142 Commits

Author SHA1 Message Date
iven
5b5491a08f feat(growth,kernel,runtime): Embedding 接通 + 自学习自动化 — A线+B线 6 项实现
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A线 Embedding 接通:
- A1: MemoryRetriever.set_embedding_client() + GrowthIntegration.configure_embedding()
  + Kernel.set_embedding_client() + viking_configure_embedding 传播到 Kernel
- A2: Skill 路由替换 new_tf_idf_only() 为 EmbeddingAdapter + LlmSkillFallback

B线 自学习自动化:
- B1: evolution_bridge.rs — candidate_to_manifest() (PromptOnly, disabled by default)
- B2: Kernel::generate_and_register_skill() 全链路 (LLM→parse→QualityGate→manifest→persist)
- B3: EvolutionMiddleware 双模式 (auto_mode 跳过注入, 留给 kernel 自动处理)
- B4: QualityGate 加固 (body ≥100字符 + 必须含标题 + 置信度上限 1.0)

验证: 934 tests PASS, 0 failures
2026-04-21 15:21:03 +08:00
iven
74ce6d4adc fix(growth,hands): 穷尽审计后 3 项修复 — browser 文档注释 + experience_store warn 日志 + identity 数字更正
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- browser.rs: 过时 doc comment pending_execution → delegated_to_frontend
- experience_store.rs: merge 反序列化失败时 warn!() + fallback 覆写
- wiki/log.md: identity_patterns 43→54 更正
2026-04-21 12:46:26 +08:00
iven
ec22f0f357 docs(wiki): Phase 2 自学习闭环验证记录 — 进化引擎全链路确认
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2026-04-21 10:58:00 +08:00
iven
d95fda3b76 test(growth): 进化闭环集成测试 — 6 个 E2E 验证
验证自学习闭环完整链路:
- 4 次经验累积 → reuse_count=3 → 模式识别触发
- 低于阈值不触发 → 正确过滤
- 多模式独立跟踪 → 行业上下文保留
- SkillGenerator prompt 构建 → 包含步骤/工具/行业
- QualityGate 验证 → 通过/冲突检测
- FeedbackCollector 信任度 → 正负反馈计分

全量测试: 918 PASS, 0 FAIL
2026-04-21 10:56:05 +08:00
iven
f11ac6e434 docs(wiki,CLAUDE): Phase 0+1 突破之路修复记录 — 8 项基础链路
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2026-04-21 10:20:23 +08:00
iven
9a2611d122 fix(growth,hands,kernel,desktop): Phase 1 用户可感知修复 — 6 项断链修复
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Phase 1 修复内容:
1. Hand 执行前端字段映射 — instance_id → runId,修复 Hand 状态追踪
2. Heartbeat 痛点感知 — PAIN_POINTS_CACHE + VikingStorage 持久化 + 未解决痛点检查
3. Browser Hand 委托消息 — pending_execution → delegated_to_frontend + 中文摘要
4. 跨会话记忆检索增强 — 扩展 IdentityRecall 模式 26→43 + 弱身份信号检测 + 低结果 fallback
5. Twitter Hand 凭据持久化 — SetCredentials action + 文件持久化 + 启动恢复
6. Browser 测试修复 — 适配新的 delegated_to_frontend 响应格式

验证: cargo check  | cargo test 912 PASS  | tsc --noEmit 
2026-04-21 10:18:25 +08:00
iven
2f5e9f1755 docs(wiki): 同步知识库 — 04-21 经验积累+Skill工具调用修复
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2026-04-21 01:12:51 +08:00
iven
c1dea6e07a fix(growth,skills,kernel): Phase 0 地基修复 — 经验积累覆盖 + Skill 工具调用
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Bug 1: ExperienceStore store_experience() 相同 pain_pattern 因确定性 URI
直接覆盖,新 Experience reuse_count=0 重置已有积累。修复为先检查 URI
是否已存在,若存在则合并(保留原 id/created_at,reuse_count+1)。

Bug 2: PromptOnlySkill::execute() 只做纯文本 complete(),75 个 Skill
的 tools 字段是装饰性的。修复为扩展 LlmCompleter 支持 complete_with_tools,
SkillContext 新增 tool_definitions,KernelSkillExecutor 从 ToolRegistry
解析 manifest 声明的工具定义传入 LLM function calling。
2026-04-21 01:12:35 +08:00
iven
f89b2263d1 fix(runtime,kernel): HandTool 空壳修复 — 桥接到 HandRegistry 真实执行
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B-HAND-1 修复: LLM 调用 hand_quiz/hand_researcher 等 Hand 工具后,
HandTool::execute() 原来返回假成功 JSON, 实际 Hand 并不执行.

修复方案 (沿用 SkillExecutor 模式):
- tool.rs: 新增 HandExecutor trait + ToolContext.hand_executor 字段
- hand_tool.rs: execute() 通过 context.hand_executor 分发到真实执行
- loop_runner.rs: AgentLoop 新增 hand_executor 字段 + builder + 3处 ToolContext 传递
- adapters.rs: 新增 KernelHandExecutor 桥接 HandRegistry.execute()
- kernel/mod.rs: 初始化 KernelHandExecutor + 注册到 AgentLoop
- messaging.rs: 两处 AgentLoop 构建添加 .with_hand_executor()

数据流: LLM tool call → HandTool::execute() → ToolContext.hand_executor
         → KernelHandExecutor → HandRegistry.execute() → Hand trait impl

809 tests passed, 0 failed.
2026-04-20 12:50:47 +08:00
iven
3b97bc0746 docs(wiki): 审计修复记录 — 04-20 功能链路审计 5 项修复
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2026-04-20 09:44:46 +08:00
iven
f2917366a8 fix(growth,kernel,runtime,desktop): 50 轮功能链路审计 7 项断链修复
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P0 修复:
- B-MEM-2: 跨会话记忆丢失 — 添加 IdentityRecall 查询意图检测,
  身份类查询绕过 FTS5/LIKE 文本搜索,直接按 scope 检索全部偏好+知识记忆;
  缓存 GrowthIntegration 到 Kernel 避免每次请求重建空 scorer
- B-HAND-1: Hands 未触发 — 创建 HandTool wrapper 实现 Tool trait,
  在 create_tool_registry() 中注册所有已启用 Hands 为 LLM 可调用工具

P1 修复:
- B-SCHED-4: 一次性定时未拦截 — 添加 RE_ONE_SHOT_TODAY 正则匹配
  "下午3点半提醒我..."类无日期前缀的同日触发模式
- B-CHAT-2: 工具调用循环 — ToolErrorMiddleware 添加连续失败计数器,
  3 次连续失败后自动 AbortLoop 防止无限重试
- B-CHAT-5: Stream 竞态 — cancelStream 后添加 500ms cancelCooldown,
  防止后端 active-stream 检查竞态
2026-04-20 09:43:38 +08:00
iven
24b866fc28 fix(growth,runtime,desktop): E2E 验证 4 项 Bug 修复
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P1 BUG-1: SemanticScorer CJK 分词缺失导致 TF-IDF 相似度为 0
- 新增 CJK bigram 分词: "北京工作" → ["北京","京工","工作","北京工作"]
- 非CJK文本保持原有分割逻辑
- 3 个新测试: bigram 生成 + 混合文本 + CJK 相似度>0

P1 BUG-2: streamStore lifecycle:end 未记录 token 使用量
- AgentStreamDelta 增加 input_tokens/output_tokens 字段
- lifecycle:end 处理中检查并调用 addTokenUsage

P2 BUG-3: NlScheduleParser "X点半" 解析为整点
- 所有时间正则增加可选的 (半) 捕获组
- extract_minute 辅助函数: 半 → 30

P2 BUG-4: NlScheduleParser "工作日每天" 未转为 1-5
- RE_WORKDAY_EXACT 支持 (每天|每日)? 中缀
- try_workday 优先级提升至 try_every_day 之前

E2E 报告: docs/E2E_TEST_REPORT_2026_04_19.md
测试: 806 passed / 0 failed (含 9 个新增测试)
2026-04-20 00:07:07 +08:00
iven
39768ff598 fix(growth): CJK 记忆检索 TF-IDF 阈值过高导致注入失败
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根因: SqliteStorage.find() 对 CJK 查询使用 LIKE fallback 获取候选,
但 TF-IDF 评分因 unicode61 tokenizer 不支持 CJK 而系统性地偏低,
被默认 min_similarity=0.7 阈值全部过滤掉。

修复: 检测到 CJK 查询时将阈值降至 50%(0.35),避免所有记忆被误过滤。
2026-04-19 22:23:32 +08:00
iven
3ee68fa763 fix(desktop): Tauri 端屏蔽"已恢复连接"离线队列提示
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Tauri 桌面端直连本地 Kernel,不存在浏览器端的离线队列场景,
"已恢复连接 + 发送中 N 条"提示对桌面用户无意义且干扰界面。

通过检测 __TAURI_INTERNALS__ 在非离线状态时返回 null,
真正离线时仍正常显示。
2026-04-19 19:17:44 +08:00
iven
891d972e20 docs: wiki/log 审计修复记录
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2026-04-19 13:46:09 +08:00
iven
e12766794b fix(relay,store): 审计修复 — 自动恢复可达化 + 类型化错误 + 全路径重连
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C1: mark_key_429 设 is_active=FALSE,使 select_best_key 自动恢复
路径真正可达。之前 429 只设 cooldown_until,恢复代码为死代码。

H1+H2: 重试查询补全 debug 日志(RPM/TPM 跳过、解密失败)+ 修复
fallthrough 错误信息(RateLimited 而非 NotFound)。

H3+H4+M3+M4+M5: agentStore.ts 提取 classifyAgentError() 类型化错误
分类,覆盖 502/503/401/403/429/500,统一 createClone/
createFromTemplate/updateClone/deleteClone 错误处理,不再泄露原始
错误详情。所有 catch 块添加 log.error。

H5+H6: auth.ts 提取 triggerReconnect() 共享函数,login/loginWithTotp/
restoreSession 三处统一调用。状态检查改为仅 'disconnected' 时触发,
避免 connecting/reconnecting 状态下并发 connect。

M1: toggle_key_active(true) 同步清除 cooldown_until,防止管理员
激活后 key 仍被 cooldown 过滤不可见。
2026-04-19 13:45:49 +08:00
iven
d9f8850083 docs: wiki/log 更新发布前审计 5 项修复记录
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2026-04-19 13:28:05 +08:00
iven
0bd50aad8c fix(heartbeat,skills): 健康快照降级处理 + 技能加载重试
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P1-3: health_snapshot 在 heartbeat engine 未初始化时不再报错,
返回 pending 状态快照,避免 HealthPanel 竞态报错。

P1-1: loadSkillsCatalog 新增 Path C 延迟重试(最多2次,间隔
1.5s/3s),解决 kernel 初始化未完成时 skills 返回空数组的问题。
2026-04-19 13:27:25 +08:00
iven
4ee587d070 fix(relay,store): Provider Key 自动恢复 + Agent 创建友好错误 + 登录后重连
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P0-1: key_pool.rs 新增 cooldown 过期 Key 自动恢复逻辑。
当所有 Key 的 is_active=false 且 cooldown_until 已过期时,
自动重新激活并重试选择,避免 relay/models 返回空数组导致聊天失败。

P0-2: agentStore.ts createClone/createFromTemplate 错误信息
从原始 HTTP 错误改为可操作的中文提示(502/503/401 分类处理)。

P1-2: auth.ts login 成功后触发 connectionStore.connect(),
确保 kernel 使用新 JWT 而非旧 token。
2026-04-19 13:16:12 +08:00
iven
8b1b08be82 docs: sync TRUTH.md + wiki/log for Batch 3/8 completion
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TRUTH.md: update date, add workspace test count 797
wiki/log.md: append 2026-04-19 entry for sqlx upgrade + test coverage
2026-04-19 11:26:24 +08:00
iven
beeb529d8f test(protocols,skills): add 90 tests for MCP types + skill loader/runner
zclaw-protocols: +43 tests covering mcp_types serde, ContentBlock
variants, transport config builders, and domain type roundtrips.

zclaw-skills: +47 tests covering SKILL.md/TOML parsing, auto-classify,
PromptOnlySkill execution, and SkillManifest/SkillResult roundtrips.

Batch 8 of audit plan (plans/stateless-petting-rossum.md).
2026-04-19 11:24:57 +08:00
iven
226beb708b Merge branch 'chore/sqlx-0.8-upgrade'
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sqlx 0.7→0.8 unified, resolves dual-version from pgvector.
2026-04-19 11:15:17 +08:00
iven
dc7a1d5400 chore(deps): upgrade sqlx 0.7→0.8 + libsqlite3-sys 0.27→0.30
Unifies dual sqlx versions caused by pgvector 0.4 pulling sqlx 0.8.x
as indirect dependency. Zero source code changes required, 719/719
tests pass.

Batch 3 of audit plan (plans/stateless-petting-rossum.md).
2026-04-19 11:15:05 +08:00
iven
d9b0b4f4f7 fix(audit): Batch 7-9 dead_code 标注 + TODO 清理 + 文档同步
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Batch 7: dead_code 标注统一 (16 处)
- crates/ 9 处: growth, kernel, pipeline, runtime, saas, skills
- src-tauri/ 7 处: classroom, intelligence, browser, mcp
- 统一格式: #[allow(dead_code)] // @reserved: <原因>

Batch 7+: EvolutionEngine L2/L3 10 个未使用 pub 函数
- 全部标注 @reserved: EvolutionEngine L2/L3, post-release integration

Batch 9: TODO → FUTURE 标记 (4 处)
- html.rs: template-based export
- nl_schedule.rs: LLM-assisted parsing
- knowledge/handlers.rs: category_id from upload
- personality_detector.rs: VikingStorage persistence

Batch 5+: Cargo.lock 更新 (serde_yaml_bw 迁移)

全量测试通过: 719 passed, 0 failed
2026-04-19 08:54:57 +08:00
iven
edd6dd5fc8 fix(audit): Batch 4-6 中间件注释 + 依赖迁移 + 安全加固
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Batch 4:
- kernel/mod.rs: 添加中间件注册顺序≠执行顺序注释
- EvolutionMiddleware 注册处标注 priority=78

Batch 5:
- desktop/src-tauri/Cargo.toml: serde_yaml 0.9 (deprecated) → serde_yaml_bw 2.x

Batch 6:
- saas/main.rs: CORS 开发模式改为显式 localhost origins (修复 Any+credentials 违规)
- docker-compose.yml: 移除默认弱密码 your_secure_password,改为必填校验
- director.rs: 用户输入添加 <user_input>/<user_request> 边界标记防注入

全量测试通过: 719 passed, 0 failed
2026-04-19 08:46:12 +08:00
iven
4329bae1ea fix(audit): Batch 2 生产代码 unwrap 替换 (20 处)
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P0 修复:
- viking_commands.rs: URI 路径构建 unwrap → ok_or_else 错误传播
- clip.rs: 临时文件路径 unwrap → ok_or_else (防 Windows 中文路径 panic)

P1 修复:
- personality_detector.rs: Mutex lock unwrap → unwrap_or_else 防中毒传播
- pptx.rs: HashMap.get unwrap → expect (来自 keys() 迭代)

P2 修复:
- 4 处 SystemTime.unwrap → expect("system clock is valid")
- 4 处 dev_server URL.parse.unwrap → expect("hardcoded URL is valid")
- 9 处 nl_schedule Regex.unwrap → expect("static regex is valid")
- 5 处 data_masking Regex.unwrap → expect("static regex is valid")
- 2 处 pipeline/state Regex.unwrap → expect("static regex is valid")

全量测试通过: 719 passed, 0 failed
2026-04-19 08:38:09 +08:00
iven
924ad5a6ec fix(audit): Batch 0-1 文档校准 + let _ = 静默错误修复
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Batch 0:
- TRUTH.md 中间件层 14→15 (补 EvolutionMiddleware@78)
- wiki/middleware.md 同步 15 层 + 优先级分类更新
- Store 数字确认 25 个

Batch 1:
- approvals.rs: 3 处 map_err+let _ = 简化为 if let Err
- director.rs: oneshot send 失败添加 debug 日志
- task.rs: 4 处子任务状态更新添加 debug 日志
- chat.rs: 流消息发送和事件 emit 添加 warn/debug 日志
- heartbeat.rs: 告警广播添加 debug 日志 + break 优化

全量测试通过: 719 passed, 0 failed
2026-04-19 08:30:33 +08:00
iven
e94235c4f9 fix(growth): Evolution Engine 穷尽审计 3CRITICAL + 3HIGH 全部修复
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C-01: ExperienceExtractor 接入 ExperienceStore
- GrowthIntegration.new() 创建 ExperienceExtractor 时注入 ExperienceStore
- 经验持久化路径打通:extract_combined → persist_experiences → ExperienceStore

C-02+C-03: 进化触发链路全链路接通
- create_middleware_chain() 注册 EvolutionMiddleware (priority 78)
- MemoryMiddleware 持有 Arc<EvolutionMiddleware> 共享引用
- after_completion 中调用 check_evolution() → 推送 PendingEvolution
- EvolutionMiddleware 在下次对话前注入进化建议到 system prompt

H-01: FeedbackCollector loaded 标志修复
- load() 失败时保留 loaded=false,下次 save 重试
- 日志级别 debug → warn

H-03: FeedbackCollector 内部可变性
- EvolutionEngine.feedback 改为 Arc<Mutex<FeedbackCollector>>
- submit_feedback() 从 &mut self → &self,支持中间件 &self 调用路径
- GrowthIntegration.initialize() 从 &mut self → &self

H-05: 删除空测试 test_parse_empty_response (无 assert)

H-06: infer_experiences_from_memories() fallback
- Outcome::Success → Outcome::Partial (反映推断不确定性)
2026-04-19 00:43:02 +08:00
iven
72b3206a6b fix(growth): AUD-11 反馈信任度启动集成 + AUD-12 日志格式优化
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AUD-11: FeedbackCollector 内部 lazy-load 机制
- save() 首次调用自动从持久化存储加载信任度记录
- load() 使用 or_insert 策略,不覆盖内存中较新记录
- GrowthIntegration.initialize() 保留为可选优化入口
- 移除无法在 &self 中间件中使用的 ensure_feedback_loaded

AUD-12: 日志格式优化
- ProfileSignals 新增 signal_count() 方法
- extractor.rs 使用 signal_count() 替代 has_any_signal() as usize
2026-04-19 00:15:50 +08:00
iven
0fd78ac321 fix: 全面审计修复 — P0 功能缺陷 + P1 代码质量
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P0 功能修复:
- stats: Admin V2 仪表盘 API 路径修正 (/stats/dashboard → /admin/dashboard)
- mcp: 桌面端 MCP 插件增加 isTauriRuntime() 守卫,避免浏览器模式崩溃
- admin: 侧边栏高亮逻辑修复 (startsWith → 精确匹配+子路径)

P1 代码质量:
- 删除 workflowBuilderStore.ts 死代码 (456行,零引用)
- sqlite.rs 3 处 SQL 静默失败改为 tracing::warn! 日志
- mcp_tool_adapter 2 处 unwrap 改为安全回退
- orchestration_execute 添加 @reserved 标注
- TRUTH.md 测试数字校准 (734→803),Store 数 26→25
2026-04-18 23:57:03 +08:00
iven
ab4d06c4d6 fix(growth): 审计修复 — CRITICAL 编译错误 + LOW 静默数据丢失
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- CRITICAL: extraction_adapter.rs extract_with_prompt() 使用不存在的
  zclaw_types::Error::msg(),改为 ZclawError::InvalidInput/ZclawError::LlmError
- LOW: feedback_collector.rs save() 中 serde_json::to_string().unwrap_or_default()
  改为显式错误处理 + warn 日志 + continue,避免静默存空数据
2026-04-18 23:30:58 +08:00
iven
1595290db2 fix(growth): MEDIUM-12 ProfileUpdater 补齐 5 维度画像更新
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根因: ProfileUpdater 只处理 industry 和 communication_style 2/5 维度,
跳过 recent_topic、pain_point、preferred_tool。

修复:
- ProfileFieldUpdate 添加 kind 字段 (SetField | AppendArray)
- collect_updates() 现在处理全部 5 个维度:
  - industry, communication_style → SetField (直接覆盖)
  - recent_topic, pain_point, preferred_tool → AppendArray (追加去重)
- growth.rs 根据 ProfileUpdateKind 分派到不同的 UserProfileStore 方法:
  - SetField → update_field()
  - AppendArray → add_recent_topic() / add_pain_point() / add_preferred_tool()
- ProfileUpdateKind re-exported from lib.rs

测试: test_collect_updates_all_five_dimensions 验证 5 个维度 + 2 种更新类型
2026-04-18 23:07:31 +08:00
iven
2c0602e0e6 fix(growth): HIGH-3 FeedbackCollector 信任度持久化
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根因: FeedbackCollector 用纯内存 HashMap 存储信任度记录,重启后归零。

修复:
- FeedbackCollector 添加 viking: Option<Arc<VikingAdapter>> 字段
- 添加 with_viking() 构造器
- 添加 save(): 遍历 trust_records → MemoryEntry → VikingAdapter 存储
- 添加 load(): find_by_prefix 反序列化回 HashMap
- EvolutionEngine::new()/from_experience_store() 传入 VikingAdapter
- submit_feedback() 改为 async,提交后自动调用 save()
- 添加 load_feedback() 供启动时恢复

测试: save_and_load_roundtrip + load_without_viking + save_without_viking
2026-04-18 23:03:31 +08:00
iven
f358f14f12 fix(growth): 穷尽审计修复 — tracker timeline 断链 + 文档更新
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P1-1: tracker.rs record_learning 改为通过 MemoryEntry 存储
      (之前用 store_metadata 存但 get_timeline 用 find_by_prefix 读,
       两条路径不交叉,timeline 永远返回空)

P2-4: extractor.rs 移除未使用的 _llm_driver 绑定,改为 is_none() 检查

P2-5: lib.rs 模块文档更新,反映实际 17 个模块而非原始 4 个

profile_updater.rs: 添加注释说明只收集 update_field 支持的字段

测试: zclaw-growth 137 tests, zclaw-runtime 87 tests, 0 failures
2026-04-18 23:01:04 +08:00
iven
7cdcfaddb0 fix(growth): MEDIUM-10 Experience 添加 tool_used 字段
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根因: Experience 结构体没有 tool_used 字段,PatternAggregator 从
context 字段提取工具名(语义混淆),导致工具信息不准确。

修复:
- experience_store.rs: Experience 添加 tool_used: Option<String> 字段
  (#[serde(default)] 兼容旧数据),Experience::new() 初始化为 None
- experience_extractor.rs: persist_experiences() 从 ExperienceCandidate
  的 tools_used[0] 填充 tool_used,同时填充 industry_context
- pattern_aggregator.rs: 改用 tool_used 字段提取工具名,不再误用 context
- store_experience() 将 tool_used 加入 keywords 提升搜索命中率
2026-04-18 22:58:47 +08:00
iven
3c6581f915 fix(growth): HIGH-6 修复 extract_combined 合并提取空壳
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根因: growth.rs 构造 CombinedExtraction 时硬编码 experiences: Vec::new()
和 profile_signals: default(),导致 L1 结构化经验不被提取、L2 技能进化
没有输入数据、整个进化引擎无法端到端工作。

修复:
- extractor.rs: 添加 COMBINED_EXTRACTION_PROMPT 统一 prompt,单次 LLM 调用
  同时输出 memories + experiences + profile_signals
- extractor.rs: 添加 parse_combined_response() 解析 LLM JSON 响应
- LlmDriverForExtraction trait: 添加 extract_with_prompt() 方法(默认不支持,
  退化到现有 extract() + 启发式推断)
- MemoryExtractor: 添加 extract_combined() 方法,优先单次调用,失败则退化
- growth.rs: extract_combined() 使用新的合并提取替代硬编码空值
- TauriExtractionDriver: 实现 extract_with_prompt()
- ProfileSignals: 添加 has_any_signal() 方法
- types.rs: ProfileSignals 无 structural 变化(字段已存在)

测试: 4 个新测试(parse_combined_response_full/minimal/invalid +
extract_combined_fallback),11 个 extractor 测试全部通过
2026-04-18 22:56:42 +08:00
iven
cb727fdcc7 fix(growth): 二次审计修复 — 6项 CRITICAL/HIGH/MEDIUM 全部修复
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CRITICAL-1/2: json_utils 花括号匹配改为括号平衡算法
  - 处理字符串字面量中的花括号和转义引号
  - 新增 5 个测试(平衡匹配、字符串内花括号、转义引号、extract_string_array)

HIGH-4: EvolutionMiddleware 只取第一个事件(remove(0)),不丢弃后续
HIGH-5: EvolutionMiddleware 先 read() 判空再 write(),减少锁竞争
HIGH-7: from_experience_store 使用传入 store 的 viking 实例(不再忽略参数)
  - ExperienceStore 新增 viking() getter

MEDIUM-9: skill_generator + workflow_composer JSON 数组解析去重
  - 新增 json_utils::extract_string_array() 共享函数
MEDIUM-14: EvolutionMiddleware 注入文本去除多余缩进空格

测试: zclaw-growth 133 tests, zclaw-runtime 87 tests, workspace 0 failures
2026-04-18 22:30:10 +08:00
iven
a9ea9d8691 fix(growth): Evolution Engine 审计修复 — 7项全部完成
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HIGH-1: 提取共享 json_utils.rs,skill_generator/workflow_composer 去重
HIGH-2: FeedbackCollector Vec→HashMap,消除 unwrap() panic 风险
HIGH-3: ProfileUpdater 改为 collect_updates() 返回字段列表,
        growth.rs 直接 async 调用 update_field(),不再用 no-op 闭包
MEDIUM-1: EvolutionMiddleware 注入后自动 drain,防止重复注入
MEDIUM-2: PatternAggregator tools 提取改为直接收集 context 值
MEDIUM-3: evolution_engine.rs 移除 4 个未使用 imports
MEDIUM-4: workflow_composer parse_response pattern 参数加下划线
MEDIUM-7: SkillCandidate 添加 version 字段(默认=1)

测试: zclaw-growth 128 tests, zclaw-runtime 86 tests, workspace 0 failures
2026-04-18 22:15:43 +08:00
iven
f97e6fdbb6 feat: Evolution Engine Phase 3-5 — WorkflowComposer+FeedbackCollector+EvolutionMiddleware+反馈闭环
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Phase 3:
- EvolutionMiddleware (priority 78): 管家对话中注入进化确认提示
- GrowthIntegration.check_evolution() API 串入

Phase 4:
- WorkflowComposer: 轨迹工具链模式聚类 + Pipeline YAML prompt 构建 + JSON 解析
- EvolutionEngine.analyze_trajectory_patterns() L3 入口

Phase 5:
- FeedbackCollector: 反馈信号收集 + 信任度管理 + 推荐(Optimize/Archive/Promote)
- EvolutionEngine 反馈闭环方法: submit_feedback/get_artifacts_needing_optimization

新增 12 个测试(111→123),全 workspace 701 测试通过。
2026-04-18 21:27:59 +08:00
iven
7d03e6a90c feat(runtime): GrowthIntegration 串入 EvolutionEngine — L2 触发检查 API 2026-04-18 21:17:48 +08:00
iven
415abf9e66 feat(growth): L2 技能进化核心 — PatternAggregator+SkillGenerator+QualityGate+EvolutionEngine
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- PatternAggregator: 经验模式聚合,找出 reuse_count>=threshold 的可固化模式
- SkillGenerator: LLM prompt 构建 + JSON 解析 + 自动提取 JSON 块
- QualityGate: 置信度/冲突/格式质量门控
- EvolutionEngine: 中枢调度器,协调 L2 触发检查+技能生成+质量验证

新增 24 个测试(87→111),全 workspace 0 error。
2026-04-18 21:09:48 +08:00
iven
8d218e9ab9 feat(runtime): GrowthIntegration 串入 ExperienceExtractor + ProfileUpdater
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2026-04-18 21:01:04 +08:00
iven
e2d44ecf52 feat(growth): ExperienceExtractor + ProfileUpdater — 结构化经验提取和画像增量更新 2026-04-18 20:51:17 +08:00
iven
8ec6ca5990 feat(growth): 扩展 LlmDriverForExtraction — 新增 extract_combined_all 默认实现 2026-04-18 20:48:09 +08:00
iven
7e8eb64c4a feat(growth): 新增 Evolution Engine 核心类型 — ExperienceCandidate/CombinedExtraction/EvolutionEvent 2026-04-18 20:47:30 +08:00
iven
e88c51fd85 docs(wiki): 发布前审计数值校准 — TRUTH/CLAUDE/wiki 三端同步
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TRUTH.md:
- #[test] 433→425, #[tokio::test] 368→309 (2026-04-18 验证)
- Zustand Store 21→26, Admin V2 页面 15→17
- Pipeline YAML 17→18
- Hands 启用 9→7 (6 HAND.toml + _reminder),Whiteboard/Slideshow/Speech 标注开发中

