docs(claude): restructure documentation management and add feedback system
- Restructure §8 from "文档沉淀规则" to "文档管理规则" with 4 subsections - Add docs/ structure with features/ and knowledge-base/ directories - Add feature documentation template with 7 sections (概述/设计初衷/技术设计/预期作用/实际效果/演化路线/头脑风暴) - Add feature update trigger matrix (新增/修改/完成/问题/反馈) - Add documentation quality checklist - Add §16
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@@ -86,10 +86,11 @@ c8202d0 feat(viking): add local server management for privacy-first deployment
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- [x] 火山引擎 API 密钥配置
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- [x] OpenViking 服务器启动验证
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- [x] 基础 API 测试(健康检查、会话创建、消息添加)
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- [x] **火山引擎 Embedding 模型激活** (`ep-20260316102010-cq422`)
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- [x] **向量搜索功能验证** ✅
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### 进行中
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- [ ] 火山引擎 Embedding 模型激活
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- [ ] 多 Agent 协作 UI 产品化
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### 待办
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@@ -110,48 +111,30 @@ c8202d0 feat(viking): add local server management for privacy-first deployment
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| 消息添加 | ✅ | `POST /api/v1/sessions/{id}/messages` |
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| 向量搜索 | ⚠️ | 需要激活 Embedding 模型 |
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### 待解决:火山引擎 Embedding 模型激活
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### ✅ 已解决:火山引擎 Embedding 模型激活
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**错误信息**:
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```
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The model or endpoint doubao-embedding does not exist or you do not have access to it.
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**Endpoint ID**: `ep-20260316102010-cq422`
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**配置文件** (`~/.openviking/ov.conf`):
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```json
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{
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"embedding": {
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"dense": {
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"api_base": "https://ark.cn-beijing.volces.com/api/v3",
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"api_key": "3739b6b2-2bff-4a13-9f82-c0674dd4a05e",
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"provider": "volcengine",
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"model": "ep-20260316102010-cq422",
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"dimension": 1024
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}
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}
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}
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```
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**解决方案**:
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1. **登录火山引擎控制台**:
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https://console.volcengine.com/ark
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2. **激活 Embedding 模型**:
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- 进入「模型推理」→「模型服务」
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- 搜索并激活以下任一模型:
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- `Doubao-Embedding` (推荐)
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- `Doubao-Embedding-Large`
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3. **获取 Endpoint ID**:
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- 激活后,复制模型的 Endpoint ID
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- 格式类似:`ep-xxxxxxxxxxxx`
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4. **更新配置文件** (`~/.openviking/ov.conf`):
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```json
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{
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"embedding": {
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"dense": {
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"api_base": "https://ark.cn-beijing.volces.com/api/v3",
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"api_key": "your-api-key",
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"provider": "volcengine",
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"model": "ep-xxxxxxxxxxxx",
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"dimension": 1024
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}
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}
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}
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```
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5. **重启服务器**:
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```bash
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taskkill //F //IM openviking-server.exe
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cd ~/.openviking && openviking-server
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```
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**验证结果**:
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- 向量搜索 API: ✅ 正常
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- 会话创建: ✅ 正常
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- 消息添加: ✅ 正常
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- TypeScript 测试: ✅ 21 passed
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### 备选方案:使用 OpenAI Embedding
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