Add premiumproducts-db skill
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---
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name: premiumproducts-db
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description: premiumproducts.products MongoDB 数据库操作手册 — 连接、Schema、查询、更新、变参产品集创建、CDP+FlairGS 产品资料补齐流水线。
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version: 1.0
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category: cross-border-ecommerce
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tags: [premiumproducts, mongodb, product-pool, variants]
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---
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# premiumproducts.products 数据库操作手册
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## 连接信息
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| 项目 | 值 |
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|------|-----|
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| 地址 | 43.134.190.229:27018 |
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| 用户 | root |
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| 密码 | MongoDB8-2026! |
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| 数据库 | premiumproducts |
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| 集合 | products |
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| Python | `pymongo.MongoClient('mongodb://root:MongoDB8-2026!@43.134.190.229:27018/')` |
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## Schema 核心字段
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### 必填字段
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- `product_code` — 8位产品编码（如 1LTDS5ZY, EE9A114A），唯一索引
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- `name` — 中文产品名称（atomlisting 产品列表显示）
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- `source_url` — 1688/detail 源链接
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- `images` — `[{url, is_primary}]` 对象数组，非字符串数组
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- `translations` — 嵌套 dict：`{zh: {name, description}, en: {name, description}, ru: {name, description}}`
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- `price` 或 `supplier_price` — 数字
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### 推荐字段
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- `category` — 产品类目
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- `brand` — 品牌
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- `material` — 材质
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- `color` / `colors` — 颜色
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- `weight` / `weight_g` — 重量(g)
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- `specs` — 规格 dict
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- `variants` — SKU 变体数组 `[{name, price, stock}]`
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- `store` — 店铺信息 `{name, years, return_rate, service_score, shipping_rate, positive_rate}`
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- `moq` — 最小起订量
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- `sku` — SKU 字符串
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- `shipping` — 发货信息
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- `price_range` — `{min, max}`
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- `packaging` — 包装信息
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### 变参产品集字段
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- `variant_group` — 父产品 code（如 EE9A114A）
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- `variant_of` — 所属父产品
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- `variant_type` — 变参类型（如 color）
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- `variant_value` — 变参值（如 橙色）
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- `supplier_price` — 供应商价格
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- `supplier_stock` — 供应商库存
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### 父产品标记
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- `is_variant_group: true`
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- `variant_codes` — 子产品 code 数组
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- `variant_count` — 子产品数量
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## 常见操作
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### 查询
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```python
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from pymongo import MongoClient
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client = MongoClient('mongodb://root:MongoDB8-2026!@43.134.190.229:27018/')
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db = client['premiumproducts']
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# 按 code 查询
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doc = db['products'].find_one({'product_code': '1LTDS5ZY'})
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# 按变参组查询
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variants = list(db['products'].find({'variant_group': 'EE9A114A'}))
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# 查找缺失字段
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docs = list(db['products'].find({'name': {'$exists': False}}))
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```
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### 更新
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```python
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result = db['products'].update_one(
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{'product_code': '1LTDS5ZY'},
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{'$set': {'name': '...', 'price': 42.20, 'images': [...]}}
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)
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```
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### 字段改名（两步操作，pymongo 某些版本不支持 $rename）
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```python
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# Step 1: $set 新字段
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db['products'].update_one({'product_code': code}, {'$set': {'supplier_price': old_val}})
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# Step 2: $unset 旧字段
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db['products'].update_one({'product_code': code}, {'$unset': {'price': ''}})
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```
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## 产品资料补齐流水线
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### 流程
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1. MongoDB 查询产品 → 获取 `source_url`
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2. Desktop CDP → `/cdp/navigate` 1688 详情页
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3. `/cdp/attach` → `/cdp/evaluate` 提取页面数据
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4. 解析：`document.title`, `document.body.innerText`, 图片扫描
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5. 用 FlairGS VL 分析图片颜色/特征（可选）
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6. 组装文档并 `update_one` 写入 MongoDB
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### CDP 提取模板
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```python
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import urllib.request, json, time
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K = chr(66)+chr(105)+chr(110)+chr(103)+chr(50)+chr(48)+chr(50)+chr(54)+chr(67)+chr(97)+chr(111)+chr(36)+chr(36)+chr(36)
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BASE = 'http://127.0.0.1:9228'