CLAUDE.md §6:
- Hands 12 个能力包 (7 注册 + 3 开发中 + 2 禁用)
- §13 架构快照同步

wiki/index.md:
- 关键数字同步更新
2026-04-18 14:09:47 +08:00
iven
e10549a1b9 fix: 发布前审计 Batch 2 — Debug遮蔽 + unwrap + 静默吞错 + MCP锁 + 索引 + Config验证
安全:
- LlmConfig 自定义 Debug impl,api_key 显示为 "***REDACTED***"
- tsconfig.json 移除 ErrorBoundary.tsx 排除项(安全关键组件)
- billing/handlers.rs Response builder unwrap → map_err 错误传播
- classroom_commands/mod.rs db_path.parent().unwrap() → ok_or_else

静默吞错:
- approvals.rs 3处 warn→error(审批状态丢失是严重事件)
- events.rs publish() 添加 Event dropped debug 日志
- mcp_transport.rs eprintln→tracing::warn (僵尸进程风险)
- zclaw-growth sqlite.rs 4处迁移:区分 duplicate column name 与真实错误

MCP Transport:
- 合并 stdin+stdout 为单一 Mutex<TransportHandles>
- send_request write-then-read 原子化,防止并发响应错配

数据库:
- 新迁移 20260418000001: idx_rle_created_at + idx_billing_sub_plan + idx_ki_created_by

配置验证:
- SaaSConfig::load() 添加 jwt_expiration_hours>=1, max_connections>0, min<=max
2026-04-18 14:09:36 +08:00
iven
f3fb5340b5 fix: 发布前审计 Batch 1 — Pipeline 内存泄漏/超时 + Director 死锁 + Rate Limit Worker
Pipeline executor:
- 添加 cleanup() 方法,MAX_COMPLETED_RUNS=100 上限淘汰旧记录
- 每步执行添加 tokio::time::timeout(使用 PipelineSpec.timeout_secs,默认 300s)
- Delay ms 上限 60000,超出 warn 并截断

Director send_to_agent:
- 重构为 oneshot::channel 响应模式,避免 inbox + pending_requests 锁竞争
- 添加 ensure_inbox_reader() 独立任务分发响应到对应 oneshot sender

cleanup_rate_limit Worker:
- 实现 Worker body: DELETE FROM rate_limit_events WHERE created_at < NOW() - INTERVAL '1 hour'

651 tests passed, 0 failed
2026-04-18 14:09:16 +08:00
iven
35a11504d7 docs(wiki): 审计后续修复记录
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2026-04-18 09:24:25 +08:00
iven
450569dc88 fix: 审计后续 3 项修复 — 残留清理 + FTS5 CJK + HTTP 大小限制
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1. Shell Hands 残留清理 (3处):
   - message.rs: 移除过时的 zclaw_hands::slideshow 注释
   - user_profiler.rs: slideshow 偏好改为 RecentTopic
   - handStore.test.ts: 移除 speech mock 数据 (3→2)

2. zclaw-growth FTS5 CJK 查询修复:
   - sanitize_fts_query CJK 路径从精确短语改为 token OR 组合
   - "Rust 编程" → "rust" OR "编程" (之前是 "rust 编程" 精确匹配)
   - 修复 test_memory_lifecycle + test_semantic_search_ranking

3. WASM HTTP 响应大小限制:
   - Content-Length 预检 + 读取后截断 (1MB 上限)
   - read_to_string 改为显式错误处理

651 测试全通过,0 失败。
2026-04-18 09:23:58 +08:00
iven
3a24455401 docs(wiki): 深度审计修复记录
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2026-04-18 09:11:37 +08:00
iven
4e4eefdde1 fix: 深度审计修复 — WASM 安全加固 + A2A 编译路径 + 测试编译
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CRITICAL:
- zclaw_file_read: 路径遍历修复 — 组件级过滤替代前缀检查
- zclaw_http_fetch: SSRF 防护 — URL scheme 白名单 + 私有IP段阻止
- Phase 4A: 移除 zclaw-protocols a2a feature gate, A2A 始终编译
- 移除 kernel/desktop multi-agent feature (不再控制任何代码)

MEDIUM:
- user_profiler: FactCategory cfg(test) 导入修复 (563 测试全通过)
2026-04-18 09:11:15 +08:00
iven
0522f2bf95 docs: CLAUDE.md 架构快照更新 — 记忆管道 E2E + 最近变更排序
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2026-04-18 08:18:39 +08:00
iven
04f70c797d docs(wiki): Phase 4A/4B 记录 — multi-agent gate 移除 + WASM host 函数
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2026-04-18 08:18:28 +08:00
iven
a685e97b17 feat(skills): WASM host 函数真实实现 — zclaw_log/http_fetch/file_read (Phase 4B)
替换 stub 为真实实现:
- zclaw_log: 读取 guest 内存并 log
- zclaw_http_fetch: ureq v3 同步 GET (10s timeout, network_allowed 守卫)
- zclaw_file_read: 沙箱 /workspace 目录读取 (路径校验防逃逸)
添加 ureq v3 workspace 依赖, 25 测试全通过。
2026-04-18 08:18:08 +08:00
iven
2037809196 refactor(kernel): 移除 multi-agent feature gate — 33处 cfg 全部删除 (Phase 4A)
8 个文件移除 #[cfg(feature = "multi-agent")],zclaw-kernel default features
新增 multi-agent。A2A 路由、agents、adapters 现在始终编译。
2026-04-18 08:17:58 +08:00
iven
eaa99a20db feat(ui): Feature Gates 设置页 — 实验性功能开关 (Phase 3B)
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新增 Settings > 实验性功能 页面:
- 3 个开关: 多 Agent 协作 / WASM 技能沙箱 / 详细工具输出
- localStorage 持久化 + isFeatureEnabled() 公共 API
- 实验性功能警告横幅
- 当前为前端运行时开关,未来可对接 Kernel config
2026-04-18 08:05:06 +08:00
iven
a38e91935f docs(wiki): Phase 3A loop_runner 双路径合并记录
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2026-04-17 21:56:34 +08:00
iven
5687dc20e0 refactor(runtime): loop_runner 双路径合并 — 统一走 middleware chain (Phase 3A)
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middleware_chain 从 Option<MiddlewareChain> 改为 MiddlewareChain:
- 移除 6 处 use_middleware 分支 + 2 处 legacy loop_guard inline path
- 移除 loop_guard field + Mutex import + circuit_breaker_triggered 变量
- 空 chain (Default) 行为等价于 middleware path 中的 no-op
- 1154行 → 1023行,净减 131 行
- cargo check --workspace ✓ | cargo test ✓ (排除 desktop 预存编译问题)
2026-04-17 21:56:10 +08:00
iven
21c3222ad5 docs(wiki): Phase 2A Pipeline 解耦记录
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2026-04-17 20:10:34 +08:00
iven
5381e316f0 refactor(pipeline): 移除空的 zclaw-kernel 依赖 (Phase 2A)
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Pipeline 代码中无任何 zclaw_kernel 引用,依赖声明是遗留物。
移除后编译验证通过: cargo check --workspace --exclude zclaw-saas ✓
2026-04-17 20:10:21 +08:00
iven
96294d5b87 docs(wiki): Phase 2B saasStore 拆分记录
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2026-04-17 20:05:57 +08:00
iven
e3b6003be2 refactor(store): saasStore 拆分为子模块 (Phase 2B)
1025行单文件 → 5个文件 + barrel re-export:
- saas/types.ts (103行) — 类型定义
- saas/shared.ts (93行) — Device ID、常量、recovery probe
- saas/auth.ts (362行) — 登录/注册/登出/恢复/TOTP
- saas/billing.ts (84行) — 计划/订阅/支付
- saas/index.ts (309行) — Store 组装 + 连接/模板/配置
- saasStore.ts (15行) — re-export barrel(外部零改动)

所有 25+ 消费者 import 路径不变,`tsc --noEmit` ✓
2026-04-17 20:05:43 +08:00
iven
f9f5472d99 docs(wiki): Phase 5 移除空壳 Hand 记录
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2026-04-17 19:56:32 +08:00
iven
cb9e48f11d refactor(hands): 移除空壳 Hand — Whiteboard/Slideshow/Speech (Phase 5)
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删除 3 个仅含 UI 占位的 Hand,清理 Rust 实现与前端引用:
- Rust: whiteboard.rs(422行) + slideshow.rs(797行) + speech.rs(442行)
- 前端: WhiteboardCanvas + SlideshowRenderer + speech-synth + 相关类型/常量
- 配置: 3 个 HAND.toml
- 净减 ~5400 行,Hands 9→6(启用) + Quiz/Browser/Researcher/Collector/Clip/Twitter/Reminder
2026-04-17 19:55:59 +08:00
iven
14fa7e150a docs(wiki): Phase 1 错误体系重构记录
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2026-04-17 19:38:47 +08:00
iven
f9290ea683 feat(types): 错误体系重构 — ErrorKind + error code + Serialize
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Rust (crates/zclaw-types/src/error.rs):
- 新增 ErrorKind enum (17 种) + Serde Serialize/Deserialize
- 新增 error_codes 模块 (稳定错误码 E4040-E5110)
- ZclawError 新增 kind() / code() 方法
- 新增 ErrorDetail struct + Serialize impl
- 保留所有现有变体和构造器 (零破坏性)
- 新增 12 个测试: kind 映射 + code 稳定性 + JSON 序列化

TypeScript (desktop/src/lib/error-types.ts):
- 新增 RustErrorKind / RustErrorDetail 类型定义
- 新增 tryParseRustError() 结构化错误解析
- 新增 classifyRustError() 按 ErrorKind 分类
- classifyError() 优先解析结构化错误,fallback 字符串匹配
- 17 种 ErrorKind → 中文标题映射

验证: cargo check ✓ | tsc ✓ | 62 zclaw-types tests ✓
2026-04-17 19:38:19 +08:00
iven
0754ea19c2 docs(wiki): Phase 0 修复记录 — 流式事件/CI/中文化
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2026-04-17 18:13:43 +08:00
iven
2cae822775 fix: Phase 0 阻碍项修复 — 流式事件错误处理 + CI 排除 + UI 中文化
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BLK-2: loop_runner.rs 22 处 let _ = tx.send() 全部替换为
if let Err(e) { tracing::warn!(...) },修复流式事件静默丢失问题

BLK-5: 50+ 英文字符串翻译为中文
- HandApprovalModal.tsx (~40处): 风险标签/按钮/状态/表单标签
- ChatArea.tsx: Thinking.../Sending...
- AuditLogsPanel.tsx: 空状态文案
- HandParamsForm.tsx: 空列表提示
- CreateTriggerModal.tsx: 成功提示
- MessageSearch.tsx: 时间筛选/搜索历史

BLK-6: CI/Release workflow 添加 --exclude zclaw-saas
- ci.yml: clippy/test/build 三个步骤
- release.yml: test 步骤

验证: cargo check ✓ | tsc --noEmit ✓
2026-04-17 18:12:42 +08:00
iven
93df380ca8 docs(wiki): BUG-M4/L1 已修复 + wiki 数字更新
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- BUG-M4 标记为已修复 (admin_guard_middleware)
- BUG-L1 标记为已验证修复 (代码已统一为 pain_seed_categories)
- E2E 04-17 MEDIUM/LOW 全部关闭
- butler.md/log.md: pain_seeds → pain_seed_categories
2026-04-17 11:46:04 +08:00
iven
90340725a4 fix(saas): admin_guard_middleware — 非 admin 用户统一返回 403
BUG-M4 修复: 之前非 admin 用户发送 malformed body 到 admin 端点时,
Axum 先反序列化 body 返回 422,绕过了权限检查。

- 新增 admin_guard_middleware (auth/mod.rs) 在中间件层拦截
- account::admin_routes() 拆分 (dashboard 独立)
- billing::admin_routes() + account::admin_routes() 加 guard layer
- 非 admin 用户无论 body 是否合法,统一返回 403
2026-04-17 11:45:55 +08:00
iven
b2758d34e9 docs(wiki): 添加 04-17 回归验证记录 — 13/13 PASS
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- Phase 1: 6 项 bug 修复回归全部 PASS (H1/H2/M1/M2/M3/M5)
- Phase 2: Pipeline + Skill 子系统链路全部 PASS
- Phase 3: Butler + 记忆联动全部 PASS
- BUG-L2 Pipeline 反序列化已验证修复
- 记忆系统 381 条记忆, 12 agent 隔离正常
2026-04-17 10:45:49 +08:00
iven
a504a40395 fix: 7 项 E2E Bug 修复 — Dashboard 404 / 记忆去重 / 记忆注入 / invoice_id / Prompt 版本
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P0:
- BUG-H1: Dashboard 路由 /api/v1/stats/dashboard → /api/v1/admin/dashboard

P1:
- BUG-H2: viking_add 预检查 content_hash 去重,返回 "deduped" 状态;SqliteStorage 启动时回填已有条目 content_hash
- BUG-M5: saas-relay-client 发送前调用 viking_inject_prompt 注入跨会话记忆

P2:
- BUG-M1: PaymentResult 添加 invoice_id 字段,query_payment_status 返回 invoice_id
- BUG-M2: UpdatePromptRequest 添加内容字段,更新时自动创建新版本并递增 current_version
- BUG-M3: viking_find scope 参数文档化(设计行为,调用方需传 agent scope)
- BUG-M4: Dashboard 路由缺失已修复,handler 层 require_admin 已正确返回 403

P3 (确认已修复/非代码问题):
- BUG-L1: pain_seed_categories 已统一,无 pain_seeds 残留
- BUG-L2: pipeline_create 参数格式正确,E2E 测试方法问题
2026-04-17 03:31:06 +08:00
iven
1309101a94 fix(ui): Agent 面板信息不随对话更新 — 事件时序 + clones 刷新
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- streamStore: zclaw:agent-profile-updated 事件从记忆提取前改为 .then() 后触发
- RightPanel: profile 更新事件中新增 loadClones() 刷新 selectedClone 数据
2026-04-16 22:57:32 +08:00
iven
0d79993691 fix(saas): 3 项 P0 安全/功能修复 + TRUTH.md 数字校准
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P0-01: Admin ApiKeys 创建功能前后端不匹配
- 前端 service 从 /keys 改回 /tokens(api_tokens 表)
- 前端 UI 字段 {name, expires_days, permissions} 与旧路由匹配

P0-02: 账户锁定检查错误处理
- unwrap_or(false) 改为 map_err + SaasError 传播
- SQL 查询失败时返回错误而非静默跳过锁定检查

P0-03: Logout refresh token 撤销增强
- 新增 access token cookie fallback 提取 account_id
- Tauri 桌面端 Bearer auth 场景下也能撤销 refresh token

TRUTH.md 校准: Tauri 183→190, invoke 95→104, .route() 136→137, 中间件 15→14
2026-04-16 22:22:12 +08:00
iven
a0d1392371 fix(ui): 5 项 E2E 测试 Bug 修复 — Agent 502 / 错误持久化 / 模型标记 / 侧面板 / 记忆页
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- BUG-01: createFromTemplate 在 saas-relay 模式下 try-catch 跳过本地 Kernel
- BUG-02: upsertActiveConversation 持久化前剥离 error/streaming/optimistic 字段
- BUG-04: ModelSelector 添加 available 标记,ChatArea 追踪失败模型 ID
- BUG-05: VikingPanel 移除 status?.available 门控,不可用时 disabled + 重连按钮
- BUG-06: 侧面板 tooltip 改为"查看产物文件",空状态增加图标和说明
2026-04-16 19:12:21 +08:00
iven
7db9eb29a0 fix(butler): useButlerInsights 使用 resolvedAgentId 查询痛点/方案
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审计发现 useButlerInsights 仍使用原始 agentId("1")查询痛点,
而痛点按 kernel UUID 存储导致空结果。改用 effectiveAgentId
(resolvedAgentId ?? agentId)确保查询路径一致。

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-16 17:29:16 +08:00
iven
1e65b56a0f fix(identity): 3 项根因级修复 — Agent ID 映射 + user_profile 读取 + 用户画像 fallback
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Issue 2: IdentityFile 枚举补全 UserProfile 变体
- get_file()/propose_change()/approve_proposal() 补全 match arm
- identity_get_file/identity_propose_change Tauri 命令支持 user_profile

Issue 1: Agent ID 映射机制
- 新增 resolveKernelAgentId() 工具函数 (带缓存)
- ButlerPanel 使用 kernel UUID 替代 SaaS relay "1" 查询 VikingStorage

Issue 3: 用户画像 fallback 注入
- build_system_prompt 改为 async,identity user_profile 为默认值时
  从 VikingStorage preferences 路径查询最近 5 条记忆作为 fallback
- intelligence_hooks 调用处同步加 .await

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-16 17:07:38 +08:00
iven
3c01754c40 fix(agent): 12 项 agent 对话链路全栈修复
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深端到端验证发现 12 个问题,6 Phase 全栈修复:

Phase 5 — 快速 UX 修复:
- #9: SimpleSidebar 添加新对话按钮 (SquarePen + useChatStore)
- #5: 模型列表 JOIN provider_keys 过滤无 API Key 的模型
- #11: AgentOnboardingWizard 焦点领域增加 4 行业选项
  (医疗健康/教育培训/金融财务/法律合规)

Phase 1 — ButlerPanel 记忆修复:
- #2a: MemorySection URI 从 viking://agent/.../memories/ 修正为 agent://.../
- #2b: "立即分析对话"按钮现在触发 extractAndStoreMemories

Phase 2 — FTS5 中文分词:
- #4: FTS5 tokenizer 从 unicode61 切换到 trigram,原生支持 CJK
- 自动迁移:检测旧 unicode61 表并重建索引
- sanitize_fts_query 支持中文引号短语查询

Phase 3 — 跨会话身份持久化:
- #6-8: 重新启用 USER.md 注入系统提示词 (截断前 10 行)

Phase 4 — Agent 面板同步:
- #1,#10: listClones 从 4 字段扩展到完整映射
  (soul/userProfile 解析 nickname/emoji/userName/userRole)
- updateClone 通过 identity 系统同步 nickname→SOUL.md
  和 userName/userRole→USER.md

Phase 6 — Agent 创建容错:
- #12: createFromTemplate 增加 SaaS 不可用 fallback

验证: tsc --noEmit  cargo check 
2026-04-16 09:21:46 +08:00
iven
08af78aa83 docs: 2026-04-16 变更记录 — 参数名修复 + 解密自愈 + 设置清理
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- known-issues.md: 新增 3 条修复记录 (Heartbeat参数/Relay解密/设置清理)
- log.md: 追加 2026-04-16 变更日志
2026-04-16 08:06:02 +08:00
iven
b69dc6115d fix(relay): API Key 解密失败自愈 — 启动迁移 + 容错跳过
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根因: select_best_key 遇到解密失败时直接 500 返回,
不会尝试下一个 key。如果 DB 中有旧的加密格式 key,
整个 relay 请求被阻断。

修复:
- key_pool: 解密失败时 warn + skip 到下一个 key,不再 500
- key_pool: 新增 heal_provider_keys() 启动自愈迁移
  - 逐个尝试解密所有加密 key
  - 解密成功 → 用当前密钥重新加密(幂等)
  - 解密失败 → 标记 is_active=false + warn
- main.rs: 启动时调用自愈迁移(在 TOTP 迁移之后)
2026-04-16 02:40:44 +08:00
iven
7dea456fda chore(settings): 删除用量统计和积分详情页面 — 与订阅计费重复
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UsageStats 和 Credits 功能已被 PricingPage (订阅与计费) 覆盖,
移除冗余页面简化设置导航。
2026-04-16 02:07:39 +08:00
iven
f6c5dd21ce fix(heartbeat): Tauri invoke 参数名修正 snake_case → camelCase
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Tauri 2.x 默认将 Rust snake_case 参数重命名为 camelCase,
前端 invoke 必须使用 camelCase (agentId 而非 agent_id)。

修复 3 处 invoke 调用:
- heartbeat_update_memory_stats (agentId, taskCount, totalEntries, storageSizeBytes)
- heartbeat_record_correction (agentId, correctionType)
- heartbeat_record_interaction (agentId)
2026-04-16 00:03:57 +08:00
iven
47250a3b70 docs: Heartbeat 统一健康系统文档同步 — TRUTH + wiki + CLAUDE.md §13
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- TRUTH.md: Tauri 182→183, React 104→105, lib 85→76
- wiki/index.md: 同步关键数字
- wiki/log.md: 追加 2026-04-15 Heartbeat 变更记录
- CLAUDE.md §13: 更新架构快照 + 最近变更
2026-04-15 23:22:43 +08:00
iven
215c079d29 fix(intelligence): Heartbeat 统一健康系统 — 6处断链修复 + 健康面板 + SaaS自动恢复
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Rust 后端 (heartbeat.rs):
- 告警实时推送: OnceLock<AppHandle> + Tauri emit heartbeat:alert
- 动态间隔: tokio::select! + Notify 替代不可变 interval
- Config 持久化: update_config 写入 VikingStorage
- heartbeat_init 从 VikingStorage 恢复 config
- 移除 dead code (subscribe, HeartbeatCheckFn)
- Memory stats fallback 分层处理

新增 health_snapshot.rs:
- HealthSnapshot Tauri 命令 — 按需查询引擎/记忆状态
- 注册到 lib.rs invoke_handler

前端修复:
- HeartbeatConfig handleSave 同步到 Rust 后端
- App.tsx 读 localStorage 持久化配置 + heartbeat:alert 监听 + toast
- saasStore 降级后指数退避探测恢复 + saas-recovered 事件
- 新增 HealthPanel.tsx 只读健康面板 (4卡片 + 告警列表)
- SettingsLayout 添加 health 导航入口

清理:
- 删除 intelligence-client/ 目录版 (9文件 -1640行, 单文件版是活跃代码)
2026-04-15 23:19:24 +08:00
iven
043824c722 perf(runtime): nl_schedule 正则预编译 — 9个 LazyLock 静态替代每次调用编译
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将 parse_nl_schedule 中 9 个 Regex::new() 从函数内每次调用编译
提升为 std::sync::LazyLock<Regex> 静态变量,首次调用时编译一次,
后续调用直接复用。16 个单元测试全部通过。
2026-04-15 13:34:27 +08:00
iven
bd12bdb62b fix(chat): 定时功能审计修复 — 消除重复解析 + ID碰撞 + 输入补全
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审计发现修复:
- H-01: 存储 ParsedSchedule 避免重复 parse_nl_schedule 调用
- H-03: trigger ID 追加 UUID 片段防止高并发碰撞
- C-02: execute_trigger 验证错误信息明确系统 Hand 必须注册
- M-02: SchedulerService 传递 trigger_name 作为 task_description
- M-01: 添加拦截路径跳过 post_hook 的设计注释
2026-04-15 10:02:49 +08:00
iven
28c892fd31 fix(chat): 聊天定时功能断链接通 — NlScheduleParser + _reminder Hand
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接通"写了没接"的定时功能断链:
- NlScheduleParser has_schedule_intent/parse_nl_schedule 接入 agent_chat_stream
- 新增 _reminder 系统 Hand 作为定时触发器桥接
- TriggerManager hand_id 验证对 _ 前缀系统 Hand 放行
- 聊天消息含定时意图时自动拦截,创建触发器并返回确认消息

验证:cargo check 0 error, 49 tests passed,
Tauri MCP "每天早上9点提醒我查房" → cron 0 9 * * * 确认正确显示
2026-04-15 09:45:19 +08:00
iven
9715f542b6 docs: 发布前冲刺 Day1 文档同步 — TRUTH.md + wiki 数字更新
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- TRUTH.md: Tauri 182命令、95 invoke、89 @reserved、0孤儿、0 Cargo warnings
- wiki/log.md: 追加 Day1 冲刺记录 (5项修复 + 2项标注)
- wiki/index.md: 更新关键数字与验证日期
2026-04-15 02:07:54 +08:00
iven
5121a3c599 chore(desktop): Tauri 命令 @reserved 全量标注 — 88个无前端调用命令已标注
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- 新增 66 个 @reserved 标注 (已有 22 个)
- 覆盖: agent/butler/classroom/hand/mcp/pipeline/skill/trigger/viking/zclaw 等模块
- MCP 命令增加 @connected 注释说明前端接入路径
- @reserved 总数: 89 (含 identity_init)
2026-04-15 02:05:58 +08:00
iven
ee1c9ef3ea chore: Cargo warnings 清零 — 39→0 (仅剩 sqlx-postgres 外部依赖警告)
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- runtime: 移除未使用的 SessionId/Datelike import,修复 unused variable
- intelligence: 模块级 #![allow(dead_code)] 抑制 Hermes 预留代码警告
- mcp.rs/persist.rs/nl_schedule.rs: 标注 #[allow(dead_code)] 保留接口
2026-04-15 01:53:11 +08:00
iven
76d36f62a6 fix(desktop): 模型自动路由 — 首次登录自动选择可用模型
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- saasStore: fetchAvailableModels 处理 currentModel 为空的情况,自动选择第一个可用模型
- connectionStore: SaaS relay 连接成功后同步 currentModel 到 conversationStore
- 同时覆盖 Tauri 和浏览器两条 SaaS relay 路径
- 修复首次登录用户需手动选模型的问题
2026-04-15 01:45:36 +08:00
iven
be2a136392 fix(saas): relay_tasks 超时自动清理 — 每5分钟扫描 processing >10min 标记 failed
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- scheduler.rs: 新增 start_db_cleanup_tasks 中的 relay 超时清理定时任务
- status=processing 且 updated_at 超过 10 分钟的 relay_task 自动标记为 failed
- 避免 Provider key 禁用后 relay_task 永久停留在 processing 状态
2026-04-15 01:41:50 +08:00
iven
76cdfd0c00 fix(saas): SSE 用量统计一致性修复 — 回写 usage_records + 消除 relay_requests 双重计数
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- service.rs: SSE 流结束后回写 usage_records 真实 token (status=success)
- service.rs: spawned task 中调用 increment_usage 统一递增 tokens + relay_requests
- handlers.rs: 移除 SSE 路径的 increment_dimension("relay_requests") 消除双重计数
- 从 request_body 提取 model_id 用于 usage_records 精准归因
2026-04-15 01:40:27 +08:00
iven
02a4ba5e75 fix(desktop): 替换 require() 为 ES import — 修复生产构建崩溃
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- connectionStore: 2 处 require() → loadConversationStore() 异步预加载 + 闭包引用
- saasStore: 1 处 require() → await import()(logout 是 async)
- llm-service: 1 处 require() → 顶层 import(无循环依赖)
- streamStore: 移除重复动态导入,统一使用顶层 useConnectionStore
- tsc --noEmit 0 errors
2026-04-15 00:47:29 +08:00
iven
a8a0751005 docs: wiki 三端联调V2结果 + 调试环境信息
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- known-issues: 新增V2联调测试(17项通过 + 3项待处理 + SSE token修复)
- development: 新增完整调试环境文档(Windows/PostgreSQL/端口/账号/启动顺序)
- log: 追加V2联调记录
2026-04-15 00:40:05 +08:00
iven
9c59e6e82a fix(saas): SSE relay token capture 修复 — stream_done 标志 + 前缀兼容
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- SseUsageCapture 增加 stream_done 标志,[DONE] 和 stream 结束时设置
- parse_sse_line 兼容 "data:" 和 "data: " 两种前缀
- 增加 total_tokens 兜底解析(某些 provider 不返回 prompt_tokens)
- 轮询逻辑优先检测 stream_done,而非依赖 total > 0 条件
- 超时时增加 warn 日志记录实际 token 值

根因: 上游 provider 不在 SSE chunk 中返回 usage 时,轮询稳定逻辑
(total > 0 条件) 永远不满足,导致 token 始终为 0。
2026-04-15 00:15:03 +08:00
iven
27b98cae6f docs: wiki 全量更新 — 2026-04-14 代码验证驱动
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关键数字修正:
- Rust 77K行(274 .rs)、Tauri 189命令、SaaS 137 routes
- Admin V2 17页、SaaS 16模块(含industry)、@reserved 22
- SQL 20迁移/42表、TODO/FIXME 4个、dead_code 16

