Phase 1 MVP: crawl 10 high-quality oshwhub projects into LFS

Why:
- Charles 指定：先爬 10 个高质量项目存 Gitea LFS，一个项目一个文件夹，
  保留原文件和 URL。先以小批量验证 schema + LFS 流水线，放量前再拍板
  存储规模。

What:
- crawlers/oshwhub: 列表 API (`/api/project?sort=hot`) + SSR HTML 解析，
  一次性产出 metadata / description / cover / files / _urls
- schemas/project.schema.json: 跨源统一 schema
- docs/sources/oshwhub.md: API 入口 / 字段映射 / 陷阱调研
- pyproject.toml: httpx[http2] 单依赖
- .gitattributes: data/raw/**/files/** 一律走 LFS（规则写窄，避免误伤 schemas/*.json 等）
- .gitignore: 移除 data/raw/* 排除（改走 LFS 入库）

10 个项目覆盖：调试器 / 加热台 / 盖革计数器 / 数控电源 / 焊台 /
智能手表 / USB 测电流 / ZVS 感应加热 / AI 开发板 / 红外热成像。
共 52 附件 ≈ 524 MB 入 LFS，筛选判据 grade=4 & likes>=100 & 多样性。

Known gaps（见 plan.md § Phase 1.4）：
- EasyEDA 源 JSON 需登录 (u.lceda.cn)，v0.1 跳过
- fs-web-stream.jlc.com 的工程源下载未测
- scripts/validate.py 自动 schema 校验未实现

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

data/raw/oshwhub/f974b06d9c01470bb319e7df6d4512c9/metadata.json

@@ -0,0 +1,63 @@
+{
+  "source": "oshwhub",
+  "source_url": "https://oshwhub.com/diy17102800/tu-teng-zvs",
+  "project_id": "f974b06d9c01470bb319e7df6d4512c9",
+  "title": "大功率感应加热2500W 增强型ZVS",
+  "description_short": "测试已成功",
+  "description_path": "description.md",
+  "author": {
+    "username": "diy17102800",
+    "display_name": "金石之声",
+    "user_id": "de940107caa34d989e9485cc41026732"
+  },
+  "license": "TAPR Open Hardware License",
+  "tags": [],
+  "created_at": "2023-02-14T16:30:50.000Z",
+  "updated_at": "2025-10-27T07:11:41.000Z",
+  "published_at": "2024-05-20T02:40:14.000Z",
+  "crawled_at": "2026-04-23T11:30:55.186691+00:00",
+  "metrics": {
+    "likes": 355,
+    "stars": 708,
+    "forks": 378,
+    "views": 61550,
+    "watch": 0,
+    "comments": 265
+  },
+  "cover": {
+    "url": "https://image.lceda.cn/pullimage/Qf1Gu6y5cpQQQ5YzNoFf4gqZYwNCOzKYlO9eerXB.jpeg",
+    "path": "cover.jpeg"
+  },
+  "files": [
+    {
+      "name": "测试视频.mp4",
+      "url": "https://image.lceda.cn/attachments/2023/3/hcSO16Po6ZKhmHnR3M2UJ2ttbc4jNDE0FthmsFE0.mp4",
+      "original_id": "e0ef95cfceb04edc9076a4e8f5ebd9dd",
+      "ext": "mp4",
+      "mime": "video/mp4",
+      "size": 8101940,
+      "md5": "229f35937d3b13a0a862b7d47654eb0f",
+      "path": "files/测试视频.mp4",
+      "sha256": "613b326cb8c3c222c955c259968b4fac5dd31daa5a93e85e53a55b24ef30c320"
+    },
+    {
+      "name": "1133.mp4",
+      "url": "https://image.lceda.cn/attachments/2024/5/BiyaOevIDxQtW4RbBjuS1FZ3P2cDsGBB1M5mf2aN.mp4",
+      "original_id": "40cab71898a7457b92f5e6ef7c8a8bd5",
+      "ext": "mp4",
+      "mime": "video/mp4",
+      "size": 1100753,
+      "md5": "3dc3d5f4c556e3c057eede3cfbcefb83",
+      "path": "files/1133.mp4",
+      "sha256": "7a707feb0a82435b59439552f211075dafeab39aa5d490e5195d861f75515126"
+    }
+  ],
+  "raw_fields": {
+    "path": "diy17102800/tu-teng-zvs",
+    "grade": 4,
+    "origin": "std",
+    "public": true,
+    "publish": true,
+    "skipped_files": []
+  }
+}