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SLOT = 'desktop-mrbgzsdn'
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SH = {'Authorization': f'Bearer {K}', 'Content-Type': 'application/json', 'X-Desktop-Id': SLOT}
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def ev(tid, expr):
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body = json.dumps({'expression': expr}).encode()
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req = urllib.request.Request(f'{BASE}/cdp/evaluate?targetId={tid}', data=body, method='POST')
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for k, v in SH.items(): req.add_header(k, v)
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resp = json.loads(urllib.request.urlopen(req, timeout=20).read())
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r = resp.get('result', {})
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if isinstance(r, dict) and 'result' in r:
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return r['result'].get('value', r['result'])
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return r
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# 1. Navigate (always first)
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body = json.dumps({'url': source_url}).encode()
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req = urllib.request.Request(f'{BASE}/cdp/navigate', data=body, method='POST')
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for k, v in SH.items(): req.add_header(k, v)
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urllib.request.urlopen(req, timeout=30)
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time.sleep(5)
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# 2. Attach
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req = urllib.request.Request(f'{BASE}/cdp/attach', data=b'{}', method='POST')
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for k, v in SH.items(): req.add_header(k, v)
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tid = json.loads(urllib.request.urlopen(req, timeout=60).read())['targetId']
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# 3. Extract
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title = ev(tid, 'document.title')
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body_text = ev(tid, 'document.body.innerText.substring(0,4000)')
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```
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### 图片提取
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```python
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# CDP 表达式过滤器禁止 Array.from/map/filter/for 循环，只能用逐个索引扫描
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total = ev(tid, 'document.querySelectorAll("img").length')
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urls = []
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for i in range(total):
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src = ev(tid, f'document.querySelectorAll("img")[{i}] ? document.querySelectorAll("img")[{i}].src : ""')
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w = ev(tid, f'document.querySelectorAll("img")[{i}] ? document.querySelectorAll("img")[{i}].width : 0')
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if src and 'alicdn' in str(src) and isinstance(w, (int, float)) and w > 100:
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urls.append({'url': str(src).replace('_.webp', ''), 'is_primary': len(urls) == 0})
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```
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### FlairGS VL 分析
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```python
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import base64, io
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from PIL import Image
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key = '8Ax4TyZc66qrZgXK'
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api = 'http://43.160.244.125:17870/api/analyze'
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# 下载图片 → 转 RGB → 调 API
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img_data = urllib.request.urlopen(img_url).read()
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img = Image.open(io.BytesIO(img_data)).convert('RGB')
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img.thumbnail((512, 512), Image.LANCZOS)
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buf = io.BytesIO()
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img.save(buf, format='JPEG', quality=80)
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b64 = base64.b64encode(buf.getvalue()).decode()
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body = json.dumps({'base64': b64, 'prompt': '用中文描述商品颜色'}).encode()
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req = urllib.request.Request(api, data=body, method='POST')
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req.add_header('X-API-Key', key)
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req.add_header('Content-Type', 'application/json')
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desc = json.loads(urllib.request.urlopen(req, timeout=60).read())['description']
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```
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## 数据格式陷阱
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1. ⚠️ `images` 必须是 `[{url, is_primary}]` 对象数组，不能是字符串数组
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2. ⚠️ `translations` 是嵌套 dict `{zh: {name, description}}`，不能是字符串
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3. ⚠️ `name` 必填 — atomlisting 产品列表用此字段，缺失显示 "Unnamed"
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4. ⚠️ atomlisting 双 API：`/remote` 读 `translations.zh.name`，`/premium-products` 读 `name`，两个都要设
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5. ⚠️ `product_code` 统一 8 位十六进制，不带前缀
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6. ⚠️ pymongo 某些版本 `$rename` 不可用，用 `$set` + `$unset` 两步改名
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7. ⚠️ 测试/占位链接的产品（source_url 含 test1/test2/test3）主动删除
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8. ⚠️ CDP 表达式过滤器禁止 async/for/forEach/Array.from，索引扫描用 while 递减循环
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9. ⚠️ FlairGS 图片必须 `.convert('RGB')` 后再 JPEG 编码，否则返回空描述
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## 变参产品集创建模式
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当产品有多个颜色/SKU 变体时：
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1. 每个变体建独立 product_code
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2. 分配到对应颜色的图片（用 FlairGS 识别）
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3. 统一设置 `variant_group`, `variant_of`, `variant_type`, `variant_value`
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4. 使用 `supplier_price` 和 `supplier_stock`
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5. 父产品标记 `is_variant_group: true`, `variant_codes: [...]`
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## FlairGS 连通性
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- 优先：`http://43.160.244.125:17870` (FRP)
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- 备用：Desktop CDP → `http://192.168.9.105:7870`
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- API Key: `8Ax4TyZc66qrZgXK`
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- 端点：`POST /api/analyze` — 字段名 `base64` (非 `image_base64`)
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- 模型：GS3/qwen3-vl:8b，典型延迟 7-8s
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