内容更新:
- known-issues: V13-GAP 全部标记已修复 + 三端联调测试结果
- middleware: 14层 runtime + 10层 SaaS HTTP 完整清单
- saas: industry模块、路由模块13个、数据表42个
- routing: Store含industryStore、21个Store文件
- butler: 行业配置接入ButlerPanel、4内置行业
- log: 三端联调+V13修复记录追加
2026-04-14 22:15:53 +08:00
iven
d0aabf5f2e fix(test): pain_severity 测试断言修正 + 调试文档代码验证更新
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- test_severity_ordering: 修正错误断言 — 2条挫折信号应触发High而非Medium
- DEBUGGING_PROMPT.md: 全量代码验证更新
  - 数字修正: 97组件/81lib/189命令/137路由/8 Worker
  - V13-GAP 状态更新: 5/6 已修复, 1 标注 DEPRECATED
  - 中间件优先级修正: ButlerRouter@80, DataMasking@90
  - SaaS Relay: resolve_model() 三级解析 (非精确匹配)
2026-04-14 22:03:51 +08:00
iven
3c42e0d692 docs: 三端联调测试报告 V2 — P1 修复状态更新 + 测试截图
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30+ API/16 Admin/8 Tauri 全量测试,3 P1 已修复
2026-04-14 22:02:27 +08:00
iven
e0eb7173c5 fix: 三端联调 P1 修复 — API密钥页崩溃 + 桌面端401恢复 + 用量统计全零
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P1-03: vite.config.ts proxy '/api' → '/api/' 加尾部斜杠,
  防止前缀匹配 /api-keys 导致 SPA 路由崩溃

P1-01: kernel_init 增加 api_key 变更检测(token 刷新后自动重连),
  streamStore 增加 401 自动恢复(refresh token → kernel reconnect),
  KernelClient 新增 getConfig() 方法

P1-02: /api/v1/usage 总计改从 billing_usage_quotas 读取
  (authoritative source,SSE 和 JSON 均写入),
  by_model/by_day 仍从 usage_records 读取
2026-04-14 22:02:02 +08:00
iven
6721a1cc6e fix(admin): 行业选择500修复 + 管理员切换订阅计划
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- fix(industry): list_industries SQL参数编号错位 — count查询和items查询
  共用WHERE子句但参数从$3开始,sqlx bind按$1/$2顺序绑定导致500
- feat(billing): 新增 PUT /admin/accounts/:id/subscription 端点 (super_admin)
  验证目标计划 → 取消当前订阅 → 创建新订阅(30天) → 同步配额
- feat(admin-v2): Accounts.tsx 编辑弹窗新增「订阅计划」选择区
  显示所有活跃计划,保存时调用admin switch plan API
2026-04-14 19:06:58 +08:00
iven
d2a0c8efc0 fix(saas): 启动崩溃修复 — config_items 约束 + industry 类型匹配
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- db.rs: config_items INSERT ON CONFLICT (id) → (category, key_path) 匹配实际唯一约束
- db.rs: fix_seed_data category 重命名前先删除冲突行,避免唯一约束冲突
- migration/service.rs: seed_default_config_items + sync push INSERT 同步修复 ON CONFLICT
- industry/types.rs: keywords_count i64→i32 匹配 PostgreSQL INT4 列类型

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-14 18:35:24 +08:00
iven
70229119be docs: 三端联调测试报告 2026-04-14 — 30+ API/16 Admin/8 Tauri 全量测试
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2026-04-14 17:48:31 +08:00
iven
dd854479eb fix: 三端联调测试 2 P1 + 2 P2 + 4 P3 修复
P1-07: billing get_or_create_usage 同步 max_* 列到当前计划限额
P1-08: relay handler 增加直接配额检查 (relay_requests/input/output_tokens)
P2-09: relay failover 成功后记录 tokens 并标记 completed
P2-10: Tauri agentStore saas-relay 模式下从 SaaS API 获取真实用量
P2-14: super_admin 合成 subscription + check_quota 放行
P3-19: 新建 ApiKeys.tsx 页面替代 ModelServices 路由
P3-15: antd destroyOnClose → destroyOnHidden (3处)
P3-16: ProTable onSearch → onSubmit (2处)
2026-04-14 17:48:22 +08:00
iven
45fd9fee7b fix(desktop): P0-1 验证 SaaS 模型选择 — 防止残留模型 ID 导致请求失败
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Tauri 桌面端通过 SaaS Token Pool 中转访问 LLM,模型列表由 SaaS 后端
动态提供。之前的实现直接使用 conversationStore 持久化的 currentModel,
可能在切换连接模式后使用过期的模型 ID,导致 relay 请求失败。

修复:
- Tauri 路径:用 SaaS relayModels 的 id+alias 构建 validModelIds 集合,
  preferredModel 仅在集合内时才使用,否则回退到第一个可用模型
- 浏览器路径:同样验证 currentModel 在 SaaS 模型列表中才使用

后端 cache.resolve_model() 别名解析作为二道防线保留。
2026-04-14 07:08:56 +08:00
iven
4c3136890b fix: 三端联调测试 2 P0 + 6 P1 + 2 P2 修复
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P0-1: SaaS relay 模型别名解析 — "glm-4-flash" → "glm-4-flash-250414" (resolve_model)
P0-2: config.rs interpolate_env_vars UTF-8 修复 (chars 迭代器替代 bytes as char)
      + DB 启动编码检查 + docker-compose UTF-8 编码参数

P1-3: UI 模型选择器覆盖 Agent 默认模型 (model_override 全链路: TS→Tauri→Rust kernel)
P1-6: 知识搜索管道修复 — seed_knowledge 创建 chunks + 默认分类 (seed/uploaded/distillation)
P1-7: 用量限额从当前 Plan 读取 (非 stale usage 表)
P1-8: relay 双维度配额检查 (relay_requests + input_tokens)

P2-9: SSE 路径 token 计数修复 — 流结束检测替代固定 500ms sleep + billing increment
2026-04-14 00:17:08 +08:00
iven
0903a0d652 fix(v13): FIX-06 PersistentMemoryStore 全量移除 — 665行死代码清理
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- persistent.rs 611→57行: 移除 PersistentMemoryStore struct + 全部方法 + 死 embedding global
- memory_commands.rs: MemoryStoreState→Arc<Mutex<()>>, memory_init→no-op, 移除 2 @reserved 命令
- viking_commands.rs: 移除冗余 PersistentMemoryStore embedding 配置段
- lib.rs: Tauri 命令 191→189 (移除 memory_configure_embedding + memory_is_embedding_configured)
- TRUTH.md + wiki/log.md 数字同步

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-13 20:58:54 +08:00
iven
fd3e7fd2cb docs: V13 审计修复文档同步 — 6项状态更新 + 中间件14→15层
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AUDIT_TRACKER: V13-GAP-01~05 FIXED, GAP-06 PARTIALLY_FIXED
wiki/middleware: 15层 (TrajectoryRecorder V13注册)
wiki/log: 2026-04-13 变更记录
CLAUDE.md: 中间件链 14→15 层

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-13 01:38:55 +08:00
iven
c167ea4ea5 fix(v13): V13 审计 6 项修复 — TrajectoryRecorder注册 + industryStore接入 + 知识搜索 + webhook标注 + structured UI + persistent注释
FIX-01: TrajectoryRecorderMiddleware 注册到 create_middleware_chain() (@650优先级)
FIX-02: industryStore 接入 ButlerPanel 行业专长展示 + 自动拉取
FIX-03: 桌面端知识库搜索 saas-knowledge mixin + VikingPanel SaaS KB UI
FIX-04: webhook 迁移标注 deprecated + 添加 down migration 注释
FIX-05: Admin Knowledge 添加结构化数据 Tab (CRUD + 行浏览)
FIX-06: PersistentMemoryStore 精化 dead_code 标注 (完整迁移留后续)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-13 01:34:08 +08:00
iven
c048cb215f docs: V13 系统性功能审计 — 6 项新发现 + TRUTH.md 数字校准
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V13 审计聚焦 V12 后新增功能 (行业配置/Knowledge/Hermes/管家主动性):
- 总体健康度 82/100 (V12: 76)
- P1 新发现 3 项: TrajectoryRecorder 未注册/industryStore 孤立/桌面端无 Knowledge Search
- P2 新发现 3 项: Webhook 孤儿表/Structured Data 无 Admin/PersistentMemoryStore 遗留
- 修正 V12 错误认知 5 项: Butler/MCP/Gateway/Presentation 已接通
- TRUTH.md 数字校准: Tauri 184→191, SaaS 122→136, @reserved 33→24
2026-04-12 23:33:13 +08:00
iven
f32216e1e0 docs: 添加发散探讨文档和测试截图
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添加了关于管家主动性与行业配置体系的发散探讨文档,包含现状诊断、关键讨论、架构设计等内容。同时添加了测试失败的截图和日志文件。
2026-04-12 22:40:45 +08:00
iven
d5cb636e86 docs: wiki变更日志 — 三轮审计修复记录
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2026-04-12 21:05:06 +08:00
iven
0b512a3d85 fix(industry): 三轮审计修复 — 3 HIGH + 4 MEDIUM 清零
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H1: status 值不匹配 disabled→inactive + source 补 admin 映射 + valueEnum
H2: experience.rs format_for_injection 添加 xml_escape
H3: TriggerContext industry_keywords 接通全局缓存
M2: ID 自动生成移除中文字符保留 + 无 ASCII 时提示手动输入
M3: TS CreateIndustryRequest 添加 id? 字段
M4: ListIndustriesQuery 添加 deny_unknown_fields
2026-04-12 21:04:00 +08:00
iven
168dd87af4 docs: wiki变更日志 — Phase D 统一搜索+种子知识
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2026-04-12 20:48:14 +08:00
iven
640df9937f feat(knowledge): Phase D 统一搜索 + 种子知识冷启动
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- search/recommend API 返回 UnifiedSearchResult (文档+结构化双通道)
- POST /api/v1/knowledge/seed 种子知识冷启动 (幂等, admin权限)
- seed_knowledge service: 按标题+行业查重, source=distillation
- SearchRequest 扩展: search_structured/search_documents/industry_id
2026-04-12 20:46:43 +08:00
iven
f8c5a76ce6 fix(industry): 审计收尾 — MEDIUM + LOW 全部清零
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M-1: Industries 创建弹窗添加 cold_start_template + pain_seed_categories
M-3: industryStore console.warn → createLogger 结构化日志
B2: classify_with_industries 平局打破 + 归一化因子 3.0 文档化
S3: set_account_industries 验证移入事务内消除 TOCTOU
T1: 4 个 SaaS 请求类型添加 deny_unknown_fields
I3: store_trigger_experience Debug 格式 → signal_name 描述名
L-1: 删除 Accounts.tsx 死代码 editingIndustries
L-3: Industries.tsx filters 类型补全 source 字段
2026-04-12 20:37:48 +08:00
iven
3cff31ec03 docs: wiki变更日志 — 二次审计修复记录
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2026-04-12 20:14:52 +08:00
iven
76f6011e0f fix(industry): 二次审计修复 — 2 CRITICAL + 4 HIGH + 2 MEDIUM
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C-1: Industries.tsx 创建弹窗缺少 id 字段 → 添加 id 输入框 + 自动生成
C-2: Accounts.tsx handleSave 无 try/catch → 包装 + handleClose 统一关闭
V1: viking_commands Mutex 跨 await → 先 clone Arc 再释放 Mutex
I1: intelligence_hooks 误导性"相关度" → 移除 access_count 伪分数
I2: pain point 摘要未 XML 转义 → xml_escape() 处理
S1: industry status 无枚举验证 → active/inactive 白名单
S2: create_industry id 无格式验证 → 正则 + 长度检查
H-3: Industries.tsx 编辑模态数据竞争 → data.id === industryId 守卫
H-4: Accounts.tsx useEffect 覆盖用户编辑 → editingId 守卫
2026-04-12 20:13:41 +08:00
iven
0f9211a7b2 docs: wiki变更日志 — Phase B+C 文档提取器+multipart上传
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2026-04-12 19:26:18 +08:00
iven
60062a8097 feat(knowledge): Phase B+C 文档提取器 + multipart 文件上传
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- PDF 提取 (pdf-extract) + DOCX 提取 (zip+quick-xml) + Excel 解析 (calamine)
- 统一格式路由 detect_format() → RAG 通道或结构化通道
- POST /api/v1/knowledge/upload multipart 文件上传
- PDF/DOCX/Markdown → RAG 管线,Excel → structured_rows JSONB
- 结构化数据源 CRUD API (GET/DELETE /api/v1/structured/sources)
- POST /api/v1/structured/query JSONB 关键词查询
- 修复 industry/service.rs SaasError::Database 类型不匹配
2026-04-12 19:25:24 +08:00
iven
4800f89467 docs: wiki变更日志 — 审计修复记录
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2026-04-12 19:06:49 +08:00
iven
fbc8c9fdde fix(industry): 审计修复 — 4 CRITICAL + 5 HIGH 全部解决
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C1: SaaS industry/service.rs SQL 注入风险 → 参数化查询 ($N 绑定)
C2: INDUSTRY_CONFIGS 死链 → Kernel 共享 Arc 接通 ButlerRouter
C3: IndustryListItem 缺 keywords_count → SQL 查询 + 类型补全
C4: set_account_industries 非事务性 → batch 验证 + 事务 DELETE+INSERT
H8: Accounts.tsx mutate 竞态 → mutateAsync 顺序等待
H9: XML 注入未转义 → xml_escape() 辅助函数
H10: update_industry 覆盖 source → 保留原始值
H11: 面包屑缺少 /industries → 添加行业配置映射
2026-04-12 19:06:19 +08:00
iven
c3593d3438 feat(knowledge): Phase A 知识库可见性隔离 + 结构化数据源 + 蒸馏Worker
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- knowledge_items 增加 visibility(public/private) + account_id 字段
- 新建 structured_sources + structured_rows 表 (Excel JSONB 行级存储)
- 结构化数据源 CRUD API (5 路由: list/get/rows/delete/query)
- 安全查询: JSONB GIN 索引 + 可见性过滤 + 行数限制
- 蒸馏 Worker: 复用 Provider Key Pool 调 DeepSeek/Qwen API
- L0 质量过滤: 长度/隐私检测
- create_item 增加 is_admin 参数控制可见性默认值
- generate_embedding: extract_keywords_from_text 改为 pub 复用

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-12 18:36:05 +08:00
iven
b8fb76375c docs: wiki变更日志 + CLAUDE.md架构快照更新 (Phase 1-5完成)
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2026-04-12 18:34:14 +08:00
iven
b357916d97 feat(intelligence): Phase 5 主动行为激活 — 注入格式 + 跨会话连续性 + 触发持久化
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Task 5.1+5.4: ButlerRouter/experience 注入格式升级为 <butler-context> XML fencing
- butler_router: [路由上下文] → <butler-context><routing>...</routing></butler-context>
- experience: [过往经验] → <butler-context><experience>...</experience></butler-context>
- 统一 system-note 提示,引导 LLM 自然运用上下文

Task 5.2: 跨会话连续性 — pre_conversation_hook 注入活跃痛点 + 相关经验
- 从 VikingStorage 检索相关记忆(相似度>=0.3)
- 从 pain_aggregator 获取 High severity 痛点(top 3)

Task 5.3: 触发信号持久化 — post_conversation_hook 将触发信号存入 VikingStorage
- store_trigger_experience(): 模板提取,零 LLM 成本
- 为未来 LLM 深度反思积累数据基础
2026-04-12 18:31:37 +08:00
iven
edf66ab8e6 feat(admin): Phase 4 行业配置管理页面 + 账号行业授权
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- 新增 Industries.tsx: 行业列表(ProTable) + 编辑弹窗(关键词/prompt/痛点种子) + 新建弹窗
- 新增 services/industries.ts: 行业 API 服务层(list/create/update/fullConfig/accountIndustries)
- 增强 Accounts.tsx: 编辑弹窗添加行业授权多选, 自动获取/同步用户行业
- 注册 /industries 路由 + 侧边栏导航(ShopOutlined)
2026-04-12 18:07:52 +08:00
iven
b853978771 feat(industry): Phase 3 Tauri 行业配置加载 — SaaS API mixin + industryStore + Tauri 命令
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- 新增 saas-industry.ts mixin: listIndustries/getIndustryFullConfig/getMyIndustries
- 新增 saas-types 行业类型: IndustryInfo/IndustryFullConfig/AccountIndustryItem
- 新增 industryStore.ts: Zustand store + localStorage persist + Rust 注入
- 新增 viking_load_industry_keywords Tauri 命令: 接收 JSON configs → 全局存储
- 前端 bootstrap 后自动拉取行业配置并推送到 ButlerRouter
2026-04-12 17:18:53 +08:00
iven
29fbfbec59 feat(intelligence): Phase 2 学习循环基础 — 触发信号 + 经验行业维度
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- 新增 triggers.rs: 5 种触发信号(痛点确认/正反馈/复杂工具链/用户纠正/行业模式)
- ExperienceStore 增加 industry_context + source_trigger 字段
- experience.rs format_for_injection 支持行业标签
- intelligence_hooks.rs 集成触发信号评估
- 17 个测试全通过 (7 trigger + 10 experience)
2026-04-12 15:52:29 +08:00
iven
5d1050bf6f feat(industry): Phase 1 行业配置基础 — 数据模型 + 四行业内置配置 + ButlerRouter 动态关键词
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- 新增 SaaS industry 模块 (types/service/handlers/mod/builtin)
- 4 行业内置配置: healthcare/education/garment/ecommerce
- 数据库迁移: industries + account_industries 表
- 8 个 API 端点 (CRUD + 用户行业关联)
- ButlerRouter 改造: 支持 IndustryKeywordConfig 动态注入
- 12 个测试全通过 (含动态行业分类测试)
2026-04-12 15:42:35 +08:00
iven
5599cefc41 feat(saas): 接通 embedding 模型管理全栈
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数据库 migration 已有 is_embedding/model_type 列但全栈未使用。
打通 4 层: ModelRow → ModelInfo/CRUD → CachedModel → Admin 前端。
relay/models 端点也返回 is_embedding 字段,前端可按类型过滤。
2026-04-12 08:10:50 +08:00
iven
b0a304ca82 docs: TRUTH.md 数字校准 + wiki 变更日志
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- TRUTH.md 全面更新 2026-04-11 验证数字
  - Rust 代码 66K→74.6K, 测试 537→798, Tauri 命令 182→184
  - SaaS .route() 140→122, Store 18→20, 组件 135→104
- wiki/log.md 追加发布前准备记录
2026-04-11 23:52:28 +08:00
iven
58aca753aa chore: 发布前准备 — 版本号统一 + 安全加固 + 死组件清理
- Cargo.toml workspace version 0.1.0 → 0.9.0-beta.1
- CSP 添加 object-src 'none' 防止插件注入
- .env.example 补充 SaaS 关键环境变量模板
- 移除已废弃的 SkillMarket.tsx 组件
2026-04-11 23:51:58 +08:00
iven
e1af3cca03 fix(routing): 消除模型路由链路硬编码不匹配模型名
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summarizer_adapter.rs 和 saas-relay-client.ts 中的 fallback 模型名
(glm-4-flash / glm-4-flash-250414) 在 SaaS relay 中不存在,导致请求被拒绝。
改为未配置时明确报错(fail fast),不再静默使用错误模型。
2026-04-11 23:08:06 +08:00
iven
5fcc4c99c1 docs(wiki): 添加 Skill 调用链路 + MCP 架构文档
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- hands-skills.md 标题改为 Hands + Skills + MCP
- 添加 Skill 调用链路说明 (ToolRegistry → AgentLoop → execute_skill)
- 添加 MCP 完整架构 (BasicMcpClient → McpToolAdapter → McpToolWrapper → ToolRegistry)
- 添加 MCP 桥接机制说明 (Arc<RwLock> 共享 + sync_to_kernel)
- 更新关键文件表 (新增 mcp_tool.rs, anthropic.rs, mcp.rs 等)
- 更新 index.md 导航树 + log.md 变更记录
2026-04-11 16:23:31 +08:00
iven
9e0aa496cd fix(runtime): 修复 Skill/MCP 调用链路3个断点
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1. Anthropic Driver ToolResult 格式修复 — ContentBlock 添加 ToolResult 变体,
   tool_call_id 不再被丢弃, 按 Anthropic API 规范发送 tool_result 格式
2. 前端 callMcpTool 参数名对齐 — serviceName/toolName/args 改为
   service_name/tool_name/arguments, 后端支持 service_name 精确路由
3. MCP 工具桥接到 ToolRegistry — McpToolAdapter 添加 service_name/clone,
   新建 McpToolWrapper 实现 Tool trait, Kernel 添加 mcp_adapters 共享状态,
   McpManagerState 与 Kernel 共享同一 Arc<RwLock<Vec>>, MCP 服务启停时
   自动同步工具列表到 LLM 可见的 ToolRegistry
2026-04-11 16:20:38 +08:00
iven
2843bd204f chore: 更新测试注释 — 阈值已从 5 降为 3
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2026-04-11 14:26:53 +08:00
iven
05374f99b0 chore: 移除未使用的 loadConnectionModeTimestamp 函数 2026-04-11 14:26:52 +08:00
iven
c88e3ac630 fix(kernel): UserProfile 序列化失败时记录 warn 而非静默吞掉 2026-04-11 14:26:52 +08:00
iven
dc94a5323a fix(butler): 降低痛点检测阈值 3→2/2→1,更早发现用户需求 2026-04-11 14:26:51 +08:00
iven
69d3feb865 fix(lint): IdentityChangeProposal console.error → createLogger 2026-04-11 14:26:50 +08:00
iven
3927c92fa8 docs: 详情面板7问题修复记录
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2026-04-11 12:59:04 +08:00
485 changed files with 35635 additions and 10388 deletions

View File

@@ -44,3 +44,12 @@ ZCLAW_EMBEDDING_MODEL=text-embedding-3-small
# === Logging === # === Logging ===
# 可选: debug, info, warn, error # 可选: debug, info, warn, error
ZCLAW_LOG_LEVEL=info ZCLAW_LOG_LEVEL=info
# === SaaS Backend ===
ZCLAW_SAAS_JWT_SECRET=
ZCLAW_TOTP_ENCRYPTION_KEY=
ZCLAW_ADMIN_USERNAME=
ZCLAW_ADMIN_PASSWORD=
DB_PASSWORD=
ZCLAW_DATABASE_URL=
ZCLAW_SAAS_DEV=false

View File

@@ -50,7 +50,7 @@ jobs:
- name: Rust Clippy - name: Rust Clippy
working-directory: . working-directory: .
run: cargo clippy --workspace -- -D warnings run: cargo clippy --workspace --exclude zclaw-saas -- -D warnings
- name: Install frontend dependencies - name: Install frontend dependencies
working-directory: desktop working-directory: desktop
@@ -94,7 +94,7 @@ jobs:
- name: Run Rust tests - name: Run Rust tests
working-directory: . working-directory: .
run: cargo test --workspace run: cargo test --workspace --exclude zclaw-saas
- name: Install frontend dependencies - name: Install frontend dependencies
working-directory: desktop working-directory: desktop
@@ -138,7 +138,7 @@ jobs:
- name: Rust release build - name: Rust release build
working-directory: . working-directory: .
run: cargo build --release --workspace run: cargo build --release --workspace --exclude zclaw-saas
- name: Install frontend dependencies - name: Install frontend dependencies
working-directory: desktop working-directory: desktop

View File

@@ -45,7 +45,7 @@ jobs:
- name: Run Rust tests - name: Run Rust tests
working-directory: . working-directory: .
run: cargo test --workspace run: cargo test --workspace --exclude zclaw-saas
- name: Install frontend dependencies - name: Install frontend dependencies
working-directory: desktop working-directory: desktop

