iven
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256dba49db
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fix(audit): 第五轮审计修复 — 反思LLM分析、语义路由、并行执行、错误中文化
- P2: 反思引擎接入 LLM 深度行为分析 (analyze_patterns_with_llm)
- P3-M6: 语义路由 RuntimeLlmIntentDriver 真实 LLM 匹配
- P3-L1: V2 Pipeline execute_parallel 改用 buffer_unordered 真正并行
- P3-S10: Rust 用户可见错误提示统一中文化
累计修复 27 项，完成度 ~72% → ~78%
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2026-03-27 12:10:48 +08:00 |
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iven
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9a77fd4645
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fix(intelligence): 精确化 dead_code 标注并实现 LLM 上下文压缩
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- 将 intelligence/llm/memory/browser 模块的 dead_code 注释从模糊的
"reserved for future" 改为明确说明 Tauri invoke_handler 运行时注册机制
- 为 identity.rs 中 3 个真正未使用的方法添加 #[allow(dead_code)]
- 实现 compactor use_llm: true 功能：新增 compact_with_llm 方法和
compactor_compact_llm Tauri 命令，支持 LLM 驱动的对话摘要生成
- 将 pipeline_commands.rs 中 40+ 处 println!/eprintln! 调试输出替换为
tracing::debug!/warn!/error! 结构化日志
- 移除 intelligence/mod.rs 中不必要的 #[allow(unused_imports)]
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2026-03-27 00:43:14 +08:00 |
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iven
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b7f3d94950
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fix(presentation): 修复 presentation 模块类型错误和语法问题
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- 创建 types.ts 定义完整的类型系统
- 重写 DocumentRenderer.tsx 修复语法错误
- 重写 QuizRenderer.tsx 修复语法错误
- 重写 PresentationContainer.tsx 添加类型守卫
- 重写 TypeSwitcher.tsx 修复类型引用
- 更新 index.ts 移除不存在的 ChartRenderer 导出
审计结果:
- 类型检查: 通过
- 单元测试: 222 passed
- 构建: 成功
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2026-03-26 17:19:28 +08:00 |
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iven
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d0c6319fc1
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feat: 添加ESLint和Prettier配置并优化代码结构
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style: 格式化代码文件并修复样式问题
docs: 新增部署文档和系统要求文档
test: 更新测试截图和覆盖率报告
refactor: 重构SchedulerPanel加载状态逻辑
ci: 添加lint和format脚本到package.json
build: 更新依赖项并添加开发工具
chore: 添加验证报告和上线审查计划
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2026-03-26 08:02:23 +08:00 |
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iven
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bf6d81f9c6
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refactor: 清理未使用代码并添加未来功能标记
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style: 统一代码格式和注释风格
docs: 更新多个功能文档的完整度和状态
feat(runtime): 添加路径验证工具支持
fix(pipeline): 改进条件判断和变量解析逻辑
test(types): 为ID类型添加全面测试用例
chore: 更新依赖项和Cargo.lock文件
perf(mcp): 优化MCP协议传输和错误处理
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2026-03-25 21:55:12 +08:00 |
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iven
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9c781f5f2a
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feat(pipeline): implement Pipeline DSL system for automated workflows
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Add complete Pipeline DSL system including:
- Rust backend (zclaw-pipeline crate) with parser, executor, and state management
- Frontend components: PipelinesPanel, PipelineResultPreview, ClassroomPreviewer
- Pipeline recommender for Agent conversation integration
- 5 pipeline templates: education, marketing, legal, research, productivity
- Documentation for Pipeline DSL architecture
Pipeline DSL enables declarative workflow definitions with:
- YAML-based configuration
- Expression resolution (${inputs.topic}, ${steps.step1.output})
- LLM integration, parallel execution, file export
- Agent smart recommendations in conversations
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2026-03-25 00:52:12 +08:00 |
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