
+echo ""
+echo -e "日志文件:"
+echo -e "  后端: logs/backend.log"
+echo ""
+echo -e "停止服务:"
+echo -e "  后端: kill \$(cat logs/backend.pid)"
+echo -e "  前端: Ctrl+C"
+echo ""
+echo -e "${YELLOW}正在启动前端服务...${NC}"
+echo -e "${YELLOW}按 Ctrl+C 停止前端服务${NC}"
+echo ""
+
+./scripts/start_frontend.sh