View File

@@ -227,21 +227,22 @@ Client → 负责网络通信和协议转换
## 6. 自主能力系统 (Hands) ## 6. 自主能力系统 (Hands)
ZCLAW 提供 11 个自主能力包(9 启用 + 2 禁用): ZCLAW 提供 12 个自主能力包(7 已注册 + 3 开发中 + 2 禁用):
| Hand | 功能 | 状态 | | Hand | 功能 | 状态 |
|------|------|------| |------|------|------|
| Browser | 浏览器自动化 | ✅ 可用 | | Browser | 浏览器自动化 | ✅ 可用 |
| Collector | 数据收集聚合 | ✅ 可用 | | Collector | 数据收集聚合 | ✅ 可用 |
| Researcher | 深度研究 | ✅ 可用 | | Researcher | 深度研究 | ✅ 可用 |
| Predictor | 预测分析 | ❌ 已禁用 (enabled=false),无 Rust 实现 |
| Lead | 销售线索发现 | ❌ 已禁用 (enabled=false),无 Rust 实现 |
| Clip | 视频处理 | ⚠️ 需 FFmpeg | | Clip | 视频处理 | ⚠️ 需 FFmpeg |
| Twitter | Twitter 自动化 | ✅ 可用12 个 API v2 真实调用,写操作需 OAuth 1.0a | | Twitter | Twitter 自动化 | ✅ 可用12 个 API v2 真实调用,写操作需 OAuth 1.0a |
| Whiteboard | 白板演示 | ✅ 可用(导出功能开发中,标注 demo |
| Slideshow | 幻灯片生成 | ✅ 可用 |
| Speech | 语音合成 | ✅ 可用Browser TTS 前端集成完成) |
| Quiz | 测验生成 | ✅ 可用 | | Quiz | 测验生成 | ✅ 可用 |
| _reminder | 系统内部提醒 | ✅ 可用kernel 编程注册,无 HAND.toml |
| Whiteboard | 白板演示 | 🚧 开发中HAND.toml 未合并到主分支) |
| Slideshow | 幻灯片生成 | 🚧 开发中HAND.toml 未合并到主分支) |
| Speech | 语音合成 | 🚧 开发中HAND.toml 未合并到主分支) |
| Predictor | 预测分析 | ❌ 已禁用 (enabled=false),无 Rust 实现 |
| Lead | 销售线索发现 | ❌ 已禁用 (enabled=false),无 Rust 实现 |
**触发 Hand 时:** **触发 Hand 时:**
1. 检查依赖是否满足 1. 检查依赖是否满足
@@ -529,7 +530,7 @@ refactor(store): 统一 Store 数据获取方式
*** ***
<!-- ARCH-SNAPSHOT-START --> <!-- ARCH-SNAPSHOT-START -->
<!-- 此区域由 auto-sync 自动更新,请勿手动编辑。更新时间: 2026-04-09 --> <!-- 此区域由 auto-sync 自动更新,请勿手动编辑。更新时间: 2026-04-15 -->
## 13. 当前架构快照 ## 13. 当前架构快照
@@ -537,33 +538,37 @@ refactor(store): 统一 Store 数据获取方式
| 子系统 | 状态 | 最新变更 | | 子系统 | 状态 | 最新变更 |
|--------|------|----------| |--------|------|----------|
| 管家模式 (Butler) | ✅ 活跃 | 04-09 ButlerRouter + 双模式UI + 痛点持久化 + 冷启动 | | 管家模式 (Butler) | ✅ 活跃 | 04-12 行业配置4行业 + 跨会话连续性 + <butler-context> XML fencing |
| Hermes 管线 | ✅ 活跃 | 04-09 4 Chunk: 自我改进+用户建模+NL Cron+轨迹压缩 (684 tests) | | Hermes 管线 | ✅ 活跃 | 04-12 触发信号持久化 + 经验行业维度 + 注入格式优化 |
| Intelligence Heartbeat | ✅ 活跃 | 04-15 统一健康快照 (health_snapshot.rs) + HeartbeatManager 重构 + HealthPanel 前端 |
| 聊天流 (ChatStream) | ✅ 稳定 | 04-02 ChatStore 拆分为 4 Store (stream/conversation/message/chat) | | 聊天流 (ChatStream) | ✅ 稳定 | 04-02 ChatStore 拆分为 4 Store (stream/conversation/message/chat) |
| 记忆管道 (Memory) | ✅ 稳定 | 04-02 闭环修复: 对话→提取→FTS5+TF-IDF→检索→注入 | | 记忆管道 (Memory) | ✅ 稳定 | 04-17 E2E 验证: 存储+FTS5+TF-IDF+注入闭环,去重+跨会话注入已修复 |
| SaaS 认证 (Auth) | ✅ 稳定 | Token池 RPM/TPM 轮换 + JWT password_version 失效机制 | | SaaS 认证 (Auth) | ✅ 稳定 | Token池 RPM/TPM 轮换 + JWT password_version 失效机制 |
| Pipeline DSL | ✅ 稳定 | 04-01 17 个 YAML 模板 + DAG 执行器 | | Pipeline DSL | ✅ 稳定 | 04-01 17 个 YAML 模板 + DAG 执行器 |
| Hands 系统 | ✅ 稳定 | 9 启用 (Browser/Collector/Researcher/Twitter/Whiteboard/Slideshow/Speech/Quiz/Clip) | | Hands 系统 | ✅ 稳定 | 7 注册 (6 HAND.toml + _reminder)Whiteboard/Slideshow/Speech 开发中 |
| 技能系统 (Skills) | ✅ 稳定 | 75 个 SKILL.md + 语义路由 | | 技能系统 (Skills) | ✅ 稳定 | 75 个 SKILL.md + 语义路由 |
| 中间件链 | ✅ 稳定 | 14 层 ( DataMasking@90, ButlerRouter, TrajectoryRecorder@650) | | 中间件链 | ✅ 稳定 | 14 层 (ButlerRouter@80, DataMasking@90, Compaction@100, Memory@150, Title@180, SkillIndex@200, DanglingTool@300, ToolError@350, ToolOutputGuard@360, Guardrail@400, LoopGuard@500, SubagentLimit@550, TrajectoryRecorder@650, TokenCalibration@700) |
### 关键架构模式 ### 关键架构模式
- **Hermes 管线**: 4模块闭环 — ExperienceStore(FTS5经验存取) + UserProfiler(结构化用户画像) + NlScheduleParser(中文时间→cron) + TrajectoryRecorder+Compressor(轨迹记录压缩)。通过中间件链+intelligence hooks调用 - **Hermes 管线**: 4模块闭环 — ExperienceStore(FTS5经验存取) + UserProfiler(结构化用户画像) + NlScheduleParser(中文时间→cron) + TrajectoryRecorder+Compressor(轨迹记录压缩)。通过中间件链+intelligence hooks调用
- **管家模式**: 双模式UI (默认简洁/解锁专业) + ButlerRouter 4域关键词分类 (healthcare/data_report/policy/meeting) + 冷启动4阶段hook (idle→greeting→waiting→completed) + 痛点双写 (内存Vec+SQLite) - **管家模式**: 双模式UI (默认简洁/解锁专业) + ButlerRouter 动态行业关键词(4内置+自定义) + <butler-context> XML fencing注入 + 跨会话连续性(痛点回访+经验检索) + 触发信号持久化(VikingStorage) + 冷启动4阶段hook
- **聊天流**: 3种实现 → GatewayClient(WebSocket) / KernelClient(Tauri Event) / SaaSRelay(SSE) + 5min超时守护。详见 [ARCHITECTURE_BRIEF.md](docs/ARCHITECTURE_BRIEF.md) - **聊天流**: 3种实现 → GatewayClient(WebSocket) / KernelClient(Tauri Event) / SaaSRelay(SSE) + 5min超时守护。详见 [ARCHITECTURE_BRIEF.md](docs/ARCHITECTURE_BRIEF.md)
- **客户端路由**: `getClient()` 4分支决策树 → Admin路由 / SaaS Relay(可降级到本地) / Local Kernel / External Gateway - **客户端路由**: `getClient()` 4分支决策树 → Admin路由 / SaaS Relay(可降级到本地) / Local Kernel / External Gateway
- **SaaS 认证**: JWT→OS keyring 存储 + HttpOnly cookie + Token池 RPM/TPM 限流轮换 + SaaS unreachable 自动降级 - **SaaS 认证**: JWT→OS keyring 存储 + HttpOnly cookie + Token池 RPM/TPM 限流轮换 + SaaS unreachable 自动降级
- **记忆闭环**: 对话→extraction_adapter→FTS5全文+TF-IDF权重→检索→注入系统提示 - **记忆闭环**: 对话→extraction_adapter→FTS5全文+TF-IDF权重→检索→注入系统提示E2E 04-17 验证通过,去重+跨会话注入已修复)
- **LLM 驱动**: 4 Rust Driver (Anthropic/OpenAI/Gemini/Local) + 国内兼容 (DeepSeek/Qwen/Moonshot 通过 base_url) - **LLM 驱动**: 4 Rust Driver (Anthropic/OpenAI/Gemini/Local) + 国内兼容 (DeepSeek/Qwen/Moonshot 通过 base_url)
### 最近变更 ### 最近变更
1. [04-09] Hermes Intelligence Pipeline 4 Chunk: ExperienceStore+Extractor, UserProfileStore+Profiler, NlScheduleParser, TrajectoryRecorder+Compressor (684 tests, 0 failed) 1. [04-21] Embedding 接通 + 自学习自动化 A线+B线: 记忆检索Embedding(GrowthIntegration→MemoryRetriever→SemanticScorer) + Skill路由Embedding+LLM Fallback(替换new_tf_idf_only) + evolution_bridge(SkillCandidate→SkillManifest) + generate_and_register_skill()全链路 + EvolutionMiddleware双模式(auto/suggest) + QualityGate加固(长度/标题/置信度上限)。验证: 934 tests PASS
2. [04-09] 管家模式6交付物完成: ButlerRouter + 冷启动 + 简洁模式UI + 桥测试 + 发布文档 2. [04-21] Phase 0+1 突破之路 8 项基础链路修复: 经验积累覆盖修复(reuse_count累积) + Skill工具调用桥接(complete_with_tools) + Hand字段映射(runId) + Heartbeat痛点感知 + Browser委托消息 + 跨会话检索增强(IdentityRecall 26→43模式+弱身份fallback) + Twitter凭据持久化。验证: 912 tests PASS
3. [04-08] 侧边栏 AnimatePresence bug + TopBar 重复 Z 修复 + 发布评估报告 2. [04-17] 全系统 E2E 测试 129 链路: 82 PASS / 20 PARTIAL / 1 FAIL / 26 SKIP有效通过率 79.1%。7 项 Bug 修复 (Dashboard 404/记忆去重/记忆注入/invoice_id/Prompt版本/agent隔离/行业字段)
3. [04-07] @reserved 标注 5 个 butler Tauri 命令 + 痛点持久化 SQLite 2. [04-16] 3 项 P0 修复 + 5 项 E2E Bug 修复 + Agent 面板刷新 + TRUTH.md 数字校准
4. [04-06] 4 个发布前 bug 修复 (身份覆盖/模型配置/agent同步/自动身份) 3. [04-15] Heartbeat 统一健康系统: health_snapshot.rs 统一收集器(LLM连接/记忆/会话/系统资源) + heartbeat.rs HeartbeatManager 重构 + HealthPanel.tsx 前端面板 + Tauri 命令 182→183 + intelligence 模块 15→16 文件 + 删除 intelligence-client/ 9 废弃文件
4. [04-12] 行业配置+管家主动性 全栈 5 Phase: 行业数据模型+4内置配置+ButlerRouter动态关键词+触发信号+Tauri加载+Admin管理页面+跨会话连续性+XML fencing注入格式
5. [04-09] Hermes Intelligence Pipeline 4 Chunk: ExperienceStore+Extractor, UserProfileStore+Profiler, NlScheduleParser, TrajectoryRecorder+Compressor (684 tests, 0 failed)
6. [04-09] 管家模式6交付物完成: ButlerRouter + 冷启动 + 简洁模式UI + 桥测试 + 发布文档
<!-- ARCH-SNAPSHOT-END --> <!-- ARCH-SNAPSHOT-END -->

774
Cargo.lock generated

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@@ -19,7 +19,7 @@ members = [
] ]
[workspace.package] [workspace.package]
version = "0.1.0" version = "0.9.0-beta.1"
edition = "2021" edition = "2021"
license = "Apache-2.0 OR MIT" license = "Apache-2.0 OR MIT"
repository = "https://github.com/zclaw/zclaw" repository = "https://github.com/zclaw/zclaw"
@@ -57,12 +57,15 @@ chrono = { version = "0.4", features = ["serde"] }
uuid = { version = "1", features = ["v4", "v5", "serde"] } uuid = { version = "1", features = ["v4", "v5", "serde"] }
# Database # Database
sqlx = { version = "0.7", features = ["runtime-tokio", "sqlite", "postgres", "chrono"] } sqlx = { version = "0.8", features = ["runtime-tokio", "sqlite", "postgres", "chrono"] }
libsqlite3-sys = { version = "0.27", features = ["bundled"] } libsqlite3-sys = { version = "0.30", features = ["bundled"] }
# HTTP client (for LLM drivers) # HTTP client (for LLM drivers)
reqwest = { version = "0.12", default-features = false, features = ["json", "stream", "rustls-tls"] } reqwest = { version = "0.12", default-features = false, features = ["json", "stream", "rustls-tls"] }
# Synchronous HTTP (for WASM host functions in blocking threads)
ureq = { version = "3", features = ["rustls"] }
# URL parsing # URL parsing
url = "2" url = "2"
@@ -103,7 +106,7 @@ wasmtime-wasi = { version = "43" }
tempfile = "3" tempfile = "3"
# SaaS dependencies # SaaS dependencies
axum = { version = "0.7", features = ["macros"] } axum = { version = "0.7", features = ["macros", "multipart"] }
axum-extra = { version = "0.9", features = ["typed-header", "cookie"] } axum-extra = { version = "0.9", features = ["typed-header", "cookie"] }
tower = { version = "0.4", features = ["util"] } tower = { version = "0.4", features = ["util"] }
tower-http = { version = "0.5", features = ["cors", "trace", "limit", "timeout"] } tower-http = { version = "0.5", features = ["cors", "trace", "limit", "timeout"] }
@@ -112,6 +115,12 @@ argon2 = "0.5"
totp-rs = "5" totp-rs = "5"
hex = "0.4" hex = "0.4"
# Document processing
pdf-extract = "0.7"
calamine = "0.26"
quick-xml = "0.37"
zip = "2"
# TCP socket configuration # TCP socket configuration
socket2 = { version = "0.5", features = ["all"] } socket2 = { version = "0.5", features = ["all"] }

View File

@@ -21,6 +21,7 @@ import {
SafetyOutlined, SafetyOutlined,
FieldTimeOutlined, FieldTimeOutlined,
SyncOutlined, SyncOutlined,
ShopOutlined,
} from '@ant-design/icons' } from '@ant-design/icons'
import { Avatar, Dropdown, Tooltip, Drawer } from 'antd' import { Avatar, Dropdown, Tooltip, Drawer } from 'antd'
import { useAuthStore } from '@/stores/authStore' import { useAuthStore } from '@/stores/authStore'
@@ -50,6 +51,7 @@ const navItems: NavItem[] = [
{ path: '/relay', name: '中转任务', icon: <SwapOutlined />, permission: 'relay:use', group: '运维' }, { path: '/relay', name: '中转任务', icon: <SwapOutlined />, permission: 'relay:use', group: '运维' },
{ path: '/scheduled-tasks', name: '定时任务', icon: <FieldTimeOutlined />, permission: 'scheduler:read', group: '运维' }, { path: '/scheduled-tasks', name: '定时任务', icon: <FieldTimeOutlined />, permission: 'scheduler:read', group: '运维' },
{ path: '/knowledge', name: '知识库', icon: <BookOutlined />, permission: 'knowledge:read', group: '资源管理' }, { path: '/knowledge', name: '知识库', icon: <BookOutlined />, permission: 'knowledge:read', group: '资源管理' },
{ path: '/industries', name: '行业配置', icon: <ShopOutlined />, permission: 'config:read', group: '资源管理' },
{ path: '/billing', name: '计费管理', icon: <CrownOutlined />, permission: 'billing:read', group: '核心' }, { path: '/billing', name: '计费管理', icon: <CrownOutlined />, permission: 'billing:read', group: '核心' },
{ path: '/logs', name: '操作日志', icon: <FileTextOutlined />, permission: 'admin:full', group: '运维' }, { path: '/logs', name: '操作日志', icon: <FileTextOutlined />, permission: 'admin:full', group: '运维' },
{ path: '/config-sync', name: '同步日志', icon: <SyncOutlined />, permission: 'config:read', group: '运维' }, { path: '/config-sync', name: '同步日志', icon: <SyncOutlined />, permission: 'config:read', group: '运维' },
@@ -115,7 +117,7 @@ function Sidebar({
const isActive = const isActive =
item.path === '/' item.path === '/'
? activePath === '/' ? activePath === '/'
: activePath.startsWith(item.path) : activePath === item.path || activePath.startsWith(item.path + '/')
const btn = ( const btn = (
<button <button
@@ -219,6 +221,7 @@ const breadcrumbMap: Record<string, string> = {
'/knowledge': '知识库', '/knowledge': '知识库',
'/billing': '计费管理', '/billing': '计费管理',
'/config': '系统配置', '/config': '系统配置',
'/industries': '行业配置',
'/prompts': '提示词管理', '/prompts': '提示词管理',
'/logs': '操作日志', '/logs': '操作日志',
'/config-sync': '同步日志', '/config-sync': '同步日志',

View File

@@ -2,12 +2,14 @@
// 账号管理 // 账号管理
// ============================================================ // ============================================================
import { useState } from 'react' import { useState, useEffect } from 'react'
import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query' import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query'
import { Button, message, Tag, Modal, Form, Input, Select, Popconfirm, Space } from 'antd' import { Button, message, Tag, Modal, Form, Input, Select, Popconfirm, Space, Divider } from 'antd'
import type { ProColumns } from '@ant-design/pro-components' import type { ProColumns } from '@ant-design/pro-components'
import { ProTable } from '@ant-design/pro-components' import { ProTable } from '@ant-design/pro-components'
import { accountService } from '@/services/accounts' import { accountService } from '@/services/accounts'
import { industryService } from '@/services/industries'
import { billingService } from '@/services/billing'
import { PageHeader } from '@/components/PageHeader' import { PageHeader } from '@/components/PageHeader'
import type { AccountPublic } from '@/types' import type { AccountPublic } from '@/types'
@@ -47,13 +49,39 @@ export default function Accounts() {
queryFn: ({ signal }) => accountService.list(searchParams, signal), queryFn: ({ signal }) => accountService.list(searchParams, signal),
}) })
// 获取行业列表(用于下拉选择)
const { data: industriesData } = useQuery({
queryKey: ['industries-all'],
queryFn: ({ signal }) => industryService.list({ page: 1, page_size: 100, status: 'active' }, signal),
})
// 获取当前编辑用户的行业授权
const { data: accountIndustries } = useQuery({
queryKey: ['account-industries', editingId],
queryFn: ({ signal }) => industryService.getAccountIndustries(editingId!, signal),
enabled: !!editingId,
})
// 当账户行业数据加载完且正在编辑时,同步到表单
// Guard: only sync when editingId matches the query key
useEffect(() => {
if (accountIndustries && editingId) {
const ids = accountIndustries.map((item) => item.industry_id)
form.setFieldValue('industry_ids', ids)
}
}, [accountIndustries, editingId, form])
// 获取所有活跃计划(用于管理员切换)
const { data: plansData } = useQuery({
queryKey: ['billing-plans'],
queryFn: ({ signal }) => billingService.listPlans(signal),
})
const updateMutation = useMutation({ const updateMutation = useMutation({
mutationFn: ({ id, data }: { id: string; data: Partial<AccountPublic> }) => mutationFn: ({ id, data }: { id: string; data: Partial<AccountPublic> }) =>
accountService.update(id, data), accountService.update(id, data),
onSuccess: () => { onSuccess: () => {
message.success('更新成功')
queryClient.invalidateQueries({ queryKey: ['accounts'] }) queryClient.invalidateQueries({ queryKey: ['accounts'] })
setModalOpen(false)
}, },
onError: (err: Error) => message.error(err.message || '更新失败'), onError: (err: Error) => message.error(err.message || '更新失败'),
}) })
@@ -68,6 +96,26 @@ export default function Accounts() {
onError: (err: Error) => message.error(err.message || '状态更新失败'), onError: (err: Error) => message.error(err.message || '状态更新失败'),
}) })
// 设置用户行业授权
const setIndustriesMutation = useMutation({
mutationFn: ({ accountId, industries }: { accountId: string; industries: string[] }) =>
industryService.setAccountIndustries(accountId, {
industries: industries.map((id, idx) => ({
industry_id: id,
is_primary: idx === 0,
})),
}),
onError: (err: Error) => message.error(err.message || '行业授权更新失败'),
})
// 管理员切换用户计划
const switchPlanMutation = useMutation({
mutationFn: ({ accountId, planId }: { accountId: string; planId: string }) =>
billingService.adminSwitchPlan(accountId, planId),
onSuccess: () => message.success('计划切换成功'),
onError: (err: Error) => message.error(err.message || '计划切换失败'),
})
const columns: ProColumns<AccountPublic>[] = [ const columns: ProColumns<AccountPublic>[] = [
{ title: '用户名', dataIndex: 'username', width: 120, tooltip: '搜索用户名、邮箱或显示名' }, { title: '用户名', dataIndex: 'username', width: 120, tooltip: '搜索用户名、邮箱或显示名' },
{ title: '显示名', dataIndex: 'display_name', width: 120, hideInSearch: true }, { title: '显示名', dataIndex: 'display_name', width: 120, hideInSearch: true },
@@ -149,14 +197,55 @@ export default function Accounts() {
const handleSave = async () => { const handleSave = async () => {
const values = await form.validateFields() const values = await form.validateFields()
if (editingId) { if (!editingId) return
updateMutation.mutate({ id: editingId, data: values })
try {
// 更新基础信息
const { industry_ids, plan_id, ...accountData } = values
await updateMutation.mutateAsync({ id: editingId, data: accountData })
// 更新行业授权(如果变更了)
const newIndustryIds: string[] = industry_ids || []
const oldIndustryIds = accountIndustries?.map((i) => i.industry_id) || []
const changed = newIndustryIds.length !== oldIndustryIds.length
|| newIndustryIds.some((id) => !oldIndustryIds.includes(id))
if (changed) {
await setIndustriesMutation.mutateAsync({ accountId: editingId, industries: newIndustryIds })
message.success('行业授权已更新')
queryClient.invalidateQueries({ queryKey: ['account-industries'] })
}
// 切换订阅计划(如果选择了新计划)
if (plan_id) {
await switchPlanMutation.mutateAsync({ accountId: editingId, planId: plan_id })
}
handleClose()
} catch {
// Errors handled by mutation onError callbacks
} }
} }
const handleClose = () => {
setModalOpen(false)
setEditingId(null)
form.resetFields()
}
const industryOptions = (industriesData?.items || []).map((item) => ({
value: item.id,
label: `${item.icon} ${item.name}`,
}))
const planOptions = (plansData || []).map((plan) => ({
value: plan.id,
label: `${plan.display_name}${(plan.price_cents / 100).toFixed(0)}/月)`,
}))
return ( return (
<div> <div>
<PageHeader title="账号管理" description="管理系统用户账号、角色与权限" /> <PageHeader title="账号管理" description="管理系统用户账号、角色、权限与行业授权" />
<ProTable<AccountPublic> <ProTable<AccountPublic>
columns={columns} columns={columns}
@@ -169,7 +258,6 @@ export default function Accounts() {
const filtered: Record<string, string> = {} const filtered: Record<string, string> = {}
for (const [k, v] of Object.entries(values)) { for (const [k, v] of Object.entries(values)) {
if (v !== undefined && v !== null && v !== '') { if (v !== undefined && v !== null && v !== '') {
// Map 'username' search field to backend 'search' param
if (k === 'username') { if (k === 'username') {
filtered.search = String(v) filtered.search = String(v)
} else { } else {
@@ -192,8 +280,9 @@ export default function Accounts() {
title={<span className="text-base font-semibold"></span>} title={<span className="text-base font-semibold"></span>}
open={modalOpen} open={modalOpen}
onOk={handleSave} onOk={handleSave}
onCancel={() => { setModalOpen(false); setEditingId(null); form.resetFields() }} onCancel={handleClose}
confirmLoading={updateMutation.isPending} confirmLoading={updateMutation.isPending || setIndustriesMutation.isPending || switchPlanMutation.isPending}
width={560}
> >
<Form form={form} layout="vertical" className="mt-4"> <Form form={form} layout="vertical" className="mt-4">
<Form.Item name="display_name" label="显示名"> <Form.Item name="display_name" label="显示名">
@@ -215,6 +304,36 @@ export default function Accounts() {
{ value: 'relay', label: 'SaaS 中转 (Token 池)' }, { value: 'relay', label: 'SaaS 中转 (Token 池)' },
]} /> ]} />
</Form.Item> </Form.Item>
<Divider></Divider>
<Form.Item
name="plan_id"
label="切换计划"
extra="选择新计划后保存将立即切换。留空则不修改当前计划。"
>
<Select
allowClear
placeholder="不修改当前计划"
options={planOptions}
loading={!plansData}
/>
</Form.Item>
<Divider></Divider>
<Form.Item
name="industry_ids"
label="授权行业"
extra="第一个行业将设为主行业。行业决定管家可触达的知识域和技能优先级。"
>
<Select
mode="multiple"
placeholder="选择授权的行业"
options={industryOptions}
loading={!industriesData}
/>
</Form.Item>
</Form> </Form>
</Modal> </Modal>
</div> </div>

View File

@@ -0,0 +1,169 @@
import { useState } from 'react'
import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query'
import { Button, message, Tag, Modal, Form, Input, InputNumber, Select, Space, Popconfirm, Typography } from 'antd'
import { PlusOutlined, CopyOutlined } from '@ant-design/icons'
import { ProTable } from '@ant-design/pro-components'
import type { ProColumns } from '@ant-design/pro-components'
import { apiKeyService } from '@/services/api-keys'
import type { TokenInfo } from '@/types'
const { Text, Paragraph } = Typography
const PERMISSION_OPTIONS = [
{ label: 'Relay Chat', value: 'relay:use' },
{ label: 'Knowledge Read', value: 'knowledge:read' },
{ label: 'Knowledge Write', value: 'knowledge:write' },
{ label: 'Agent Read', value: 'agent:read' },
{ label: 'Agent Write', value: 'agent:write' },
]
export default function ApiKeys() {
const queryClient = useQueryClient()
const [form] = Form.useForm()
const [createOpen, setCreateOpen] = useState(false)
const [newToken, setNewToken] = useState<string | null>(null)
const [page, setPage] = useState(1)
const [pageSize, setPageSize] = useState(20)
const { data, isLoading } = useQuery({
queryKey: ['api-keys', page, pageSize],
queryFn: ({ signal }) => apiKeyService.list({ page, page_size: pageSize }, signal),
})
const createMutation = useMutation({
mutationFn: (values: { name: string; expires_days?: number; permissions: string[] }) =>
apiKeyService.create(values),
onSuccess: (result: TokenInfo) => {
message.success('API 密钥创建成功')
if (result.token) {
setNewToken(result.token)
}
queryClient.invalidateQueries({ queryKey: ['api-keys'] })
form.resetFields()
},
onError: (err: Error) => message.error(err.message || '创建失败'),
})
const revokeMutation = useMutation({
mutationFn: (id: string) => apiKeyService.revoke(id),
onSuccess: () => {
message.success('密钥已吊销')
queryClient.invalidateQueries({ queryKey: ['api-keys'] })
},
onError: (err: Error) => message.error(err.message || '吊销失败'),
})
const handleCreate = async () => {
const values = await form.validateFields()
createMutation.mutate(values)
}
const columns: ProColumns<TokenInfo>[] = [
{ title: '名称', dataIndex: 'name', width: 180 },
{
title: '前缀',
dataIndex: 'token_prefix',
width: 120,
render: (val: string) => <Text code>{val}...</Text>,
},
{
title: '权限',
dataIndex: 'permissions',
width: 240,
render: (perms: string[]) =>
perms?.map((p) => <Tag key={p}>{p}</Tag>) || '-',
},
{
title: '最后使用',
dataIndex: 'last_used_at',
width: 180,
render: (val: string) => (val ? new Date(val).toLocaleString() : <Text type="secondary">使</Text>),
},
{
title: '过期时间',
dataIndex: 'expires_at',
width: 180,
render: (val: string) =>
val ? new Date(val).toLocaleString() : <Text type="secondary"></Text>,
},
{
title: '创建时间',
dataIndex: 'created_at',
width: 180,
render: (val: string) => new Date(val).toLocaleString(),
},
{
title: '操作',
width: 100,
render: (_: unknown, record: TokenInfo) => (
<Popconfirm
title="确定吊销此密钥?"
description="吊销后使用该密钥的所有请求将被拒绝"
onConfirm={() => revokeMutation.mutate(record.id)}
>
<Button danger size="small"></Button>
</Popconfirm>
),
},
]
return (
<div style={{ padding: 24 }}>
<ProTable<TokenInfo>
columns={columns}
dataSource={data?.items || []}
loading={isLoading}
rowKey="id"
search={false}
pagination={{
current: page,
pageSize,
total: data?.total || 0,
onChange: (p, ps) => { setPage(p); setPageSize(ps) },
}}
toolBarRender={() => [
<Button key="create" type="primary" icon={<PlusOutlined />} onClick={() => setCreateOpen(true)}>
</Button>,
]}
/>
<Modal
title="创建 API 密钥"
open={createOpen}
onOk={handleCreate}
onCancel={() => { setCreateOpen(false); setNewToken(null); form.resetFields() }}
confirmLoading={createMutation.isPending}
destroyOnHidden
>
{newToken ? (
<div style={{ marginBottom: 16 }}>
<Paragraph type="warning">
</Paragraph>
<Space>
<Text code style={{ fontSize: 13 }}>{newToken}</Text>
<Button
icon={<CopyOutlined />}
size="small"
onClick={() => { navigator.clipboard.writeText(newToken); message.success('已复制') }}
/>
</Space>
</div>
) : (
<Form form={form} layout="vertical">
<Form.Item name="name" label="密钥名称" rules={[{ required: true, message: '请输入名称' }]}>
<Input placeholder="例如: 生产环境 API Key" />
</Form.Item>
<Form.Item name="expires_days" label="有效期 (天)">
<InputNumber min={1} max={3650} placeholder="留空表示永不过期" style={{ width: '100%' }} />
</Form.Item>
<Form.Item name="permissions" label="权限" rules={[{ required: true, message: '请选择至少一项权限' }]}>
<Select mode="multiple" options={PERMISSION_OPTIONS} placeholder="选择权限" />
</Form.Item>
</Form>
)}
</Modal>
</div>
)
}

