chore: clean up old plan files and update gitignore
- Add build artifacts to .gitignore (binaries/, *.exe, *.pdb) - Update WORK_SUMMARY with latest progress - Remove outdated plan files (moved to docs/archive/plans/) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
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.gitignore
vendored
5
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vendored
@@ -35,3 +35,8 @@ Thumbs.db
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# Tauri
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desktop/src-tauri/target/
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desktop/dist/
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# Build artifacts
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desktop/src-tauri/binaries/
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*.exe
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*.pdb
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@@ -63,6 +63,10 @@ docs/
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| Viking Adapter 测试 | ✅ 21 passed |
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| Rust 测试 | ✅ 10 passed |
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| Cargo Build | ✅ 成功 |
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| OpenViking 服务器启动 | ✅ 成功(端口 1933) |
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| API 健康检查 | ✅ `/health` 返回 `{"status":"ok"}` |
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| 会话创建 | ✅ 成功 |
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| 消息添加 | ✅ 成功 |
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## 提交记录
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@@ -77,10 +81,15 @@ c8202d0 feat(viking): add local server management for privacy-first deployment
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- [x] Agent 智能层 Phase 1-3(274 passing tests)
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- [x] OpenViking 本地服务器管理
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- [x] 文档结构整理
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- [x] Python 3.12 安装(通过 winget)
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- [x] OpenViking pip 安装成功(v0.2.6)
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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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### 进行中
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- [ ] OpenViking 真实 CLI 集成(需要用户安装 `pip install openviking`)
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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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@@ -88,37 +97,114 @@ c8202d0 feat(viking): add local server management for privacy-first deployment
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- [ ] RuntimeAdapter 接口抽象
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- [ ] 领域模型标准化
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## 下一步建议
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## OpenViking 集成状态
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### 已完成
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- ✅ Python 3.12 安装(通过 winget)
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- ✅ OpenViking pip 安装成功(v0.2.6)
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### 已验证功能
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### 待完成
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1. **配置 API 密钥**(必需):
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```powershell
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# 选项 1: OpenAI
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$env:OPENAI_API_KEY = "your-key-here"
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| 功能 | 状态 | 说明 |
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|------|------|------|
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| 服务器启动 | ✅ | `http://127.0.0.1:1933` |
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| 健康检查 | ✅ | `GET /health` → `{"status":"ok"}` |
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| 系统状态 | ✅ | `GET /api/v1/system/status` |
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| 会话创建 | ✅ | `POST /api/v1/sessions` |
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| 消息添加 | ✅ | `POST /api/v1/sessions/{id}/messages` |
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| 向量搜索 | ⚠️ | 需要激活 Embedding 模型 |
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# 选项 2: 火山引擎(豆包)
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$env:VOLCENGINE_API_KEY = "your-key-here"
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### 待解决: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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```
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2. **启动 OpenViking 服务器**:
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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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"C:/Users/szend/AppData/Local/Programs/Python/Python312/Scripts/openviking-server.exe"
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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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3. **验证集成**:
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启动 ZCLAW 桌面应用,检查记忆面板是否正常工作
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### 备选方案:使用 OpenAI Embedding
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如果不想激活火山引擎 Embedding,可以改用 OpenAI:
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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://api.openai.com/v1",
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"api_key": "${OPENAI_API_KEY}",
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"provider": "openai",
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"model": "text-embedding-3-small",
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"dimension": 1536
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}
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}
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}
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```
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## 配置文件
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已创建 `~/.openviking/ov.conf`,需要设置环境变量 `OPENAI_API_KEY`
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当前配置 (`~/.openviking/ov.conf`):
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```json
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{
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"storage": {
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"workspace": "C:/Users/szend/.openviking/workspace",
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"vectordb": { "name": "context", "backend": "local" },
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"agfs": { "port": 1833, "log_level": "warn", "backend": "local" }
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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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"dimension": 1024,
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"model": "doubao-embedding"
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}
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},
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"server": { "host": "127.0.0.1", "port": 1933 }
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}
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```
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## 文件变更统计
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- 新增文件:4 个
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- 修改文件:3 个
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- 归档文件:10+ 个
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- 文档更新:1 个
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- 文档更新:2 个
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## 下一步工作
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1. **完成 Embedding 模型激活**(阻塞项)
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2. 验证向量搜索功能
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3. 测试 ZCLAW 记忆面板集成
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4. 提交完整集成代码
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