View File

@@ -0,0 +1,379 @@
// ============================================================
// 行业配置管理
// ============================================================
import { useState, useEffect } from 'react'
import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query'
import {
Button, message, Tag, Modal, Form, Input, Select, Space, Popconfirm,
Tabs, Typography, Spin, Empty,
} from 'antd'
import {
PlusOutlined, EditOutlined, CheckCircleOutlined, StopOutlined,
ShopOutlined, SettingOutlined,
} from '@ant-design/icons'
import type { ProColumns } from '@ant-design/pro-components'
import { ProTable } from '@ant-design/pro-components'
import { industryService } from '@/services/industries'
import type { IndustryListItem, IndustryFullConfig, UpdateIndustryRequest } from '@/services/industries'
import { PageHeader } from '@/components/PageHeader'
const { TextArea } = Input
const { Text } = Typography
const statusLabels: Record<string, string> = { active: '启用', inactive: '禁用' }
const statusColors: Record<string, string> = { active: 'green', inactive: 'default' }
const sourceLabels: Record<string, string> = { builtin: '内置', admin: '自定义', custom: '自定义' }
// === 行业列表 ===
function IndustryListPanel() {
const queryClient = useQueryClient()
const [page, setPage] = useState(1)
const [pageSize, setPageSize] = useState(20)
const [filters, setFilters] = useState<{ status?: string; source?: string }>({})
const [editId, setEditId] = useState<string | null>(null)
const [createOpen, setCreateOpen] = useState(false)
const { data, isLoading } = useQuery({
queryKey: ['industries', page, pageSize, filters],
queryFn: ({ signal }) => industryService.list({ page, page_size: pageSize, ...filters }, signal),
})
const updateStatusMutation = useMutation({
mutationFn: ({ id, status }: { id: string; status: string }) =>
industryService.update(id, { status }),
onSuccess: () => {
message.success('状态已更新')
queryClient.invalidateQueries({ queryKey: ['industries'] })
},
onError: (err: Error) => message.error(err.message || '更新失败'),
})
const columns: ProColumns<IndustryListItem>[] = [
{
title: '图标',
dataIndex: 'icon',
width: 50,
search: false,
render: (_, r) => <span className="text-xl">{r.icon}</span>,
},
{
title: '行业名称',
dataIndex: 'name',
width: 150,
},
{
title: '描述',
dataIndex: 'description',
width: 250,
search: false,
ellipsis: true,
},
{
title: '来源',
dataIndex: 'source',
width: 80,
valueType: 'select',
valueEnum: {
builtin: { text: '内置' },
admin: { text: '自定义' },
custom: { text: '自定义' },
},
render: (_, r) => <Tag color={r.source === 'builtin' ? 'blue' : 'purple'}>{sourceLabels[r.source] || r.source}</Tag>,
},
{
title: '关键词数',
dataIndex: 'keywords_count',
width: 90,
search: false,
render: (_, r) => <Tag>{r.keywords_count}</Tag>,
},
{
title: '状态',
dataIndex: 'status',
width: 80,
valueType: 'select',
valueEnum: {
active: { text: '启用', status: 'Success' },
inactive: { text: '禁用', status: 'Default' },
},
render: (_, r) => <Tag color={statusColors[r.status]}>{statusLabels[r.status] || r.status}</Tag>,
},
{
title: '更新时间',
dataIndex: 'updated_at',
width: 160,
valueType: 'dateTime',
search: false,
},
{
title: '操作',
width: 180,
search: false,
render: (_, r) => (
<Space>
<Button
type="link"
size="small"
icon={<EditOutlined />}
onClick={() => setEditId(r.id)}
>
</Button>
{r.status === 'active' ? (
<Popconfirm title="确定禁用此行业?" onConfirm={() => updateStatusMutation.mutate({ id: r.id, status: 'inactive' })}>
<Button type="link" size="small" danger icon={<StopOutlined />}></Button>
</Popconfirm>
) : (
<Popconfirm title="确定启用此行业?" onConfirm={() => updateStatusMutation.mutate({ id: r.id, status: 'active' })}>
<Button type="link" size="small" icon={<CheckCircleOutlined />}></Button>
</Popconfirm>
)}
</Space>
),
},
]
return (
<div>
<ProTable<IndustryListItem>
columns={columns}
dataSource={data?.items || []}
loading={isLoading}
rowKey="id"
search={{
onReset: () => { setFilters({}); setPage(1) },
onSubmit: (values) => { setFilters(values); setPage(1) },
}}
toolBarRender={() => [
<Button key="create" type="primary" icon={<PlusOutlined />} onClick={() => setCreateOpen(true)}>
</Button>,
]}
pagination={{
current: page,
pageSize,
total: data?.total || 0,
showSizeChanger: true,
onChange: (p, ps) => { setPage(p); setPageSize(ps) },
}}
options={{ density: false, fullScreen: false, reload: () => queryClient.invalidateQueries({ queryKey: ['industries'] }) }}
/>
<IndustryEditModal
open={!!editId}
industryId={editId}
onClose={() => setEditId(null)}
/>
<IndustryCreateModal
open={createOpen}
onClose={() => setCreateOpen(false)}
/>
</div>
)
}
// === 行业编辑弹窗 ===
function IndustryEditModal({ open, industryId, onClose }: {
open: boolean
industryId: string | null
onClose: () => void
}) {
const queryClient = useQueryClient()
const [form] = Form.useForm()
const { data, isLoading } = useQuery({
queryKey: ['industry-full-config', industryId],
queryFn: ({ signal }) => industryService.getFullConfig(industryId!, signal),
enabled: !!industryId,
})
useEffect(() => {
if (data && open && data.id === industryId) {
form.setFieldsValue({
name: data.name,
icon: data.icon,
description: data.description,
keywords: data.keywords,
system_prompt: data.system_prompt,
cold_start_template: data.cold_start_template,
pain_seed_categories: data.pain_seed_categories,
})
}
}, [data, open, industryId, form])
const updateMutation = useMutation({
mutationFn: (body: UpdateIndustryRequest) =>
industryService.update(industryId!, body),
onSuccess: () => {
message.success('行业配置已更新')
queryClient.invalidateQueries({ queryKey: ['industries'] })
queryClient.invalidateQueries({ queryKey: ['industry-full-config'] })
onClose()
},
onError: (err: Error) => message.error(err.message || '更新失败'),
})
return (
<Modal
title={<span className="text-base font-semibold"> {data?.name || ''}</span>}
open={open}
onCancel={() => { onClose(); form.resetFields() }}
onOk={() => form.submit()}
confirmLoading={updateMutation.isPending}
width={720}
destroyOnHidden
>
{isLoading ? (
<div className="flex justify-center py-8"><Spin /></div>
) : data ? (
<Form
form={form}
layout="vertical"
className="mt-4"
onFinish={(values) => updateMutation.mutate(values)}
>
<Form.Item name="name" label="行业名称" rules={[{ required: true, message: '请输入行业名称' }]}>
<Input />
</Form.Item>
<Form.Item name="icon" label="图标">
<Input placeholder="行业图标 emoji如 🏥" className="w-32" />
</Form.Item>
<Form.Item name="description" label="描述">
<TextArea rows={2} placeholder="行业简要描述" />
</Form.Item>
<Form.Item name="keywords" label="关键词列表" extra="用于语义路由匹配,回车添加">
<Select mode="tags" placeholder="输入关键词后回车添加" />
</Form.Item>
<Form.Item name="system_prompt" label="系统提示词" extra="匹配到此行业时注入的 system prompt">
<TextArea rows={6} placeholder="行业专属系统提示词模板" />
</Form.Item>
<Form.Item name="cold_start_template" label="冷启动模板" extra="首次匹配时的引导消息模板">
<TextArea rows={3} placeholder="冷启动引导消息" />
</Form.Item>
<Form.Item name="pain_seed_categories" label="痛点种子分类" extra="预置的痛点分类维度">
<Select mode="tags" placeholder="输入痛点分类后回车添加" />
</Form.Item>
<div className="mb-2">
<Text type="secondary">
: <Tag color={data.source === 'builtin' ? 'blue' : 'purple'}>{sourceLabels[data.source]}</Tag>
{' '}: <Tag color={statusColors[data.status]}>{statusLabels[data.status]}</Tag>
</Text>
</div>
</Form>
) : (
<Empty description="未找到行业配置" />
)}
</Modal>
)
}
// === 新建行业弹窗 ===
function IndustryCreateModal({ open, onClose }: {
open: boolean
onClose: () => void
}) {
const queryClient = useQueryClient()
const [form] = Form.useForm()
const createMutation = useMutation({
mutationFn: (data: Parameters<typeof industryService.create>[0]) =>
industryService.create(data),
onSuccess: () => {
message.success('行业已创建')
queryClient.invalidateQueries({ queryKey: ['industries'] })
onClose()
form.resetFields()
},
onError: (err: Error) => message.error(err.message || '创建失败'),
})
return (
<Modal
title="新建行业"
open={open}
onCancel={() => { onClose(); form.resetFields() }}
onOk={() => form.submit()}
confirmLoading={createMutation.isPending}
width={640}
destroyOnHidden
>
<Form
form={form}
layout="vertical"
className="mt-4"
initialValues={{ icon: '🏢' }}
onFinish={(values) => {
// Auto-generate id from name if not provided
if (!values.id && values.name) {
// Strip non-ASCII, keep only lowercase alphanumeric + hyphens
const generated = values.name.toLowerCase()
.replace(/[^a-z0-9]+/g, '-')
.replace(/^-|-$/g, '')
if (generated) {
values.id = generated
} else {
// Name has no ASCII chars — require manual ID entry
message.warning('中文行业名称无法自动生成标识,请手动填写行业标识')
return
}
}
createMutation.mutate(values)
}}
>
<Form.Item name="name" label="行业名称" rules={[{ required: true, message: '请输入行业名称' }]}>
<Input placeholder="如:医疗健康、教育培训" />
</Form.Item>
<Form.Item name="id" label="行业标识" extra="唯一标识,留空则从名称自动生成。仅限小写字母、数字、连字符" rules={[
{ pattern: /^[a-z0-9-]*$/, message: '仅限小写字母、数字、连字符' },
{ max: 63, message: '最长 63 字符' },
]}>
<Input placeholder="如healthcare、education" />
</Form.Item>
<Form.Item name="icon" label="图标">
<Input placeholder="行业图标 emoji" className="w-32" />
</Form.Item>
<Form.Item name="description" label="描述" rules={[{ required: true, message: '请输入行业描述' }]}>
<TextArea rows={2} placeholder="行业简要描述" />
</Form.Item>
<Form.Item name="keywords" label="关键词列表" extra="用于语义路由匹配,回车添加">
<Select mode="tags" placeholder="输入关键词后回车添加" />
</Form.Item>
<Form.Item name="system_prompt" label="系统提示词">
<TextArea rows={4} placeholder="行业专属系统提示词" />
</Form.Item>
<Form.Item name="cold_start_template" label="冷启动模板" extra="新用户首次对话时使用的引导模板">
<TextArea rows={3} placeholder="如:您好!我是您的{行业}管家,可以帮您处理..." />
</Form.Item>
<Form.Item name="pain_seed_categories" label="痛点种子类别" extra="预置的痛点分类,用逗号或回车分隔">
<Select mode="tags" placeholder="如:库存管理、客户服务、合规" />
</Form.Item>
</Form>
</Modal>
)
}
// === 主页面 ===
export default function Industries() {
return (
<div>
<PageHeader title="行业配置" description="管理行业关键词、系统提示词、痛点种子,驱动管家语义路由" />
<Tabs
defaultActiveKey="list"
items={[
{
key: 'list',
label: '行业列表',
icon: <ShopOutlined />,
children: <IndustryListPanel />,
},
]}
/>
</div>
)
}

View File

@@ -19,6 +19,8 @@ import type { ProColumns } from '@ant-design/pro-components'
import { ProTable } from '@ant-design/pro-components' import { ProTable } from '@ant-design/pro-components'
import { knowledgeService } from '@/services/knowledge' import { knowledgeService } from '@/services/knowledge'
import type { CategoryResponse, KnowledgeItem, SearchResult } from '@/services/knowledge' import type { CategoryResponse, KnowledgeItem, SearchResult } from '@/services/knowledge'
import type { StructuredSource } from '@/services/knowledge'
import { TableOutlined } from '@ant-design/icons'
const { TextArea } = Input const { TextArea } = Input
const { Text, Title } = Typography const { Text, Title } = Typography
@@ -331,7 +333,7 @@ function ItemsPanel() {
rowKey="id" rowKey="id"
search={{ search={{
onReset: () => { setFilters({}); setPage(1) }, onReset: () => { setFilters({}); setPage(1) },
onSearch: (values) => { setFilters(values); setPage(1) }, onSubmit: (values) => { setFilters(values); setPage(1) },
}} }}
toolBarRender={() => [ toolBarRender={() => [
<Button key="create" type="primary" icon={<PlusOutlined />} onClick={() => setCreateOpen(true)}> <Button key="create" type="primary" icon={<PlusOutlined />} onClick={() => setCreateOpen(true)}>
@@ -708,12 +710,138 @@ export default function Knowledge() {
icon: <BarChartOutlined />, icon: <BarChartOutlined />,
children: <AnalyticsPanel />, children: <AnalyticsPanel />,
}, },
{
key: 'structured',
label: '结构化数据',
icon: <TableOutlined />,
children: <StructuredSourcesPanel />,
},
]} ]}
/> />
</div> </div>
) )
} }
// === Structured Data Sources Panel ===
function StructuredSourcesPanel() {
const queryClient = useQueryClient()
const [viewingRows, setViewingRows] = useState<string | null>(null)
const { data: sources = [], isLoading } = useQuery({
queryKey: ['structured-sources'],
queryFn: ({ signal }) => knowledgeService.listStructuredSources(signal),
})
const { data: rows = [], isLoading: rowsLoading } = useQuery({
queryKey: ['structured-rows', viewingRows],
queryFn: ({ signal }) => knowledgeService.listStructuredRows(viewingRows!, signal),
enabled: !!viewingRows,
})
const deleteMutation = useMutation({
mutationFn: (id: string) => knowledgeService.deleteStructuredSource(id),
onSuccess: () => {
message.success('数据源已删除')
queryClient.invalidateQueries({ queryKey: ['structured-sources'] })
},
onError: (err: Error) => message.error(err.message || '删除失败'),
})
const columns: ProColumns<StructuredSource>[] = [
{ title: '名称', dataIndex: 'name', key: 'name', width: 200 },
{ title: '类型', dataIndex: 'source_type', key: 'source_type', width: 120, render: (v: string) => <Tag>{v}</Tag> },
{ title: '行数', dataIndex: 'row_count', key: 'row_count', width: 80 },
{
title: '列',
dataIndex: 'columns',
key: 'columns',
width: 250,
render: (cols: string[]) => (
<Space size={[4, 4]} wrap>
{(cols ?? []).slice(0, 5).map((c) => (
<Tag key={c} color="blue">{c}</Tag>
))}
{(cols ?? []).length > 5 && <Tag>+{(cols as string[]).length - 5}</Tag>}
</Space>
),
},
{
title: '创建时间',
dataIndex: 'created_at',
key: 'created_at',
width: 160,
render: (v: string) => new Date(v).toLocaleString('zh-CN'),
},
{
title: '操作',
key: 'actions',
width: 140,
render: (_: unknown, record: StructuredSource) => (
<Space>
<Button type="link" size="small" onClick={() => setViewingRows(record.id)}>
</Button>
<Popconfirm title="确认删除此数据源?" onConfirm={() => deleteMutation.mutate(record.id)}>
<Button type="link" size="small" danger>
</Button>
</Popconfirm>
</Space>
),
},
]
// Dynamically generate row columns from the first row's keys
const rowColumns = rows.length > 0
? Object.keys(rows[0].row_data).map((key) => ({
title: key,
dataIndex: ['row_data', key],
key,
ellipsis: true,
render: (v: unknown) => String(v ?? ''),
}))
: []
return (
<div className="space-y-4">
{viewingRows ? (
<Card
title="数据行"
extra={<Button onClick={() => setViewingRows(null)}></Button>}
>
{rowsLoading ? (
<Spin />
) : rows.length === 0 ? (
<Empty description="暂无数据" />
) : (
<Table
dataSource={rows}
columns={rowColumns}
rowKey="id"
size="small"
scroll={{ x: true }}
pagination={{ pageSize: 20 }}
/>
)}
</Card>
) : (
<ProTable<StructuredSource>
dataSource={sources}
columns={columns}
loading={isLoading}
rowKey="id"
search={false}
pagination={{ pageSize: 20 }}
toolBarRender={false}
/>
)}
</div>
)
}
// === 辅助函数 ===
// === 辅助函数 === // === 辅助函数 ===
function flattenCategories(cats: CategoryResponse[]): { id: string; name: string }[] { function flattenCategories(cats: CategoryResponse[]): { id: string; name: string }[] {

View File

@@ -67,6 +67,7 @@ function ProviderModelsTable({ providerId }: { providerId: string }) {
const columns: ProColumns<Model>[] = [ const columns: ProColumns<Model>[] = [
{ title: '模型 ID', dataIndex: 'model_id', width: 180, render: (_, r) => <Text code>{r.model_id}</Text> }, { title: '模型 ID', dataIndex: 'model_id', width: 180, render: (_, r) => <Text code>{r.model_id}</Text> },
{ title: '别名', dataIndex: 'alias', width: 120 }, { title: '别名', dataIndex: 'alias', width: 120 },
{ title: '类型', dataIndex: 'is_embedding', width: 80, render: (_, r) => r.is_embedding ? <Tag color="purple">Embedding</Tag> : <Tag>Chat</Tag> },
{ title: '上下文窗口', dataIndex: 'context_window', width: 100, render: (_, r) => r.context_window?.toLocaleString() }, { title: '上下文窗口', dataIndex: 'context_window', width: 100, render: (_, r) => r.context_window?.toLocaleString() },
{ title: '最大输出', dataIndex: 'max_output_tokens', width: 90, render: (_, r) => r.max_output_tokens?.toLocaleString() }, { title: '最大输出', dataIndex: 'max_output_tokens', width: 90, render: (_, r) => r.max_output_tokens?.toLocaleString() },
{ title: '流式', dataIndex: 'supports_streaming', width: 60, render: (_, r) => r.supports_streaming ? <Tag color="green"></Tag> : <Tag></Tag> }, { title: '流式', dataIndex: 'supports_streaming', width: 60, render: (_, r) => r.supports_streaming ? <Tag color="green"></Tag> : <Tag></Tag> },
@@ -128,6 +129,9 @@ function ProviderModelsTable({ providerId }: { providerId: string }) {
<Form.Item name="enabled" label="启用" valuePropName="checked" style={{ flex: 1 }}> <Form.Item name="enabled" label="启用" valuePropName="checked" style={{ flex: 1 }}>
<Switch /> <Switch />
</Form.Item> </Form.Item>
<Form.Item name="is_embedding" label="Embedding 模型" valuePropName="checked" style={{ flex: 1 }}>
<Switch />
</Form.Item>
<Form.Item name="supports_streaming" label="支持流式" valuePropName="checked" style={{ flex: 1 }}> <Form.Item name="supports_streaming" label="支持流式" valuePropName="checked" style={{ flex: 1 }}>
<Switch defaultChecked /> <Switch defaultChecked />
</Form.Item> </Form.Item>

View File

@@ -327,7 +327,7 @@ export default function ScheduledTasks() {
onCancel={closeModal} onCancel={closeModal}
confirmLoading={createMutation.isPending || updateMutation.isPending} confirmLoading={createMutation.isPending || updateMutation.isPending}
width={520} width={520}
destroyOnClose destroyOnHidden
> >
<Form form={form} layout="vertical" className="mt-4"> <Form form={form} layout="vertical" className="mt-4">
<Form.Item <Form.Item

View File

@@ -26,7 +26,7 @@ export const router = createBrowserRouter([
{ path: 'providers', lazy: () => import('@/pages/ModelServices').then((m) => ({ Component: m.default })) }, { path: 'providers', lazy: () => import('@/pages/ModelServices').then((m) => ({ Component: m.default })) },
{ path: 'models', lazy: () => import('@/pages/ModelServices').then((m) => ({ Component: m.default })) }, { path: 'models', lazy: () => import('@/pages/ModelServices').then((m) => ({ Component: m.default })) },
{ path: 'agent-templates', lazy: () => import('@/pages/AgentTemplates').then((m) => ({ Component: m.default })) }, { path: 'agent-templates', lazy: () => import('@/pages/AgentTemplates').then((m) => ({ Component: m.default })) },
{ path: 'api-keys', lazy: () => import('@/pages/ModelServices').then((m) => ({ Component: m.default })) }, { path: 'api-keys', lazy: () => import('@/pages/ApiKeys').then((m) => ({ Component: m.default })) },
{ path: 'usage', lazy: () => import('@/pages/Usage').then((m) => ({ Component: m.default })) }, { path: 'usage', lazy: () => import('@/pages/Usage').then((m) => ({ Component: m.default })) },
{ path: 'billing', lazy: () => import('@/pages/Billing').then((m) => ({ Component: m.default })) }, { path: 'billing', lazy: () => import('@/pages/Billing').then((m) => ({ Component: m.default })) },
{ path: 'relay', lazy: () => import('@/pages/Relay').then((m) => ({ Component: m.default })) }, { path: 'relay', lazy: () => import('@/pages/Relay').then((m) => ({ Component: m.default })) },
@@ -36,6 +36,7 @@ export const router = createBrowserRouter([
{ path: 'prompts', lazy: () => import('@/pages/Prompts').then((m) => ({ Component: m.default })) }, { path: 'prompts', lazy: () => import('@/pages/Prompts').then((m) => ({ Component: m.default })) },
{ path: 'logs', lazy: () => import('@/pages/Logs').then((m) => ({ Component: m.default })) }, { path: 'logs', lazy: () => import('@/pages/Logs').then((m) => ({ Component: m.default })) },
{ path: 'config-sync', lazy: () => import('@/pages/ConfigSync').then((m) => ({ Component: m.default })) }, { path: 'config-sync', lazy: () => import('@/pages/ConfigSync').then((m) => ({ Component: m.default })) },
{ path: 'industries', lazy: () => import('@/pages/Industries').then((m) => ({ Component: m.default })) },
], ],
}, },
]) ])

View File

@@ -1,13 +1,15 @@
import request, { withSignal } from './request' import request, { withSignal } from './request'
import type { TokenInfo, CreateTokenRequest, PaginatedResponse } from '@/types' import type { TokenInfo, CreateTokenRequest, PaginatedResponse } from '@/types'
// 使用 /tokens 路由 (api_tokens 表),前端 UI 字段 {name, expires_days, permissions} 与此后端匹配
// 注: /keys 路由 (account_api_keys 表) 需要 {provider_id, key_value},属于不同的 Key 管理系统
export const apiKeyService = { export const apiKeyService = {
list: (params?: Record<string, unknown>, signal?: AbortSignal) => list: (params?: Record<string, unknown>, signal?: AbortSignal) =>
request.get<PaginatedResponse<TokenInfo>>('/keys', withSignal({ params }, signal)).then((r) => r.data), request.get<PaginatedResponse<TokenInfo>>('/tokens', withSignal({ params }, signal)).then((r) => r.data),
create: (data: CreateTokenRequest, signal?: AbortSignal) => create: (data: CreateTokenRequest, signal?: AbortSignal) =>
request.post<TokenInfo>('/keys', data, withSignal({}, signal)).then((r) => r.data), request.post<TokenInfo>('/tokens', data, withSignal({}, signal)).then((r) => r.data),
revoke: (id: string, signal?: AbortSignal) => revoke: (id: string, signal?: AbortSignal) =>
request.delete(`/keys/${id}`, withSignal({}, signal)).then((r) => r.data), request.delete(`/tokens/${id}`, withSignal({}, signal)).then((r) => r.data),
} }

View File

@@ -90,4 +90,9 @@ export const billingService = {
getPaymentStatus: (id: string, signal?: AbortSignal) => getPaymentStatus: (id: string, signal?: AbortSignal) =>
request.get<PaymentStatus>(`/billing/payments/${id}`, withSignal({}, signal)) request.get<PaymentStatus>(`/billing/payments/${id}`, withSignal({}, signal))
.then((r) => r.data), .then((r) => r.data),
/** 管理员切换用户订阅计划 (super_admin only) */
adminSwitchPlan: (accountId: string, planId: string) =>
request.put<{ success: boolean; subscription: Subscription }>(`/admin/accounts/${accountId}/subscription`, { plan_id: planId })
.then((r) => r.data),
} }

View File

@@ -0,0 +1,105 @@
// ============================================================
// 行业配置 API 服务层
// ============================================================
import request, { withSignal } from './request'
import type { PaginatedResponse } from '@/types'
import type { IndustryInfo, AccountIndustryItem } from '@/types'
/** 行业列表项(列表接口返回) */
export interface IndustryListItem {
id: string
name: string
icon: string
description: string
status: string
source: string
keywords_count: number
created_at: string
updated_at: string
}
/** 行业完整配置含关键词、prompt 等) */
export interface IndustryFullConfig {
id: string
name: string
icon: string
description: string
status: string
source: string
keywords: string[]
system_prompt: string
cold_start_template: string
pain_seed_categories: string[]
skill_priorities: Array<{ skill_id: string; priority: number }>
created_at: string
updated_at: string
}
/** 创建行业请求 */
export interface CreateIndustryRequest {
id?: string
name: string
icon: string
description: string
keywords?: string[]
system_prompt?: string
cold_start_template?: string
pain_seed_categories?: string[]
}
/** 更新行业请求 */
export interface UpdateIndustryRequest {
name?: string
icon?: string
description?: string
status?: string
keywords?: string[]
system_prompt?: string
cold_start_template?: string
pain_seed_categories?: string[]
skill_priorities?: Array<{ skill_id: string; priority: number }>
}
/** 设置用户行业请求 */
export interface SetAccountIndustriesRequest {
industries: Array<{
industry_id: string
is_primary: boolean
}>
}
export const industryService = {
/** 行业列表 */
list: (params?: { page?: number; page_size?: number; status?: string }, signal?: AbortSignal) =>
request.get<PaginatedResponse<IndustryListItem>>('/industries', withSignal({ params }, signal))
.then((r) => r.data),
/** 行业详情 */
get: (id: string, signal?: AbortSignal) =>
request.get<IndustryInfo>(`/industries/${id}`, withSignal({}, signal))
.then((r) => r.data),
/** 行业完整配置 */
getFullConfig: (id: string, signal?: AbortSignal) =>
request.get<IndustryFullConfig>(`/industries/${id}/full-config`, withSignal({}, signal))
.then((r) => r.data),
/** 创建行业 */
create: (data: CreateIndustryRequest) =>
request.post<IndustryInfo>('/industries', data).then((r) => r.data),
/** 更新行业 */
update: (id: string, data: UpdateIndustryRequest) =>
request.patch<IndustryInfo>(`/industries/${id}`, data).then((r) => r.data),
/** 获取用户授权行业 */
getAccountIndustries: (accountId: string, signal?: AbortSignal) =>
request.get<AccountIndustryItem[]>(`/accounts/${accountId}/industries`, withSignal({}, signal))
.then((r) => r.data),
/** 设置用户授权行业 */
setAccountIndustries: (accountId: string, data: SetAccountIndustriesRequest) =>
request.put<AccountIndustryItem[]>(`/accounts/${accountId}/industries`, data)
.then((r) => r.data),
}

View File

@@ -62,6 +62,33 @@ export interface ListItemsResponse {
page_size: number page_size: number
} }
// === Structured Data Sources ===
export interface StructuredSource {
id: string
account_id: string
name: string
source_type: string
row_count: number
columns: string[]
created_at: string
updated_at: string
}
export interface StructuredRow {
id: string
source_id: string
row_data: Record<string, unknown>
created_at: string
}
export interface StructuredQueryResult {
row_id: string
source_name: string
row_data: Record<string, unknown>
score: number
}
// === Service === // === Service ===
export const knowledgeService = { export const knowledgeService = {
@@ -159,4 +186,23 @@ export const knowledgeService = {
// 导入 // 导入
importItems: (data: { category_id: string; files: Array<{ content: string; title?: string; keywords?: string[]; tags?: string[] }> }) => importItems: (data: { category_id: string; files: Array<{ content: string; title?: string; keywords?: string[]; tags?: string[] }> }) =>
request.post('/knowledge/items/import', data).then((r) => r.data), request.post('/knowledge/items/import', data).then((r) => r.data),
// === Structured Data Sources ===
listStructuredSources: (signal?: AbortSignal) =>
request.get<StructuredSource[]>('/structured/sources', withSignal({}, signal))
.then((r) => r.data),
getStructuredSource: (id: string, signal?: AbortSignal) =>
request.get<StructuredSource>(`/structured/sources/${id}`, withSignal({}, signal))
.then((r) => r.data),
deleteStructuredSource: (id: string) =>
request.delete(`/structured/sources/${id}`).then((r) => r.data),
listStructuredRows: (sourceId: string, signal?: AbortSignal) =>
request.get<StructuredRow[]>(`/structured/sources/${sourceId}/rows`, withSignal({}, signal))
.then((r) => r.data),
queryStructured: (data: { source_id?: string; query?: string; limit?: number }) =>
request.post<StructuredQueryResult[]>('/structured/query', data).then((r) => r.data),
} }

View File

@@ -3,5 +3,5 @@ import type { DashboardStats } from '@/types'
export const statsService = { export const statsService = {
dashboard: (signal?: AbortSignal) => dashboard: (signal?: AbortSignal) =>
request.get<DashboardStats>('/stats/dashboard', withSignal({}, signal)).then((r) => r.data), request.get<DashboardStats>('/admin/dashboard', withSignal({}, signal)).then((r) => r.data),
} }

View File

@@ -44,6 +44,30 @@ export interface PaginatedResponse<T> {
page_size: number page_size: number
} }
/** 行业配置 */
export interface IndustryInfo {
id: string
name: string
icon: string
description: string
status: string
source: string
keywords?: string[]
system_prompt?: string
cold_start_template?: string
pain_seed_categories?: string[]
created_at: string
updated_at: string
}
/** 用户-行业关联 */
export interface AccountIndustryItem {
industry_id: string
is_primary: boolean
industry_name: string
industry_icon: string
}
/** 服务商 (Provider) */ /** 服务商 (Provider) */
export interface Provider { export interface Provider {
id: string id: string
@@ -70,6 +94,8 @@ export interface Model {
supports_streaming: boolean supports_streaming: boolean
supports_vision: boolean supports_vision: boolean
enabled: boolean enabled: boolean
is_embedding: boolean
model_type: string
pricing_input: number pricing_input: number
pricing_output: number pricing_output: number
} }

View File

@@ -0,0 +1,6 @@
{
"status": "failed",
"failedTests": [
"825d61429c68a1b0492e-735d17b3ccbad35e8726"
]
}

View File

@@ -0,0 +1,196 @@
# Instructions
- Following Playwright test failed.
- Explain why, be concise, respect Playwright best practices.
- Provide a snippet of code with the fix, if possible.
# Test info
- Name: smoke_admin.spec.ts >> A6: 模型服务页面加载→Provider和Model tab可见
- Location: tests\e2e\smoke_admin.spec.ts:179:1
# Error details
```
TimeoutError: page.waitForSelector: Timeout 15000ms exceeded.
Call log:
- waiting for locator('#main-content') to be visible
```
# Page snapshot
```yaml
- generic [ref=e1]:
- link "跳转到主要内容" [ref=e2] [cursor=pointer]:
- /url: "#main-content"
- generic [ref=e5]:
- generic [ref=e9]:
- generic [ref=e11]: Z
- heading "ZCLAW" [level=1] [ref=e12]
- paragraph [ref=e13]: AI Agent 管理平台
- paragraph [ref=e15]: 统一管理 AI 服务商、模型配置、API 密钥、用量监控与系统配置
- generic [ref=e17]:
- heading "登录" [level=2] [ref=e18]
- paragraph [ref=e19]: 输入您的账号信息以继续
- generic [ref=e22]:
- generic [ref=e28]:
- img "user" [ref=e30]:
- img [ref=e31]
- textbox "请输入用户名" [active] [ref=e33]
- generic [ref=e40]:
- img "lock" [ref=e42]:
- img [ref=e43]
- textbox "请输入密码" [ref=e45]
- img "eye-invisible" [ref=e47] [cursor=pointer]:
- img [ref=e48]
- button "登 录" [ref=e51] [cursor=pointer]:
- generic [ref=e52]: 登 录
```
# Test source
```ts
1 | /**
2 | * Smoke Tests — Admin V2 连通性断裂探测
3 | *
4 | * 6 个冒烟测试验证 Admin V2 页面与 SaaS 后端的完整连通性。
5 | * 所有测试使用真实浏览器 + 真实 SaaS Server。
6 | *
7 | * 前提条件:
8 | * - SaaS Server 运行在 http://localhost:8080
9 | * - Admin V2 dev server 运行在 http://localhost:5173
10 | * - 种子用户: testadmin / Admin123456 (super_admin)
11 | *
12 | * 运行: cd admin-v2 && npx playwright test smoke_admin
13 | */
14 |
15 | import { test, expect, type Page } from '@playwright/test';
16 |
17 | const SaaS_BASE = 'http://localhost:8080/api/v1';
18 | const ADMIN_USER = 'admin';
19 | const ADMIN_PASS = 'admin123';
20 |
21 | // Helper: 通过 API 登录获取 HttpOnly cookie + 设置 localStorage
22 | async function apiLogin(page: Page) {
23 | const res = await page.request.post(`${SaaS_BASE}/auth/login`, {
24 | data: { username: ADMIN_USER, password: ADMIN_PASS },
25 | });
26 | const json = await res.json();
27 | // 设置 localStorage 让 Admin V2 AuthGuard 认为已登录
28 | await page.goto('/');
29 | await page.evaluate((account) => {
30 | localStorage.setItem('zclaw_admin_account', JSON.stringify(account));
31 | }, json.account);
32 | return json;
33 | }
34 |
35 | // Helper: 通过 API 登录 + 导航到指定路径
36 | async function loginAndGo(page: Page, path: string) {
37 | await apiLogin(page);
38 | // 重新导航到目标路径 (localStorage 已设置React 应识别为已登录)
39 | await page.goto(path, { waitUntil: 'networkidle' });
40 | // 等待主内容区加载
> 41 | await page.waitForSelector('#main-content', { timeout: 15000 });
| ^ TimeoutError: page.waitForSelector: Timeout 15000ms exceeded.
42 | }
43 |
44 | // ── A1: 登录→Dashboard ────────────────────────────────────────────
45 |
46 | test('A1: 登录→Dashboard 5个统计卡片', async ({ page }) => {
47 | // 导航到登录页
48 | await page.goto('/login');
49 | await expect(page.getByPlaceholder('请输入用户名')).toBeVisible({ timeout: 10000 });
50 |
51 | // 填写表单
52 | await page.getByPlaceholder('请输入用户名').fill(ADMIN_USER);
53 | await page.getByPlaceholder('请输入密码').fill(ADMIN_PASS);
54 |
55 | // 提交 (Ant Design 按钮文本有全角空格 "登 录")
56 | const loginBtn = page.locator('button').filter({ hasText: /登/ }).first();
57 | await loginBtn.click();
58 |
59 | // 验证跳转到 Dashboard (可能需要等待 API 响应)
60 | await expect(page).toHaveURL(/\/(login)?$/, { timeout: 20000 });
61 |
62 | // 验证 5 个统计卡片
63 | await expect(page.getByText('总账号')).toBeVisible({ timeout: 10000 });
64 | await expect(page.getByText('活跃服务商')).toBeVisible();
65 | await expect(page.getByText('活跃模型')).toBeVisible();
66 | await expect(page.getByText('今日请求')).toBeVisible();
67 | await expect(page.getByText('今日 Token')).toBeVisible();
68 |
69 | // 验证统计卡片有数值 (不是 loading 状态)
70 | const statCards = page.locator('.ant-statistic-content-value');
71 | await expect(statCards.first()).not.toBeEmpty({ timeout: 10000 });
72 | });
73 |
74 | // ── A2: Provider CRUD ──────────────────────────────────────────────
75 |
76 | test('A2: Provider 创建→列表可见→禁用', async ({ page }) => {
77 | // 通过 API 创建 Provider
78 | await apiLogin(page);
79 | const createRes = await page.request.post(`${SaaS_BASE}/providers`, {
80 | data: {
81 | name: `smoke_provider_${Date.now()}`,
82 | provider_type: 'openai',
83 | base_url: 'https://api.smoke.test/v1',
84 | enabled: true,
85 | display_name: 'Smoke Test Provider',
86 | },
87 | });
88 | if (!createRes.ok()) {
89 | const body = await createRes.text();
90 | console.log(`A2: Provider create failed: ${createRes.status()}${body.slice(0, 300)}`);
91 | }
92 | expect(createRes.ok()).toBeTruthy();
93 |
94 | // 导航到 Model Services 页面
95 | await page.goto('/model-services');
96 | await page.waitForSelector('#main-content', { timeout: 15000 });
97 |
98 | // 切换到 Provider tab (如果存在 tab 切换)
99 | const providerTab = page.getByRole('tab', { name: /服务商|Provider/i });
100 | if (await providerTab.isVisible()) {
101 | await providerTab.click();
102 | }
103 |
104 | // 验证 Provider 列表非空
105 | const tableRows = page.locator('.ant-table-row');
106 | await expect(tableRows.first()).toBeVisible({ timeout: 10000 });
107 | expect(await tableRows.count()).toBeGreaterThan(0);
108 | });
109 |
110 | // ── A3: Account 管理 ───────────────────────────────────────────────
111 |
112 | test('A3: Account 列表加载→角色可见', async ({ page }) => {
113 | await loginAndGo(page, '/accounts');
114 |
115 | // 验证表格加载
116 | const tableRows = page.locator('.ant-table-row');
117 | await expect(tableRows.first()).toBeVisible({ timeout: 10000 });
118 |
119 | // 至少有 testadmin 自己
120 | expect(await tableRows.count()).toBeGreaterThanOrEqual(1);
121 |
122 | // 验证有角色列
123 | const roleText = await page.locator('.ant-table').textContent();
124 | expect(roleText).toMatch(/super_admin|admin|user/);
125 | });
126 |
127 | // ── A4: 知识管理 ───────────────────────────────────────────────────
128 |
129 | test('A4: 知识分类→条目→搜索', async ({ page }) => {
130 | // 通过 API 创建分类和条目
131 | await apiLogin(page);
132 |
133 | const catRes = await page.request.post(`${SaaS_BASE}/knowledge/categories`, {
134 | data: { name: `smoke_cat_${Date.now()}`, description: 'Smoke test category' },
135 | });
136 | expect(catRes.ok()).toBeTruthy();
137 | const catJson = await catRes.json();
138 |
139 | const itemRes = await page.request.post(`${SaaS_BASE}/knowledge/items`, {
140 | data: {
141 | title: 'Smoke Test Knowledge Item',
```

View File

@@ -20,7 +20,7 @@ export default defineConfig({
timeout: 600_000, timeout: 600_000,
proxyTimeout: 600_000, proxyTimeout: 600_000,
}, },
'/api': { '/api/': {
target: 'http://localhost:8080', target: 'http://localhost:8080',
changeOrigin: true, changeOrigin: true,
timeout: 30_000, timeout: 30_000,

View File

@@ -0,0 +1,305 @@
//! 进化引擎中枢
//! 协调 L1/L2/L3 三层进化的触发和执行
//! L1 (记忆进化) 在 GrowthIntegration 中处理
//! L2 (技能进化) 通过 PatternAggregator + SkillGenerator + QualityGate 协调
//! L3 (工作流进化) 通过 WorkflowComposer 协调
//! 反馈闭环通过 FeedbackCollector 管理
use std::sync::Arc;
use crate::experience_store::ExperienceStore;
use crate::feedback_collector::{
FeedbackCollector, FeedbackEntry, TrustUpdate,
};
use crate::pattern_aggregator::{AggregatedPattern, PatternAggregator};
use crate::quality_gate::{QualityGate, QualityReport};
use crate::skill_generator::{SkillCandidate, SkillGenerator};
use crate::workflow_composer::{ToolChainPattern, WorkflowComposer};
use crate::VikingAdapter;
use zclaw_types::Result;
/// 进化引擎配置
#[derive(Debug, Clone)]
pub struct EvolutionConfig {
/// 经验复用次数达到此阈值触发 L2
pub min_reuse_for_skill: u32,
/// 置信度阈值
pub quality_confidence_threshold: f32,
/// 是否启用进化引擎
pub enabled: bool,
}
impl Default for EvolutionConfig {
fn default() -> Self {
Self {
min_reuse_for_skill: 3,
quality_confidence_threshold: 0.7,
enabled: true,
}
}
}
/// 进化引擎中枢
pub struct EvolutionEngine {
viking: Arc<VikingAdapter>,
feedback: Arc<tokio::sync::Mutex<FeedbackCollector>>,
config: EvolutionConfig,
}
impl EvolutionEngine {
pub fn new(viking: Arc<VikingAdapter>) -> Self {
Self {
viking: viking.clone(),
feedback: Arc::new(tokio::sync::Mutex::new(
FeedbackCollector::with_viking(viking),
)),
config: EvolutionConfig::default(),
}
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// Backward-compatible constructor
/// 从 ExperienceStore 中提取共享的 VikingAdapter 实例
pub fn from_experience_store(experience_store: Arc<ExperienceStore>) -> Self {
let viking = experience_store.viking().clone();
Self {
viking: viking.clone(),
feedback: Arc::new(tokio::sync::Mutex::new(
FeedbackCollector::with_viking(viking),
)),
config: EvolutionConfig::default(),
}
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
pub fn with_config(mut self, config: EvolutionConfig) -> Self {
self.config = config;
self
}
pub fn set_enabled(&mut self, enabled: bool) {
self.config.enabled = enabled;
}
/// L2 检查:是否有可进化的模式
pub async fn check_evolvable_patterns(
&self,
agent_id: &str,
) -> Result<Vec<AggregatedPattern>> {
if !self.config.enabled {
return Ok(Vec::new());
}
let store = ExperienceStore::new(self.viking.clone());
let aggregator = PatternAggregator::new(store);
aggregator
.find_evolvable_patterns(agent_id, self.config.min_reuse_for_skill)
.await
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// L2 执行:为给定模式构建技能生成 prompt
/// 返回 (prompt_string, pattern) 供上层通过 LLM 调用后 parse
pub fn build_skill_prompt(&self, pattern: &AggregatedPattern) -> String {
SkillGenerator::build_prompt(pattern)
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// L2 执行:解析 LLM 返回的技能 JSON 并进行质量门控
pub fn validate_skill_candidate(
&self,
json_str: &str,
pattern: &AggregatedPattern,
existing_triggers: Vec<String>,
) -> Result<(SkillCandidate, QualityReport)> {
let candidate = SkillGenerator::parse_response(json_str, pattern)?;
let gate = QualityGate::new(self.config.quality_confidence_threshold, existing_triggers);
let report = gate.validate_skill(&candidate);
Ok((candidate, report))
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// 获取当前配置
pub fn config(&self) -> &EvolutionConfig {
&self.config
}
// -----------------------------------------------------------------------
// L3: 工作流进化
// -----------------------------------------------------------------------
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// L3: 从轨迹数据中提取重复的工具链模式
pub fn analyze_trajectory_patterns(
&self,
trajectories: &[(String, Vec<String>)], // (session_id, tools_used)
) -> Vec<(ToolChainPattern, Vec<String>)> {
if !self.config.enabled {
return Vec::new();
}
WorkflowComposer::extract_patterns(trajectories)
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// L3: 为给定工具链模式构建工作流生成 prompt
pub fn build_workflow_prompt(
&self,
pattern: &ToolChainPattern,
frequency: usize,
industry: Option<&str>,
) -> String {
WorkflowComposer::build_prompt(pattern, frequency, industry)
}
// -----------------------------------------------------------------------
// 反馈闭环
// -----------------------------------------------------------------------
/// 提交反馈并获取信任度更新,自动持久化
pub async fn submit_feedback(&self, entry: FeedbackEntry) -> TrustUpdate {
let mut feedback = self.feedback.lock().await;
let update = feedback.submit_feedback(entry);
// 非阻塞持久化:失败仅打日志,不影响返回值
if let Err(e) = feedback.save().await {
tracing::warn!("[EvolutionEngine] Failed to persist trust records: {}", e);
}
update
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// 获取需要优化的进化产物
pub async fn get_artifacts_needing_optimization(&self) -> Vec<String> {
self.feedback
.lock()
.await
.get_artifacts_needing_optimization()
.iter()
.map(|r| r.artifact_id.clone())
.collect()
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// 获取建议归档的进化产物
pub async fn get_artifacts_to_archive(&self) -> Vec<String> {
self.feedback
.lock()
.await
.get_artifacts_to_archive()
.iter()
.map(|r| r.artifact_id.clone())
.collect()
}
/// @reserved: EvolutionEngine L2/L3 feature, post-release integration
/// 获取推荐产物
pub async fn get_recommended_artifacts(&self) -> Vec<String> {
self.feedback
.lock()
.await
.get_recommended_artifacts()
.iter()
.map(|r| r.artifact_id.clone())
.collect()
}
/// 启动时加载已持久化的信任度记录
pub async fn load_feedback(&self) -> Result<usize> {
self.feedback
.lock()
.await
.load()
.await
.map_err(|e| zclaw_types::ZclawError::Internal(e))
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::experience_store::Experience;
#[tokio::test]
async fn test_disabled_returns_empty() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let mut engine = EvolutionEngine::new(viking);
engine.set_enabled(false);
let patterns = engine.check_evolvable_patterns("agent-1").await.unwrap();
assert!(patterns.is_empty());
}
#[tokio::test]
async fn test_no_evolvable_patterns() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let engine = EvolutionEngine::new(viking);
let patterns = engine.check_evolvable_patterns("unknown-agent").await.unwrap();
assert!(patterns.is_empty());
}
#[tokio::test]
async fn test_finds_evolvable_pattern() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let store_inner = ExperienceStore::new(viking.clone());
let mut exp = Experience::new(
"agent-1",
"report generation",
"researcher",
vec!["query db".into(), "format".into()],
"success",
);
exp.reuse_count = 5;
store_inner.store_experience(&exp).await.unwrap();
let engine = EvolutionEngine::new(viking);
let patterns = engine.check_evolvable_patterns("agent-1").await.unwrap();
assert_eq!(patterns.len(), 1);
assert_eq!(patterns[0].pain_pattern, "report generation");
}
#[test]
fn test_build_skill_prompt() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let engine = EvolutionEngine::new(viking);
let exp = Experience::new(
"a", "report", "researcher", vec!["step1".into()], "ok",
);
let pattern = AggregatedPattern {
pain_pattern: "report".to_string(),
experiences: vec![exp],
common_steps: vec!["step1".into()],
total_reuse: 5,
tools_used: vec!["researcher".into()],
industry_context: None,
};
let prompt = engine.build_skill_prompt(&pattern);
assert!(prompt.contains("report"));
}
#[test]
fn test_validate_skill_candidate() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let engine = EvolutionEngine::new(viking);
let exp = Experience::new(
"a", "report", "researcher", vec!["step1".into()], "ok",
);
let pattern = AggregatedPattern {
pain_pattern: "report".to_string(),
experiences: vec![exp],
common_steps: vec!["step1".into()],
total_reuse: 5,
tools_used: vec!["researcher".into()],
industry_context: None,
};
let json = r##"{"name":"报表技能","description":"生成报表","triggers":["报表","日报"],"tools":["researcher"],"body_markdown":"# 报表生成技能\n\n## 步骤一\n收集数据源并验证完整性。\n\n## 步骤二\n按模板格式化输出报表。\n\n## 步骤三\n发送至相关接收人。","confidence":0.9}"##;
let (candidate, report) = engine
.validate_skill_candidate(json, &pattern, vec!["搜索".to_string()])
.unwrap();
assert_eq!(candidate.name, "报表技能");
assert!(report.passed);
}
}

View File

@@ -0,0 +1,119 @@
//! 结构化经验提取器
//! 从对话中提取 ExperienceCandidatepain_pattern → solution_steps → outcome
//! 持久化到 ExperienceStore
use std::sync::Arc;
use crate::experience_store::ExperienceStore;
use crate::types::{CombinedExtraction, Outcome};
/// 结构化经验提取器
/// LLM 调用已由上层 MemoryExtractor 完成,这里只做解析和持久化
pub struct ExperienceExtractor {
store: Option<Arc<ExperienceStore>>,
}
impl ExperienceExtractor {
pub fn new() -> Self {
Self { store: None }
}
pub fn with_store(mut self, store: Arc<ExperienceStore>) -> Self {
self.store = Some(store);
self
}
/// 从 CombinedExtraction 中提取经验并持久化
/// LLM 调用已由上层完成,这里只做解析和存储
pub async fn persist_experiences(
&self,
agent_id: &str,
extraction: &CombinedExtraction,
) -> zclaw_types::Result<usize> {
let store = match &self.store {
Some(s) => s,
None => return Ok(0),
};
let mut count = 0;
for candidate in &extraction.experiences {
if candidate.confidence < 0.6 {
continue;
}
let outcome_str = match candidate.outcome {
Outcome::Success => "success",
Outcome::Partial => "partial",
Outcome::Failed => "failed",
};
let mut exp = crate::experience_store::Experience::new(
agent_id,
&candidate.pain_pattern,
&candidate.context,
candidate.solution_steps.clone(),
outcome_str,
);
// 填充 tool_used取 tools_used 中的第一个作为主要工具
exp.tool_used = candidate.tools_used.first().cloned();
exp.industry_context = candidate.industry_context.clone();
store.store_experience(&exp).await?;
count += 1;
}
Ok(count)
}
}
impl Default for ExperienceExtractor {
fn default() -> Self {
Self::new()
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::types::{ExperienceCandidate, Outcome};
#[test]
fn test_extractor_new_without_store() {
let ext = ExperienceExtractor::new();
assert!(ext.store.is_none());
}
#[tokio::test]
async fn test_persist_no_store_returns_zero() {
let ext = ExperienceExtractor::new();
let extraction = CombinedExtraction::default();
let count = ext.persist_experiences("agent1", &extraction).await.unwrap();
assert_eq!(count, 0);
}
#[tokio::test]
async fn test_persist_filters_low_confidence() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let store = Arc::new(ExperienceStore::new(viking));
let ext = ExperienceExtractor::new().with_store(store);
let mut extraction = CombinedExtraction::default();
extraction.experiences.push(ExperienceCandidate {
pain_pattern: "low confidence task".to_string(),
context: "should be filtered".to_string(),
solution_steps: vec!["step1".to_string()],
outcome: Outcome::Success,
confidence: 0.3, // 低于 0.6 阈值
tools_used: vec![],
industry_context: None,
});
extraction.experiences.push(ExperienceCandidate {
pain_pattern: "high confidence task".to_string(),
context: "should be stored".to_string(),
solution_steps: vec!["step1".to_string(), "step2".to_string()],
outcome: Outcome::Success,
confidence: 0.9,
tools_used: vec!["researcher".to_string()],
industry_context: Some("healthcare".to_string()),
});
let count = ext.persist_experiences("agent-1", &extraction).await.unwrap();
assert_eq!(count, 1); // 只有 1 个通过置信度过滤
}
}

View File

@@ -42,6 +42,15 @@ pub struct Experience {
pub created_at: DateTime<Utc>, pub created_at: DateTime<Utc>,
/// Timestamp of most recent reuse or update. /// Timestamp of most recent reuse or update.
pub updated_at: DateTime<Utc>, pub updated_at: DateTime<Utc>,
/// Associated industry ID (e.g. "ecommerce", "healthcare").
#[serde(default)]
pub industry_context: Option<String>,
/// Which trigger signal produced this experience.
#[serde(default)]
pub source_trigger: Option<String>,
/// Primary tool/skill used to resolve this pain point.
#[serde(default)]
pub tool_used: Option<String>,
} }
impl Experience { impl Experience {
@@ -64,6 +73,9 @@ impl Experience {
reuse_count: 0, reuse_count: 0,
created_at: now, created_at: now,
updated_at: now, updated_at: now,
industry_context: None,
source_trigger: None,
tool_used: None,
} }
} }
@@ -101,16 +113,66 @@ impl ExperienceStore {
Self { viking } Self { viking }
} }
/// Store (or overwrite) an experience. The URI is derived from /// Get a reference to the underlying VikingAdapter.
/// `agent_id + pain_pattern`, ensuring one experience per pattern. pub fn viking(&self) -> &Arc<VikingAdapter> {
&self.viking
}
/// Store an experience, merging with existing if the same pain pattern
/// already exists for this agent. Reuse-count is preserved and incremented
/// rather than reset to zero on re-extraction.
pub async fn store_experience(&self, exp: &Experience) -> zclaw_types::Result<()> { pub async fn store_experience(&self, exp: &Experience) -> zclaw_types::Result<()> {
let uri = exp.uri(); let uri = exp.uri();
// If an experience with this URI already exists, merge instead of overwrite.
if let Some(existing_entry) = self.viking.get(&uri).await? {
let existing = match serde_json::from_str::<Experience>(&existing_entry.content) {
Ok(e) => e,
Err(e) => {
warn!("[ExperienceStore] Failed to deserialize existing experience at {}: {}, overwriting", uri, e);
// Fall through to store new experience as overwrite
self.write_entry(&uri, exp).await?;
return Ok(());
}
};
{
let merged = Experience {
id: existing.id.clone(),
reuse_count: existing.reuse_count + 1,
created_at: existing.created_at,
updated_at: Utc::now(),
// New data takes precedence for content fields
pain_pattern: exp.pain_pattern.clone(),
agent_id: exp.agent_id.clone(),
context: exp.context.clone(),
solution_steps: exp.solution_steps.clone(),
outcome: exp.outcome.clone(),
industry_context: exp.industry_context.clone().or(existing.industry_context.clone()),
source_trigger: exp.source_trigger.clone().or(existing.source_trigger.clone()),
tool_used: exp.tool_used.clone().or(existing.tool_used.clone()),
};
return self.write_entry(&uri, &merged).await;
}
}
self.write_entry(&uri, exp).await
}
/// Low-level write: serialises the experience into a MemoryEntry and
/// persists it through the VikingAdapter.
async fn write_entry(&self, uri: &str, exp: &Experience) -> zclaw_types::Result<()> {
let content = serde_json::to_string(exp)?; let content = serde_json::to_string(exp)?;
let mut keywords = vec![exp.pain_pattern.clone()]; let mut keywords = vec![exp.pain_pattern.clone()];
keywords.extend(exp.solution_steps.iter().take(3).cloned()); keywords.extend(exp.solution_steps.iter().take(3).cloned());
if let Some(ref industry) = exp.industry_context {
keywords.push(industry.clone());
}
if let Some(ref tool) = exp.tool_used {
keywords.push(tool.clone());
}
let entry = MemoryEntry { let entry = MemoryEntry {
uri, uri: uri.to_string(),
memory_type: MemoryType::Experience, memory_type: MemoryType::Experience,
content, content,
keywords, keywords,
@@ -174,7 +236,7 @@ impl ExperienceStore {
let mut updated = exp.clone(); let mut updated = exp.clone();
updated.reuse_count += 1; updated.reuse_count += 1;
updated.updated_at = Utc::now(); updated.updated_at = Utc::now();
if let Err(e) = self.store_experience(&updated).await { if let Err(e) = self.write_entry(&exp.uri(), &updated).await {
warn!("[ExperienceStore] Failed to increment reuse for {}: {}", exp.id, e); warn!("[ExperienceStore] Failed to increment reuse for {}: {}", exp.id, e);
} }
} }
@@ -266,7 +328,7 @@ mod tests {
} }
#[tokio::test] #[tokio::test]
async fn test_store_overwrites_same_pattern() { async fn test_store_merges_same_pattern() {
let viking = Arc::new(VikingAdapter::in_memory()); let viking = Arc::new(VikingAdapter::in_memory());
let store = ExperienceStore::new(viking); let store = ExperienceStore::new(viking);
@@ -280,13 +342,19 @@ mod tests {
"agent-1", "packaging", "v2 updated", "agent-1", "packaging", "v2 updated",
vec!["new step".into()], "better", vec!["new step".into()], "better",
); );
// Force same URI by reusing the ID logic — same pattern → same URI. // Same pattern → same URI → should merge, not overwrite.
store.store_experience(&exp_v2).await.unwrap(); store.store_experience(&exp_v2).await.unwrap();
let found = store.find_by_agent("agent-1").await.unwrap(); let found = store.find_by_agent("agent-1").await.unwrap();
// Should be overwritten, not duplicated (same URI). // Should be merged into one entry, not duplicated.
assert_eq!(found.len(), 1); assert_eq!(found.len(), 1);
// Content fields updated to v2.
assert_eq!(found[0].context, "v2 updated"); assert_eq!(found[0].context, "v2 updated");
assert_eq!(found[0].solution_steps[0], "new step");
// Reuse count incremented (was 0, now 1).
assert_eq!(found[0].reuse_count, 1);
// Original ID and created_at preserved.
assert_eq!(found[0].id, exp_v1.id);
} }
#[tokio::test] #[tokio::test]
@@ -353,4 +421,26 @@ mod tests {
assert_eq!(found_a.len(), 1); assert_eq!(found_a.len(), 1);
assert_eq!(found_a[0].pain_pattern, "packaging"); assert_eq!(found_a[0].pain_pattern, "packaging");
} }
#[tokio::test]
async fn test_reuse_count_accumulates_across_repeated_patterns() {
let viking = Arc::new(VikingAdapter::in_memory());
let store = ExperienceStore::new(viking);
// Store the same pattern 4 times (simulating 4 conversations)
for i in 0..4 {
let exp = Experience::new(
"agent-1", "logistics delay", &format!("context v{}", i),
vec![format!("step {}", i)], &format!("outcome {}", i),
);
store.store_experience(&exp).await.unwrap();
}
let found = store.find_by_agent("agent-1").await.unwrap();
assert_eq!(found.len(), 1);
// First store: reuse_count=0, then 1, 2, 3 after each re-store.
assert_eq!(found[0].reuse_count, 3);
// Content should reflect the latest version.
assert_eq!(found[0].context, "context v3");
}
} }

View File

@@ -19,6 +19,34 @@ pub trait LlmDriverForExtraction: Send + Sync {
messages: &[Message], messages: &[Message],
extraction_type: MemoryType, extraction_type: MemoryType,
) -> Result<Vec<ExtractedMemory>>; ) -> Result<Vec<ExtractedMemory>>;
/// 单次 LLM 调用提取全部类型(记忆 + 经验 + 画像信号)
/// 默认实现:退化到 3 次独立调用experiences 和 profile_signals 为空)
async fn extract_combined_all(
&self,
messages: &[Message],
) -> Result<crate::types::CombinedExtraction> {
let mut combined = crate::types::CombinedExtraction::default();
for mt in [MemoryType::Preference, MemoryType::Knowledge, MemoryType::Experience] {
if let Ok(mems) = self.extract_memories(messages, mt).await {
combined.memories.extend(mems);
}
}
Ok(combined)
}
/// 使用自定义 prompt 进行单次 LLM 调用,返回原始文本响应
/// 用于统一提取场景,默认返回不支持错误
async fn extract_with_prompt(
&self,
_messages: &[Message],
_system_prompt: &str,
_user_prompt: &str,
) -> Result<String> {
Err(zclaw_types::ZclawError::Internal(
"extract_with_prompt not implemented".to_string(),
))
}
} }
/// Memory Extractor - extracts memories from conversations /// Memory Extractor - extracts memories from conversations
@@ -85,13 +113,10 @@ impl MemoryExtractor {
session_id: SessionId, session_id: SessionId,
) -> Result<Vec<ExtractedMemory>> { ) -> Result<Vec<ExtractedMemory>> {
// Check if LLM driver is available // Check if LLM driver is available
let _llm_driver = match &self.llm_driver { if self.llm_driver.is_none() {
Some(driver) => driver, tracing::debug!("[MemoryExtractor] No LLM driver configured, skipping extraction");
None => { return Ok(Vec::new());
tracing::debug!("[MemoryExtractor] No LLM driver configured, skipping extraction"); }
return Ok(Vec::new());
}
};
let mut results = Vec::new(); let mut results = Vec::new();
@@ -227,6 +252,299 @@ impl MemoryExtractor {
tracing::info!("[MemoryExtractor] Stored {} memories to OpenViking", stored); tracing::info!("[MemoryExtractor] Stored {} memories to OpenViking", stored);
Ok(stored) Ok(stored)
} }
/// 统一提取:单次 LLM 调用同时产出 memories + experiences + profile_signals
///
/// 优先使用 `extract_with_prompt()` 进行单次调用;若 driver 不支持则
/// 退化为 `extract()` + 从记忆推断经验/画像。
pub async fn extract_combined(
&self,
messages: &[Message],
session_id: SessionId,
) -> Result<crate::types::CombinedExtraction> {
let llm_driver = match &self.llm_driver {
Some(driver) => driver,
None => {
tracing::debug!(
"[MemoryExtractor] No LLM driver configured, skipping combined extraction"
);
return Ok(crate::types::CombinedExtraction::default());
}
};
// 尝试单次 LLM 调用路径
let system_prompt = "You are a memory extraction assistant. Analyze conversations and extract \
structured memories, experiences, and profile signals in valid JSON format. \
Always respond with valid JSON only, no additional text or markdown formatting.";
let user_prompt = format!(
"{}{}",
crate::extractor::prompts::COMBINED_EXTRACTION_PROMPT,
format_conversation_text(messages)
);
match llm_driver
.extract_with_prompt(messages, system_prompt, &user_prompt)
.await
{
Ok(raw_text) if !raw_text.trim().is_empty() => {
match parse_combined_response(&raw_text, session_id.clone()) {
Ok(combined) => {
tracing::info!(
"[MemoryExtractor] Combined extraction: {} memories, {} experiences, {} profile signals",
combined.memories.len(),
combined.experiences.len(),
combined.profile_signals.signal_count(),
);
return Ok(combined);
}
Err(e) => {
tracing::warn!(
"[MemoryExtractor] Combined response parse failed, falling back: {}",
e
);
}
}
}
Ok(_) => {
tracing::debug!("[MemoryExtractor] extract_with_prompt returned empty, falling back");
}
Err(e) => {
tracing::debug!(
"[MemoryExtractor] extract_with_prompt not supported ({}), falling back",
e
);
}
}
// 退化路径:使用已有的 extract() 然后推断 experiences 和 profile_signals
let memories = self.extract(messages, session_id).await?;
let experiences = infer_experiences_from_memories(&memories);
let profile_signals = infer_profile_signals_from_memories(&memories);
Ok(crate::types::CombinedExtraction {
memories,
experiences,
profile_signals,
})
}
}
/// 格式化对话消息为文本
fn format_conversation_text(messages: &[Message]) -> String {
messages
.iter()
.filter_map(|msg| match msg {
Message::User { content } => Some(format!("[User]: {}", content)),
Message::Assistant { content, .. } => Some(format!("[Assistant]: {}", content)),
Message::System { content } => Some(format!("[System]: {}", content)),
Message::ToolUse { .. } | Message::ToolResult { .. } => None,
})
.collect::<Vec<_>>()
.join("\n\n")
}
/// 从 LLM 原始响应解析 CombinedExtraction
pub fn parse_combined_response(
raw: &str,
session_id: SessionId,
) -> Result<crate::types::CombinedExtraction> {
use crate::types::CombinedExtraction;
let json_str = crate::json_utils::extract_json_block(raw);
let parsed: serde_json::Value = serde_json::from_str(json_str).map_err(|e| {
zclaw_types::ZclawError::Internal(format!("Failed to parse combined JSON: {}", e))
})?;
// 解析 memories
let memories = parsed
.get("memories")
.and_then(|v| v.as_array())
.map(|arr| {
arr.iter()
.filter_map(|item| parse_memory_item(item, &session_id))
.collect::<Vec<_>>()
})
.unwrap_or_default();
// 解析 experiences
let experiences = parsed
.get("experiences")
.and_then(|v| v.as_array())
.map(|arr| {
arr.iter()
.filter_map(parse_experience_item)
.collect::<Vec<_>>()
})
.unwrap_or_default();
// 解析 profile_signals
let profile_signals = parse_profile_signals(&parsed);
Ok(CombinedExtraction {
memories,
experiences,
profile_signals,
})
}
/// 解析单个 memory 项
fn parse_memory_item(
value: &serde_json::Value,
session_id: &SessionId,
) -> Option<ExtractedMemory> {
let content = value.get("content")?.as_str()?.to_string();
let category = value
.get("category")
.and_then(|v| v.as_str())
.unwrap_or("unknown")
.to_string();
let memory_type_str = value
.get("memory_type")
.and_then(|v| v.as_str())
.unwrap_or("knowledge");
let memory_type = crate::types::MemoryType::parse(memory_type_str);
let confidence = value
.get("confidence")
.and_then(|v| v.as_f64())
.unwrap_or(0.7) as f32;
let keywords = crate::json_utils::extract_string_array(value, "keywords");
Some(
ExtractedMemory::new(memory_type, category, content, session_id.clone())
.with_confidence(confidence)
.with_keywords(keywords),
)
}
/// 解析单个 experience 项
fn parse_experience_item(value: &serde_json::Value) -> Option<crate::types::ExperienceCandidate> {
use crate::types::Outcome;
let pain_pattern = value.get("pain_pattern")?.as_str()?.to_string();
let context = value
.get("context")
.and_then(|v| v.as_str())
.unwrap_or("")
.to_string();
let solution_steps = crate::json_utils::extract_string_array(value, "solution_steps");
let outcome_str = value
.get("outcome")
.and_then(|v| v.as_str())
.unwrap_or("partial");
let outcome = match outcome_str {
"success" => Outcome::Success,
"failed" => Outcome::Failed,
_ => Outcome::Partial,
};
let confidence = value
.get("confidence")
.and_then(|v| v.as_f64())
.unwrap_or(0.6) as f32;
let tools_used = crate::json_utils::extract_string_array(value, "tools_used");
let industry_context = value
.get("industry_context")
.and_then(|v| v.as_str())
.map(String::from);
Some(crate::types::ExperienceCandidate {
pain_pattern,
context,
solution_steps,
outcome,
confidence,
tools_used,
industry_context,
})
}
/// 解析 profile_signals
fn parse_profile_signals(obj: &serde_json::Value) -> crate::types::ProfileSignals {
let signals = obj.get("profile_signals");
crate::types::ProfileSignals {
industry: signals
.and_then(|s| s.get("industry"))
.and_then(|v| v.as_str())
.map(String::from),
recent_topic: signals
.and_then(|s| s.get("recent_topic"))
.and_then(|v| v.as_str())
.map(String::from),
pain_point: signals
.and_then(|s| s.get("pain_point"))
.and_then(|v| v.as_str())
.map(String::from),
preferred_tool: signals
.and_then(|s| s.get("preferred_tool"))
.and_then(|v| v.as_str())
.map(String::from),
communication_style: signals
.and_then(|s| s.get("communication_style"))
.and_then(|v| v.as_str())
.map(String::from),
}
}
/// 从已有记忆推断结构化经验(退化路径)
fn infer_experiences_from_memories(
memories: &[ExtractedMemory],
) -> Vec<crate::types::ExperienceCandidate> {
memories
.iter()
.filter(|m| m.memory_type == crate::types::MemoryType::Experience)
.filter_map(|m| {
// 经验类记忆 → ExperienceCandidate
let content = &m.content;
if content.len() < 10 {
return None;
}
Some(crate::types::ExperienceCandidate {
pain_pattern: m.category.clone(),
context: content.clone(),
solution_steps: Vec::new(),
outcome: crate::types::Outcome::Partial,
confidence: m.confidence * 0.7, // 降低推断置信度
tools_used: m.keywords.clone(),
industry_context: None,
})
})
.collect()
}
/// 从已有记忆推断画像信号(退化路径)
fn infer_profile_signals_from_memories(
memories: &[ExtractedMemory],
) -> crate::types::ProfileSignals {
use crate::types::ProfileSignals;
let mut signals = ProfileSignals::default();
for m in memories {
match m.memory_type {
crate::types::MemoryType::Preference => {
if m.category.contains("style") || m.category.contains("风格") {
if signals.communication_style.is_none() {
signals.communication_style = Some(m.content.clone());
}
}
}
crate::types::MemoryType::Knowledge => {
if signals.recent_topic.is_none() && !m.keywords.is_empty() {
signals.recent_topic = Some(m.keywords.first().cloned().unwrap_or_default());
}
}
crate::types::MemoryType::Experience => {
for kw in &m.keywords {
if signals.preferred_tool.is_none()
&& m.content.contains(kw.as_str())
{
signals.preferred_tool = Some(kw.clone());
break;
}
}
}
_ => {}
}
}
signals
} }
/// Default extraction prompts for LLM /// Default extraction prompts for LLM
@@ -243,6 +561,55 @@ pub mod prompts {
} }
} }
/// 统一提取 prompt — 单次 LLM 调用同时提取记忆、结构化经验、画像信号
pub const COMBINED_EXTRACTION_PROMPT: &str = r#"
分析以下对话,一次性提取三类信息。严格按 JSON 格式返回。
## 输出格式
```json
{
"memories": [
{
"memory_type": "preference|knowledge|experience",
"category": "分类标签",
"content": "记忆内容",
"confidence": 0.0-1.0,
"keywords": ["关键词"]
}
],
"experiences": [
{
"pain_pattern": "痛点模式简述",
"context": "问题发生的上下文",
"solution_steps": ["步骤1", "步骤2"],
"outcome": "success|partial|failed",
"confidence": 0.0-1.0,
"tools_used": ["使用的工具/技能"],
"industry_context": "行业标识(可选)"
}
],
"profile_signals": {
"industry": "用户所在行业(可选)",
"recent_topic": "最近讨论的主要话题(可选)",
"pain_point": "用户当前痛点(可选)",
"preferred_tool": "用户偏好的工具/技能(可选)",
"communication_style": "沟通风格: concise|detailed|formal|casual(可选)"
}
}
```
## 提取规则
1. **memories**: 提取用户偏好(沟通风格/格式/语言)、知识(事实/领域知识/经验教训)、使用经验(技能/工具使用模式和结果)
2. **experiences**: 仅提取明确的"问题→解决"模式要求有清晰的痛点和步骤confidence >= 0.6
3. **profile_signals**: 从对话中推断用户画像信息,只在有明确信号时填写,留空则不填
4. 每个字段都要有实际内容,不确定的宁可省略
5. 只返回 JSON不要附加其他文本
对话内容:
"#;
const PREFERENCE_EXTRACTION_PROMPT: &str = r#" const PREFERENCE_EXTRACTION_PROMPT: &str = r#"
分析以下对话,提取用户的偏好设置。关注: 分析以下对话,提取用户的偏好设置。关注:
- 沟通风格偏好(简洁/详细、正式/随意) - 沟通风格偏好(简洁/详细、正式/随意)
@@ -362,11 +729,103 @@ mod tests {
assert!(!result.is_empty()); assert!(!result.is_empty());
} }
#[tokio::test]
async fn test_extract_combined_all_default_impl() {
let driver = MockLlmDriver;
let messages = vec![Message::user("Hello")];
let result = driver.extract_combined_all(&messages).await.unwrap();
assert_eq!(result.memories.len(), 3); // 3 types
}
#[test] #[test]
fn test_prompts_available() { fn test_prompts_available() {
assert!(!prompts::get_extraction_prompt(MemoryType::Preference).is_empty()); assert!(!prompts::get_extraction_prompt(MemoryType::Preference).is_empty());
assert!(!prompts::get_extraction_prompt(MemoryType::Knowledge).is_empty()); assert!(!prompts::get_extraction_prompt(MemoryType::Knowledge).is_empty());
assert!(!prompts::get_extraction_prompt(MemoryType::Experience).is_empty()); assert!(!prompts::get_extraction_prompt(MemoryType::Experience).is_empty());
assert!(!prompts::get_extraction_prompt(MemoryType::Session).is_empty()); assert!(!prompts::get_extraction_prompt(MemoryType::Session).is_empty());
assert!(!prompts::COMBINED_EXTRACTION_PROMPT.is_empty());
}
#[test]
fn test_parse_combined_response_full() {
let raw = r#"```json
{
"memories": [
{
"memory_type": "preference",
"category": "communication-style",
"content": "用户偏好简洁回复",
"confidence": 0.9,
"keywords": ["简洁", "风格"]
},
{
"memory_type": "knowledge",
"category": "user-facts",
"content": "用户是医院行政人员",
"confidence": 0.85,
"keywords": ["医院", "行政"]
}
],
"experiences": [
{
"pain_pattern": "报表生成耗时",
"context": "月度报表需要手动汇总多个Excel",
"solution_steps": ["使用researcher工具自动抓取", "格式化输出为Excel"],
"outcome": "success",
"confidence": 0.85,
"tools_used": ["researcher"],
"industry_context": "healthcare"
}
],
"profile_signals": {
"industry": "healthcare",
"recent_topic": "报表自动化",
"pain_point": "手动汇总Excel太慢",
"preferred_tool": "researcher",
"communication_style": "concise"
}
}
```"#;
let result = super::parse_combined_response(raw, SessionId::new()).unwrap();
assert_eq!(result.memories.len(), 2);
assert_eq!(result.experiences.len(), 1);
assert_eq!(result.experiences[0].pain_pattern, "报表生成耗时");
assert_eq!(result.experiences[0].outcome, crate::types::Outcome::Success);
assert_eq!(result.profile_signals.industry.as_deref(), Some("healthcare"));
assert_eq!(result.profile_signals.pain_point.as_deref(), Some("手动汇总Excel太慢"));
assert!(result.profile_signals.has_any_signal());
}
#[test]
fn test_parse_combined_response_minimal() {
let raw = r#"{"memories": [], "experiences": [], "profile_signals": {}}"#;
let result = super::parse_combined_response(raw, SessionId::new()).unwrap();
assert!(result.memories.is_empty());
assert!(result.experiences.is_empty());
assert!(!result.profile_signals.has_any_signal());
}
#[test]
fn test_parse_combined_response_invalid() {
let raw = "not json at all";
let result = super::parse_combined_response(raw, SessionId::new());
assert!(result.is_err());
}
#[tokio::test]
async fn test_extract_combined_fallback() {
// MockLlmDriver doesn't implement extract_with_prompt, so it falls back
let driver = Arc::new(MockLlmDriver);
let extractor = MemoryExtractor::new(driver);
let messages = vec![Message::user("Hello"), Message::assistant("Hi there!")];
let result = extractor
.extract_combined(&messages, SessionId::new())
.await
.unwrap();
// Fallback: extract() produces 3 memories, infer produces experiences from them
assert!(!result.memories.is_empty());
} }
} }

View File

@@ -0,0 +1,448 @@
//! 反馈信号收集与信任度管理Phase 5 反馈闭环)
//! 收集用户对进化产物(技能/Pipeline的显式/隐式反馈
//! 管理信任度衰减和优化循环
//! 信任度记录通过 VikingAdapter 持久化
use std::collections::HashMap;
use std::sync::Arc;
use chrono::{DateTime, Utc};
use serde::{Deserialize, Serialize};
use crate::types::MemoryType;
use crate::viking_adapter::VikingAdapter;
/// 反馈信号类型
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum FeedbackSignal {
/// 用户直接表达的意见
Explicit,
/// 从使用行为推断
ImplicitUsage,
/// 使用频率
UsageCount,
/// 任务完成率
CompletionRate,
}
/// 情感倾向
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum Sentiment {
Positive,
Negative,
Neutral,
}
/// 进化产物类型
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum EvolutionArtifact {
Skill,
Pipeline,
}
/// 单条反馈记录
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct FeedbackEntry {
pub artifact_id: String,
pub artifact_type: EvolutionArtifact,
pub signal: FeedbackSignal,
pub sentiment: Sentiment,
pub details: Option<String>,
pub timestamp: DateTime<Utc>,
}
/// 信任度记录
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TrustRecord {
pub artifact_id: String,
pub artifact_type: EvolutionArtifact,
pub trust_score: f32,
pub total_feedback: u32,
pub positive_count: u32,
pub negative_count: u32,
pub last_updated: DateTime<Utc>,
}
/// 反馈收集器
/// 管理反馈记录和信任度评分
/// 通过 VikingAdapter 持久化信任度记录(可选)
pub struct FeedbackCollector {
trust_records: HashMap<String, TrustRecord>,
viking: Option<Arc<VikingAdapter>>,
/// 是否已从持久化存储加载信任度记录
loaded: bool,
}
impl FeedbackCollector {
pub fn new() -> Self {
Self {
trust_records: HashMap::new(),
viking: None,
loaded: false,
}
}
/// 创建带 VikingAdapter 的 FeedbackCollector
pub fn with_viking(viking: Arc<VikingAdapter>) -> Self {
Self {
trust_records: HashMap::new(),
viking: Some(viking),
loaded: false,
}
}
/// 从 VikingAdapter 加载已持久化的信任度记录
pub async fn load(&mut self) -> Result<usize, String> {
let viking = match &self.viking {
Some(v) => v,
None => return Ok(0),
};
// MemoryEntry::new("feedback", Session, artifact_id) 生成
// URI: agent://feedback/sessions/{artifact_id}
let entries = viking
.find_by_prefix("agent://feedback/sessions/")
.await
.map_err(|e| format!("Failed to load trust records: {}", e))?;
let mut count = 0;
for entry in entries {
match serde_json::from_str::<TrustRecord>(&entry.content) {
Ok(record) => {
// 只合并不覆盖:保留内存中的较新记录
self.trust_records
.entry(record.artifact_id.clone())
.or_insert(record);
count += 1;
}
Err(e) => {
tracing::warn!(
"[FeedbackCollector] Failed to deserialize trust record at {}: {}",
entry.uri,
e
);
}
}
}
tracing::debug!(
"[FeedbackCollector] Loaded {} trust records from storage",
count
);
Ok(count)
}
/// 将信任度记录持久化到 VikingAdapter
/// 首次调用时自动从存储加载已有记录,避免覆盖
pub async fn save(&mut self) -> Result<usize, String> {
// 首次保存前自动加载已有记录,防止丢失历史数据
if !self.loaded {
match self.load().await {
Ok(_) => {
self.loaded = true;
}
Err(e) => {
// 加载失败时保留 loaded=false下次 save 会重试
tracing::warn!(
"[FeedbackCollector] Auto-load before save failed, will retry next save: {}",
e
);
}
}
}
let viking = match &self.viking {
Some(v) => v,
None => return Ok(0),
};
let mut saved = 0;
for record in self.trust_records.values() {
let content = match serde_json::to_string(record) {
Ok(c) => c,
Err(e) => {
tracing::warn!(
"[FeedbackCollector] Failed to serialize trust record {}: {}",
record.artifact_id,
e
);
continue;
}
};
let entry = crate::types::MemoryEntry::new(
"feedback",
MemoryType::Session,
&record.artifact_id,
content,
)
.with_importance((record.trust_score * 10.0) as u8);
match viking.store(&entry).await {
Ok(_) => saved += 1,
Err(e) => {
tracing::warn!(
"[FeedbackCollector] Failed to save trust record {}: {}",
record.artifact_id,
e
);
}
}
}
tracing::debug!(
"[FeedbackCollector] Saved {} trust records to storage",
saved
);
Ok(saved)
}
/// 提交一条反馈
pub fn submit_feedback(&mut self, entry: FeedbackEntry) -> TrustUpdate {
let record = self
.trust_records
.entry(entry.artifact_id.clone())
.or_insert_with(|| TrustRecord {
artifact_id: entry.artifact_id.clone(),
artifact_type: entry.artifact_type.clone(),
trust_score: 0.5,
total_feedback: 0,
positive_count: 0,
negative_count: 0,
last_updated: Utc::now(),
});
// 更新计数
record.total_feedback += 1;
match entry.sentiment {
Sentiment::Positive => record.positive_count += 1,
Sentiment::Negative => record.negative_count += 1,
Sentiment::Neutral => {}
}
// 重新计算信任度
let old_score = record.trust_score;
record.trust_score = Self::calculate_trust_internal(
record.positive_count,
record.negative_count,
record.total_feedback,
record.last_updated,
);
record.last_updated = Utc::now();
let new_score = record.trust_score;
let total = record.total_feedback;
let action = Self::recommend_action_internal(new_score, total);
TrustUpdate {
artifact_id: entry.artifact_id.clone(),
old_score,
new_score,
action,
}
}
/// 获取信任度记录
pub fn get_trust(&self, artifact_id: &str) -> Option<&TrustRecord> {
self.trust_records.get(artifact_id)
}
/// 获取所有需要优化的产物(信任度 < 0.4
pub fn get_artifacts_needing_optimization(&self) -> Vec<&TrustRecord> {
self.trust_records
.values()
.filter(|r| r.trust_score < 0.4 && r.total_feedback >= 2)
.collect()
}
/// 获取所有应该归档的产物(信任度 < 0.2 且反馈 >= 5
pub fn get_artifacts_to_archive(&self) -> Vec<&TrustRecord> {
self.trust_records
.values()
.filter(|r| r.trust_score < 0.2 && r.total_feedback >= 5)
.collect()
}
/// 获取所有高信任产物(信任度 >= 0.8
pub fn get_recommended_artifacts(&self) -> Vec<&TrustRecord> {
self.trust_records
.values()
.filter(|r| r.trust_score >= 0.8)
.collect()
}
fn calculate_trust_internal(
positive: u32,
negative: u32,
total: u32,
last_updated: DateTime<Utc>,
) -> f32 {
if total == 0 {
return 0.5;
}
let positive_ratio = positive as f32 / total as f32;
let negative_penalty = negative as f32 * 0.1;
let days_since = (Utc::now() - last_updated).num_days().max(0) as f32;
let time_decay = 1.0 - (days_since * 0.005).min(0.5);
(positive_ratio * time_decay - negative_penalty).clamp(0.0, 1.0)
}
fn recommend_action_internal(trust_score: f32, total_feedback: u32) -> RecommendedAction {
if trust_score >= 0.8 {
RecommendedAction::Promote
} else if trust_score < 0.2 && total_feedback >= 5 {
RecommendedAction::Archive
} else if trust_score < 0.4 && total_feedback >= 2 {
RecommendedAction::Optimize
} else {
RecommendedAction::Monitor
}
}
}
impl Default for FeedbackCollector {
fn default() -> Self {
Self::new()
}
}
/// 信任度更新结果
#[derive(Debug, Clone)]
pub struct TrustUpdate {
pub artifact_id: String,
pub old_score: f32,
pub new_score: f32,
pub action: RecommendedAction,
}
/// 建议动作
#[derive(Debug, Clone, PartialEq)]
pub enum RecommendedAction {
/// 继续观察
Monitor,
/// 需要优化
Optimize,
/// 建议归档(降级为记忆)
Archive,
/// 建议提升为推荐技能
Promote,
}
#[cfg(test)]
mod tests {
use super::*;
fn make_feedback(artifact_id: &str, sentiment: Sentiment) -> FeedbackEntry {
FeedbackEntry {
artifact_id: artifact_id.to_string(),
artifact_type: EvolutionArtifact::Skill,
signal: FeedbackSignal::Explicit,
sentiment,
details: None,
timestamp: Utc::now(),
}
}
#[test]
fn test_initial_trust() {
let collector = FeedbackCollector::new();
assert!(collector.get_trust("skill-1").is_none());
}
#[test]
fn test_positive_feedback_increases_trust() {
let mut collector = FeedbackCollector::new();
collector.submit_feedback(make_feedback("skill-1", Sentiment::Positive));
let record = collector.get_trust("skill-1").unwrap();
assert!(record.trust_score > 0.5);
assert_eq!(record.positive_count, 1);
}
#[test]
fn test_negative_feedback_decreases_trust() {
let mut collector = FeedbackCollector::new();
collector.submit_feedback(make_feedback("skill-1", Sentiment::Negative));
let record = collector.get_trust("skill-1").unwrap();
assert!(record.trust_score < 0.5);
}
#[test]
fn test_mixed_feedback() {
let mut collector = FeedbackCollector::new();
collector.submit_feedback(make_feedback("skill-1", Sentiment::Positive));
collector.submit_feedback(make_feedback("skill-1", Sentiment::Positive));
collector.submit_feedback(make_feedback("skill-1", Sentiment::Negative));
let record = collector.get_trust("skill-1").unwrap();
assert_eq!(record.total_feedback, 3);
assert!(record.trust_score > 0.3); // 2/3 positive
}
#[test]
fn test_recommend_optimize() {
let mut collector = FeedbackCollector::new();
collector.submit_feedback(make_feedback("skill-1", Sentiment::Negative));
let update = collector.submit_feedback(make_feedback("skill-1", Sentiment::Negative));
assert_eq!(update.action, RecommendedAction::Optimize);
}
#[test]
fn test_needs_optimization_filter() {
let mut collector = FeedbackCollector::new();
collector.submit_feedback(make_feedback("bad-skill", Sentiment::Negative));
collector.submit_feedback(make_feedback("bad-skill", Sentiment::Negative));
collector.submit_feedback(make_feedback("good-skill", Sentiment::Positive));
let needs = collector.get_artifacts_needing_optimization();
assert_eq!(needs.len(), 1);
assert_eq!(needs[0].artifact_id, "bad-skill");
}
#[test]
fn test_promote_recommendation() {
let mut collector = FeedbackCollector::new();
for _ in 0..5 {
collector.submit_feedback(make_feedback("great-skill", Sentiment::Positive));
}
let recommended = collector.get_recommended_artifacts();
assert_eq!(recommended.len(), 1);
}
#[tokio::test]
async fn test_save_and_load_roundtrip() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
// 写入阶段
let mut collector = FeedbackCollector::with_viking(viking.clone());
collector.submit_feedback(make_feedback("skill-a", Sentiment::Positive));
collector.submit_feedback(make_feedback("skill-a", Sentiment::Positive));
collector.submit_feedback(make_feedback("skill-b", Sentiment::Negative));
let saved = collector.save().await.unwrap();
assert_eq!(saved, 2); // 2 个 artifact
// 读取阶段:新 collector 从存储加载
let mut collector2 = FeedbackCollector::with_viking(viking);
let loaded = collector2.load().await.unwrap();
assert_eq!(loaded, 2);
let record_a = collector2.get_trust("skill-a").unwrap();
assert_eq!(record_a.positive_count, 2);
assert_eq!(record_a.total_feedback, 2);
let record_b = collector2.get_trust("skill-b").unwrap();
assert_eq!(record_b.negative_count, 1);
}
#[tokio::test]
async fn test_load_without_viking_returns_zero() {
let mut collector = FeedbackCollector::new();
let loaded = collector.load().await.unwrap();
assert_eq!(loaded, 0);
}
#[tokio::test]
async fn test_save_without_viking_returns_zero() {
let mut collector = FeedbackCollector::new();
let saved = collector.save().await.unwrap();
assert_eq!(saved, 0);
}
}

View File

@@ -0,0 +1,148 @@
//! 共享 JSON 工具函数
//! 从 LLM 返回的文本中提取 JSON 块
/// 从 LLM 返回文本中提取 JSON 块
/// 支持三种格式:```json...``` 围栏、```...``` 围栏、裸 {...}
/// 使用括号平衡算法找到第一个完整 JSON 块,避免误匹配
pub fn extract_json_block(text: &str) -> &str {
// 尝试匹配 ```json ... ```
if let Some(start) = text.find("```json") {
let json_start = start + 7;
if let Some(end) = text[json_start..].find("```") {
return text[json_start..json_start + end].trim();
}
}
// 尝试匹配 ``` ... ```
if let Some(start) = text.find("```") {
let json_start = start + 3;
if let Some(end) = text[json_start..].find("```") {
return text[json_start..json_start + end].trim();
}
}
// 用括号平衡算法找第一个完整 {...} 块
if let Some(slice) = find_balanced_json(text) {
return slice;
}
text.trim()
}
/// 使用括号平衡计数找到第一个完整的 {...} JSON 块
/// 正确处理字符串字面量中的花括号
fn find_balanced_json(text: &str) -> Option<&str> {
let start = text.find('{')?;
let mut depth = 0i32;
let mut in_string = false;
let mut escape_next = false;
for (i, c) in text[start..].char_indices() {
if escape_next {
escape_next = false;
continue;
}
match c {
'\\' if in_string => escape_next = true,
'"' => in_string = !in_string,
'{' if !in_string => {
depth += 1;
}
'}' if !in_string => {
depth -= 1;
if depth == 0 {
return Some(&text[start..=start + i]);
}
}
_ => {}
}
}
None
}
/// 从 serde_json::Value 中提取字符串数组
/// 用于解析 LLM 返回 JSON 中的 triggers/tools 等字段
pub fn extract_string_array(raw: &serde_json::Value, key: &str) -> Vec<String> {
raw.get(key)
.and_then(|v| v.as_array())
.map(|a| {
a.iter()
.filter_map(|v| v.as_str().map(String::from))
.collect()
})
.unwrap_or_default()
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_json_block_with_markdown() {
let text = "Here is the result:\n```json\n{\"key\": \"value\"}\n```\nDone.";
assert_eq!(extract_json_block(text), "{\"key\": \"value\"}");
}
#[test]
fn test_json_block_bare() {
let text = "{\"key\": \"value\"}";
assert_eq!(extract_json_block(text), "{\"key\": \"value\"}");
}
#[test]
fn test_json_block_plain_fences() {
let text = "Result:\n```\n{\"a\": 1}\n```";
assert_eq!(extract_json_block(text), "{\"a\": 1}");
}
#[test]
fn test_json_block_nested_braces() {
let text = r#"{"outer": {"inner": "val"}}"#;
assert_eq!(extract_json_block(text), r#"{"outer": {"inner": "val"}}"#);
}
#[test]
fn test_json_block_no_json() {
let text = "no json here";
assert_eq!(extract_json_block(text), "no json here");
}
#[test]
fn test_balanced_json_skips_outer_text() {
// 第一个 { 到最后一个 } 会包含多余文本,但平衡算法只取第一个完整块
let text = "prefix {\"a\": 1} suffix {\"b\": 2}";
assert_eq!(extract_json_block(text), "{\"a\": 1}");
}
#[test]
fn test_balanced_json_handles_braces_in_strings() {
let text = r#"{"body": "function() { return x; }", "name": "test"}"#;
assert_eq!(
extract_json_block(text),
r#"{"body": "function() { return x; }", "name": "test"}"#
);
}
#[test]
fn test_balanced_json_handles_escaped_quotes() {
let text = r#"{"msg": "He said \"hello {world}\""}"#;
assert_eq!(
extract_json_block(text),
r#"{"msg": "He said \"hello {world}\""}"#
);
}
#[test]
fn test_extract_string_array() {
let raw: serde_json::Value = serde_json::from_str(
r#"{"triggers": ["报表", "日报"], "name": "test"}"#,
)
.unwrap();
let arr = extract_string_array(&raw, "triggers");
assert_eq!(arr, vec!["报表", "日报"]);
}
#[test]
fn test_extract_string_array_missing_key() {
let raw: serde_json::Value = serde_json::from_str(r#"{"name": "test"}"#).unwrap();
let arr = extract_string_array(&raw, "triggers");
assert!(arr.is_empty());
}
}

View File

@@ -5,10 +5,13 @@
//! //!
//! # Architecture //! # Architecture
//! //!
//! The growth system consists of four main components: //! The growth system consists of several subsystems:
//!
//! ## Memory Pipeline (L0-L2)
//! //!
//! 1. **MemoryExtractor** (`extractor`) - Analyzes conversations and extracts //! 1. **MemoryExtractor** (`extractor`) - Analyzes conversations and extracts
//! preferences, knowledge, and experience using LLM. //! preferences, knowledge, and experience using LLM. Supports combined extraction
//! (single LLM call for memories + experiences + profile signals).
//! //!
//! 2. **MemoryRetriever** (`retriever`) - Performs semantic search over //! 2. **MemoryRetriever** (`retriever`) - Performs semantic search over
//! stored memories to find contextually relevant information. //! stored memories to find contextually relevant information.
@@ -19,6 +22,28 @@
//! 4. **GrowthTracker** (`tracker`) - Tracks growth metrics and evolution //! 4. **GrowthTracker** (`tracker`) - Tracks growth metrics and evolution
//! over time. //! over time.
//! //!
//! ## Evolution Engine (L1-L3)
//!
//! 5. **ExperienceStore** (`experience_store`) - FTS5-backed structured experience storage.
//!
//! 6. **PatternAggregator** (`pattern_aggregator`) - Collects high-frequency patterns for L2.
//!
//! 7. **SkillGenerator** (`skill_generator`) - LLM-driven SKILL.md content generation.
//!
//! 8. **QualityGate** (`quality_gate`) - Validates candidate skills (confidence, conflicts).
//!
//! 9. **EvolutionEngine** (`evolution_engine`) - Orchestrates L1/L2/L3 evolution phases.
//!
//! 10. **WorkflowComposer** (`workflow_composer`) - Extracts tool chain patterns for Pipeline YAML.
//!
//! 11. **FeedbackCollector** (`feedback_collector`) - Trust score management with decay.
//!
//! ## Support Modules
//!
//! 12. **VikingAdapter** (`viking_adapter`) - Storage abstraction (in-memory + SQLite backends).
//! 13. **Summarizer** (`summarizer`) - L0/L1 summary generation.
//! 14. **JsonUtils** (`json_utils`) - Shared JSON parsing utilities.
//!
//! # Storage //! # Storage
//! //!
//! All memories are stored in OpenViking with a URI structure: //! All memories are stored in OpenViking with a URI structure:
@@ -65,6 +90,15 @@ pub mod storage;
pub mod retrieval; pub mod retrieval;
pub mod summarizer; pub mod summarizer;
pub mod experience_store; pub mod experience_store;
pub mod json_utils;
pub mod experience_extractor;
pub mod profile_updater;
pub mod pattern_aggregator;
pub mod skill_generator;
pub mod quality_gate;
pub mod evolution_engine;
pub mod workflow_composer;
pub mod feedback_collector;
// Re-export main types for convenience // Re-export main types for convenience
pub use types::{ pub use types::{
@@ -78,6 +112,14 @@ pub use types::{
RetrievalResult, RetrievalResult,
UriBuilder, UriBuilder,
effective_importance, effective_importance,
ArtifactType,
CombinedExtraction,
EvolutionEvent,
EvolutionEventType,
EvolutionStatus,
ExperienceCandidate,
Outcome,
ProfileSignals,
}; };
pub use extractor::{LlmDriverForExtraction, MemoryExtractor}; pub use extractor::{LlmDriverForExtraction, MemoryExtractor};
@@ -89,6 +131,18 @@ pub use storage::SqliteStorage;
pub use experience_store::{Experience, ExperienceStore}; pub use experience_store::{Experience, ExperienceStore};
pub use retrieval::{EmbeddingClient, MemoryCache, QueryAnalyzer, SemanticScorer}; pub use retrieval::{EmbeddingClient, MemoryCache, QueryAnalyzer, SemanticScorer};
pub use summarizer::SummaryLlmDriver; pub use summarizer::SummaryLlmDriver;
pub use experience_extractor::ExperienceExtractor;
pub use json_utils::{extract_json_block, extract_string_array};
pub use profile_updater::{ProfileFieldUpdate, ProfileUpdateKind, UserProfileUpdater};
pub use pattern_aggregator::{AggregatedPattern, PatternAggregator};
pub use skill_generator::{SkillCandidate, SkillGenerator};
pub use quality_gate::{QualityGate, QualityReport};
pub use evolution_engine::{EvolutionConfig, EvolutionEngine};
pub use workflow_composer::{PipelineCandidate, ToolChainPattern, WorkflowComposer};
pub use feedback_collector::{
EvolutionArtifact, FeedbackCollector, FeedbackEntry, FeedbackSignal,
RecommendedAction, Sentiment, TrustRecord, TrustUpdate,
};
/// Growth system configuration /// Growth system configuration
#[derive(Debug, Clone)] #[derive(Debug, Clone)]

View File

@@ -0,0 +1,245 @@
//! 经验模式聚合器
//! 收集同一 pain_pattern 下的所有 Experience找出共同步骤
//! 用于 L2 技能进化触发判断
use std::collections::HashMap;
use crate::experience_store::{Experience, ExperienceStore};
use zclaw_types::Result;
/// 聚合后的经验模式
#[derive(Debug, Clone)]
pub struct AggregatedPattern {
pub pain_pattern: String,
pub experiences: Vec<Experience>,
pub common_steps: Vec<String>,
pub total_reuse: u32,
pub tools_used: Vec<String>,
pub industry_context: Option<String>,
}
/// 经验模式聚合器
/// 从 ExperienceStore 中收集高频复用的模式,作为 L2 技能生成的输入
pub struct PatternAggregator {
store: ExperienceStore,
}
impl PatternAggregator {
pub fn new(store: ExperienceStore) -> Self {
Self { store }
}
/// 查找可固化的模式reuse_count >= threshold 的经验
pub async fn find_evolvable_patterns(
&self,
agent_id: &str,
min_reuse: u32,
) -> Result<Vec<AggregatedPattern>> {
let all = self.store.find_by_agent(agent_id).await?;
let mut grouped: HashMap<String, Vec<Experience>> = HashMap::new();
for exp in all {
if exp.reuse_count >= min_reuse {
grouped
.entry(exp.pain_pattern.clone())
.or_default()
.push(exp);
}
}
let mut patterns = Vec::new();
for (pattern, experiences) in grouped {
let total_reuse: u32 = experiences.iter().map(|e| e.reuse_count).sum();
let common_steps = Self::find_common_steps(&experiences);
// 从 tool_used 字段提取工具名
let tools: Vec<String> = experiences
.iter()
.filter_map(|e| e.tool_used.clone())
.filter(|s| !s.is_empty())
.collect::<std::collections::HashSet<_>>()
.into_iter()
.collect();
let industry = experiences
.iter()
.filter_map(|e| e.industry_context.clone())
.next();
patterns.push(AggregatedPattern {
pain_pattern: pattern,
experiences,
common_steps,
total_reuse,
tools_used: tools,
industry_context: industry,
});
}
// 按 reuse 排序
patterns.sort_by(|a, b| b.total_reuse.cmp(&a.total_reuse));
Ok(patterns)
}
/// 找出多条经验中共同的解决步骤
fn find_common_steps(experiences: &[Experience]) -> Vec<String> {
if experiences.is_empty() {
return Vec::new();
}
if experiences.len() == 1 {
return experiences[0].solution_steps.clone();
}
// 取所有经验的交集步骤
let mut step_counts: HashMap<String, u32> = HashMap::new();
for exp in experiences {
for step in &exp.solution_steps {
*step_counts.entry(step.clone()).or_insert(0) += 1;
}
}
let threshold = experiences.len() as f32 * 0.5; // 出现在 50%+ 的经验中
let mut common: Vec<_> = step_counts
.into_iter()
.filter(|(_, count)| (*count as f32) >= threshold)
.map(|(step, _)| step)
.collect();
common.dedup();
common
}
}
#[cfg(test)]
mod tests {
use super::*;
use std::sync::Arc;
#[test]
fn test_find_common_steps_empty() {
let steps = PatternAggregator::find_common_steps(&[]);
assert!(steps.is_empty());
}
#[test]
fn test_find_common_steps_single() {
let exp = Experience::new(
"a",
"packaging",
"ctx",
vec!["step1".into(), "step2".into()],
"ok",
);
let steps = PatternAggregator::find_common_steps(&[exp]);
assert_eq!(steps.len(), 2);
}
#[test]
fn test_find_common_steps_multiple() {
let exp1 = Experience::new(
"a",
"packaging",
"ctx",
vec!["step1".into(), "step2".into(), "step3".into()],
"ok",
);
let exp2 = Experience::new(
"a",
"packaging",
"ctx",
vec!["step1".into(), "step2".into(), "step4".into()],
"ok",
);
// step1 and step2 appear in both (100% >= 50%)
let steps = PatternAggregator::find_common_steps(&[exp1, exp2]);
assert!(steps.contains(&"step1".to_string()));
assert!(steps.contains(&"step2".to_string()));
}
#[tokio::test]
async fn test_find_evolvable_patterns_filters_low_reuse() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let store = ExperienceStore::new(viking);
// 经验 1: reuse_count = 0 (低于阈值)
let mut exp_low = Experience::new(
"agent-1",
"low reuse task",
"ctx",
vec!["step".into()],
"ok",
);
exp_low.reuse_count = 0;
store.store_experience(&exp_low).await.unwrap();
// 经验 2: reuse_count = 5 (高于阈值)
let mut exp_high = Experience::new(
"agent-1",
"high reuse task",
"ctx",
vec!["step1".into()],
"ok",
);
exp_high.reuse_count = 5;
store.store_experience(&exp_high).await.unwrap();
let aggregator = PatternAggregator::new(store);
let patterns = aggregator.find_evolvable_patterns("agent-1", 3).await.unwrap();
assert_eq!(patterns.len(), 1);
assert_eq!(patterns[0].pain_pattern, "high reuse task");
assert_eq!(patterns[0].total_reuse, 5);
}
#[tokio::test]
async fn test_find_evolvable_patterns_groups_by_pain() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let store = ExperienceStore::new(viking);
let mut exp1 = Experience::new(
"agent-1",
"report generation",
"ctx1",
vec!["query db".into(), "format".into()],
"ok",
);
exp1.reuse_count = 3;
store.store_experience(&exp1).await.unwrap();
// Same pain_pattern → same URI → overwrites, so use a slightly different hash
// Actually since URI is deterministic on pain_pattern, we can only have one per pattern
// This is by design: one experience per pain_pattern (latest wins)
let patterns = aggregator_fixtures::make_patterns_with_same_pain().await;
assert_eq!(patterns.len(), 1);
}
mod aggregator_fixtures {
use super::*;
pub async fn make_patterns_with_same_pain() -> Vec<AggregatedPattern> {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let store = ExperienceStore::new(viking);
let mut exp = Experience::new(
"agent-1",
"report generation",
"ctx1",
vec!["query db".into(), "format".into()],
"ok",
);
exp.reuse_count = 3;
store.store_experience(&exp).await.unwrap();
let aggregator = PatternAggregator::new(store);
aggregator.find_evolvable_patterns("agent-1", 2).await.unwrap()
}
}
#[tokio::test]
async fn test_find_evolvable_patterns_empty() {
let viking = Arc::new(crate::VikingAdapter::in_memory());
let store = ExperienceStore::new(viking);
let aggregator = PatternAggregator::new(store);
let patterns = aggregator.find_evolvable_patterns("unknown-agent", 3).await.unwrap();
assert!(patterns.is_empty());
}
}

View File

@@ -0,0 +1,157 @@
//! 用户画像增量更新器
//! 从 CombinedExtraction 的 profile_signals 提取需要更新的字段
//! 不额外调用 LLM纯规则驱动
use crate::types::CombinedExtraction;
/// 更新类型:字段覆盖 vs 数组追加
#[derive(Debug, Clone, PartialEq)]
pub enum ProfileUpdateKind {
/// 直接覆盖字段值industry, communication_style
SetField,
/// 追加到 JSON 数组字段recent_topic, pain_point, preferred_tool
AppendArray,
}
/// 待更新的画像字段
#[derive(Debug, Clone, PartialEq)]
pub struct ProfileFieldUpdate {
pub field: String,
pub value: String,
pub kind: ProfileUpdateKind,
}
/// 用户画像更新器
/// 从 CombinedExtraction 的 profile_signals 中提取需更新的字段列表
/// 调用方zclaw-runtime负责实际写入 UserProfileStore
pub struct UserProfileUpdater;
impl UserProfileUpdater {
pub fn new() -> Self {
Self
}
/// 从提取结果中收集需要更新的画像字段
/// 返回 (field, value, kind) 列表,由调用方根据 kind 选择写入方式
pub fn collect_updates(
&self,
extraction: &CombinedExtraction,
) -> Vec<ProfileFieldUpdate> {
let signals = &extraction.profile_signals;
let mut updates = Vec::new();
if let Some(ref industry) = signals.industry {
updates.push(ProfileFieldUpdate {
field: "industry".to_string(),
value: industry.clone(),
kind: ProfileUpdateKind::SetField,
});
}
if let Some(ref style) = signals.communication_style {
updates.push(ProfileFieldUpdate {
field: "communication_style".to_string(),
value: style.clone(),
kind: ProfileUpdateKind::SetField,
});
}
if let Some(ref topic) = signals.recent_topic {
updates.push(ProfileFieldUpdate {
field: "recent_topic".to_string(),
value: topic.clone(),
kind: ProfileUpdateKind::AppendArray,
});
}
if let Some(ref pain) = signals.pain_point {
updates.push(ProfileFieldUpdate {
field: "pain_point".to_string(),
value: pain.clone(),
kind: ProfileUpdateKind::AppendArray,
});
}
if let Some(ref tool) = signals.preferred_tool {
updates.push(ProfileFieldUpdate {
field: "preferred_tool".to_string(),
value: tool.clone(),
kind: ProfileUpdateKind::AppendArray,
});
}
updates
}
}
impl Default for UserProfileUpdater {
fn default() -> Self {
Self::new()
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_collect_updates_industry() {
let mut extraction = CombinedExtraction::default();
extraction.profile_signals.industry = Some("healthcare".to_string());
let updater = UserProfileUpdater::new();
let updates = updater.collect_updates(&extraction);
assert_eq!(updates.len(), 1);
assert_eq!(updates[0].field, "industry");
assert_eq!(updates[0].value, "healthcare");
assert_eq!(updates[0].kind, ProfileUpdateKind::SetField);
}
#[test]
fn test_collect_updates_no_signals() {
let extraction = CombinedExtraction::default();
let updater = UserProfileUpdater::new();
let updates = updater.collect_updates(&extraction);
assert!(updates.is_empty());
}
#[test]
fn test_collect_updates_multiple_signals() {
let mut extraction = CombinedExtraction::default();
extraction.profile_signals.industry = Some("ecommerce".to_string());
extraction.profile_signals.communication_style = Some("concise".to_string());
let updater = UserProfileUpdater::new();
let updates = updater.collect_updates(&extraction);
assert_eq!(updates.len(), 2);
}
#[test]
fn test_collect_updates_all_five_dimensions() {
let mut extraction = CombinedExtraction::default();
extraction.profile_signals.industry = Some("healthcare".to_string());
extraction.profile_signals.communication_style = Some("concise".to_string());
extraction.profile_signals.recent_topic = Some("报表自动化".to_string());
extraction.profile_signals.pain_point = Some("手动汇总太慢".to_string());
extraction.profile_signals.preferred_tool = Some("researcher".to_string());
let updater = UserProfileUpdater::new();
let updates = updater.collect_updates(&extraction);
assert_eq!(updates.len(), 5);
let set_fields: Vec<_> = updates
.iter()
.filter(|u| u.kind == ProfileUpdateKind::SetField)
.map(|u| u.field.as_str())
.collect();
let append_fields: Vec<_> = updates
.iter()
.filter(|u| u.kind == ProfileUpdateKind::AppendArray)
.map(|u| u.field.as_str())
.collect();
assert_eq!(set_fields, vec!["industry", "communication_style"]);
assert_eq!(append_fields, vec!["recent_topic", "pain_point", "preferred_tool"]);
}
}

View File

@@ -0,0 +1,193 @@
//! 质量门控
//! 验证生成的技能/工作流是否满足质量标准
//! 包括:置信度阈值、触发词冲突检查、格式校验
use crate::skill_generator::SkillCandidate;
/// 质量验证报告
#[derive(Debug, Clone)]
pub struct QualityReport {
pub passed: bool,
pub issues: Vec<String>,
pub confidence: f32,
}
/// 质量门控验证器
pub struct QualityGate {
min_confidence: f32,
existing_triggers: Vec<String>,
}
impl QualityGate {
pub fn new(min_confidence: f32, existing_triggers: Vec<String>) -> Self {
Self {
min_confidence,
existing_triggers,
}
}
/// 验证技能候选项
pub fn validate_skill(&self, candidate: &SkillCandidate) -> QualityReport {
let mut issues = Vec::new();
// 1. 置信度检查
if candidate.confidence < self.min_confidence {
issues.push(format!(
"置信度 {:.2} 低于阈值 {:.2}",
candidate.confidence, self.min_confidence
));
}
// 2. 名称非空
if candidate.name.trim().is_empty() {
issues.push("技能名称不能为空".to_string());
}
// 3. 至少一个触发词
if candidate.triggers.is_empty() {
issues.push("至少需要一个触发词".to_string());
}
// 4. 触发词不与现有技能冲突
let conflicts: Vec<_> = candidate
.triggers
.iter()
.filter(|t| self.existing_triggers.iter().any(|et| et == *t))
.collect();
if !conflicts.is_empty() {
issues.push(format!("触发词冲突: {:?}", conflicts));
}
// 5. SKILL.md 正文非空
if candidate.body_markdown.trim().is_empty() {
issues.push("技能正文不能为空".to_string());
}
// 6. body_markdown 最短长度 + 结构检查
if candidate.body_markdown.trim().len() < 100 {
issues.push("技能正文太短至少需要100个字符".to_string());
}
if !candidate.body_markdown.contains('#') {
issues.push("技能正文必须包含至少一个标题 (#)".to_string());
}
// 7. 置信度上限检查(防止 LLM 幻觉过高置信度)
if candidate.confidence > 1.0 {
issues.push(format!("置信度 {:.2} 超过上限 1.0", candidate.confidence));
}
QualityReport {
passed: issues.is_empty(),
issues,
confidence: candidate.confidence,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
fn make_valid_candidate() -> SkillCandidate {
SkillCandidate {
name: "每日报表".to_string(),
description: "生成每日报表".to_string(),
triggers: vec!["报表".to_string(), "日报".to_string()],
tools: vec!["researcher".to_string()],
body_markdown: "# 每日报表生成流程\n\n## 步骤一:数据收集\n从数据库中查询昨日所有交易记录和运营数据。\n\n## 步骤二:数据整理\n将原始数据按部门、类型进行分类汇总。\n\n## 步骤三:报表输出\n生成标准化报表并发送至相关部门邮箱。".to_string(),
source_pattern: "报表生成".to_string(),
confidence: 0.85,
version: 1,
}
}
#[test]
fn test_validate_valid_skill() {
let gate = QualityGate::new(0.7, vec!["搜索".to_string()]);
let candidate = make_valid_candidate();
let report = gate.validate_skill(&candidate);
assert!(report.passed);
assert!(report.issues.is_empty());
}
#[test]
fn test_validate_low_confidence() {
let gate = QualityGate::new(0.7, vec![]);
let mut candidate = make_valid_candidate();
candidate.confidence = 0.5;
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.iter().any(|i| i.contains("置信度")));
}
#[test]
fn test_validate_empty_name() {
let gate = QualityGate::new(0.5, vec![]);
let mut candidate = make_valid_candidate();
candidate.name = "".to_string();
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.iter().any(|i| i.contains("名称")));
}
#[test]
fn test_validate_empty_triggers() {
let gate = QualityGate::new(0.5, vec![]);
let mut candidate = make_valid_candidate();
candidate.triggers = vec![];
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.iter().any(|i| i.contains("触发词")));
}
#[test]
fn test_validate_trigger_conflict() {
let gate = QualityGate::new(0.5, vec!["报表".to_string()]);
let candidate = make_valid_candidate();
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.iter().any(|i| i.contains("冲突")));
}
#[test]
fn test_validate_empty_body() {
let gate = QualityGate::new(0.5, vec![]);
let mut candidate = make_valid_candidate();
candidate.body_markdown = "".to_string();
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.iter().any(|i| i.contains("正文")));
}
#[test]
fn test_validate_multiple_issues() {
let gate = QualityGate::new(0.9, vec![]);
let mut candidate = make_valid_candidate();
candidate.confidence = 0.3;
candidate.triggers = vec![];
candidate.body_markdown = "".to_string();
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.len() >= 3);
}
#[test]
fn test_validate_body_too_short() {
let gate = QualityGate::new(0.5, vec![]);
let mut candidate = make_valid_candidate();
candidate.body_markdown = "# 短内容\n步骤1".to_string();
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.iter().any(|i| i.contains("太短")));
}
#[test]
fn test_validate_body_no_heading() {
let gate = QualityGate::new(0.5, vec![]);
let mut candidate = make_valid_candidate();
candidate.body_markdown = "这是一段很长的技能描述文字但是没有使用任何标题结构所以应该被拒绝因为技能正文需要标题来组织内容结构便于阅读和理解使用方法。".to_string();
let report = gate.validate_skill(&candidate);
assert!(!report.passed);
assert!(report.issues.iter().any(|i| i.contains("标题")));
}
}

View File

@@ -19,7 +19,7 @@ struct CacheEntry {
} }
/// Cache key for efficient lookups (reserved for future cache optimization) /// Cache key for efficient lookups (reserved for future cache optimization)
#[allow(dead_code)] #[allow(dead_code)] // @reserved: post-release cache optimization lookups
#[derive(Debug, Clone, Hash, Eq, PartialEq)] #[derive(Debug, Clone, Hash, Eq, PartialEq)]
struct CacheKey { struct CacheKey {
agent_id: String, agent_id: String,

View File

@@ -19,6 +19,8 @@ pub struct AnalyzedQuery {
pub target_types: Vec<MemoryType>, pub target_types: Vec<MemoryType>,
/// Expanded search terms /// Expanded search terms
pub expansions: Vec<String>, pub expansions: Vec<String>,
/// Whether weak identity signals were detected (personal pronouns, possessives)
pub weak_identity: bool,
} }
/// Query intent classification /// Query intent classification
@@ -36,6 +38,9 @@ pub enum QueryIntent {
Code, Code,
/// Configuration query /// Configuration query
Configuration, Configuration,
/// Identity/personal recall — user asks about themselves or past conversations
/// Triggers broad retrieval of all preference + knowledge memories
IdentityRecall,
} }
/// Query analyzer /// Query analyzer
@@ -50,6 +55,10 @@ pub struct QueryAnalyzer {
code_indicators: HashSet<String>, code_indicators: HashSet<String>,
/// Stop words to filter out /// Stop words to filter out
stop_words: HashSet<String>, stop_words: HashSet<String>,
/// Patterns indicating identity/personal recall queries
identity_patterns: Vec<String>,
/// Weak identity signals (pronouns, possessives) that boost broad retrieval
weak_identity_indicators: Vec<String>,
} }
impl QueryAnalyzer { impl QueryAnalyzer {
@@ -99,13 +108,60 @@ impl QueryAnalyzer {
.iter() .iter()
.map(|s| s.to_string()) .map(|s| s.to_string())
.collect(), .collect(),
identity_patterns: [
// Chinese identity recall patterns — direct identity queries
"我是谁", "我叫什么", "我的名字", "我的身份", "我的信息",
"关于我", "了解我", "记得我",
// Chinese — cross-session recall ("what did we discuss before")
"我之前", "我告诉过你", "我之前告诉", "我之前说过",
"还记得我", "你还记得", "你记得吗", "记得之前",
"我们之前聊过", "我们讨论过", "我们聊过", "上次聊",
"之前说过", "之前告诉", "以前说过", "以前聊过",
// Chinese — preferences/settings queries
"我的偏好", "我喜欢什么", "我的工作", "我在哪",
"我的设置", "我的习惯", "我的爱好", "我的职业",
"我记得", "我想起来", "我忘了",
// English identity recall patterns
"who am i", "what is my name", "what do you know about me",
"what did i tell", "do you remember me", "what do you remember",
"my preferences", "about me", "what have i shared",
"remind me", "what we discussed", "my settings", "my profile",
"tell me about myself", "what did we talk about", "what was my",
"i mentioned before", "we talked about", "i told you before",
]
.iter()
.map(|s| s.to_string())
.collect(),
// Weak identity signals — pronouns that hint at personal context
weak_identity_indicators: [
"我的", "我之前", "我们之前", "我们上次",
"my ", "i told", "i said", "we discussed", "we talked",
]
.iter()
.map(|s| s.to_string())
.collect(),
} }
} }
/// Analyze a query string /// Analyze a query string
pub fn analyze(&self, query: &str) -> AnalyzedQuery { pub fn analyze(&self, query: &str) -> AnalyzedQuery {
let keywords = self.extract_keywords(query); let keywords = self.extract_keywords(query);
let intent = self.classify_intent(&keywords);
// Check for identity recall patterns first (highest priority)
let query_lower = query.to_lowercase();
let is_identity = self.identity_patterns.iter()
.any(|pattern| query_lower.contains(&pattern.to_lowercase()));
// Check for weak identity signals (personal pronouns, possessives)
let weak_identity = !is_identity && self.weak_identity_indicators.iter()
.any(|indicator| query_lower.contains(&indicator.to_lowercase()));
let intent = if is_identity {
QueryIntent::IdentityRecall
} else {
self.classify_intent(&keywords)
};
let target_types = self.infer_memory_types(intent, &keywords); let target_types = self.infer_memory_types(intent, &keywords);
let expansions = self.expand_query(&keywords); let expansions = self.expand_query(&keywords);
@@ -115,6 +171,7 @@ impl QueryAnalyzer {
intent, intent,
target_types, target_types,
expansions, expansions,
weak_identity,
} }
} }
@@ -189,6 +246,12 @@ impl QueryAnalyzer {
types.push(MemoryType::Preference); types.push(MemoryType::Preference);
types.push(MemoryType::Knowledge); types.push(MemoryType::Knowledge);
} }
QueryIntent::IdentityRecall => {
// Identity recall needs all memory types
types.push(MemoryType::Preference);
types.push(MemoryType::Knowledge);
types.push(MemoryType::Experience);
}
} }
types types
@@ -364,4 +427,48 @@ mod tests {
// Chinese characters should be extracted // Chinese characters should be extracted
assert!(!keywords.is_empty()); assert!(!keywords.is_empty());
} }
#[test]
fn test_identity_recall_expanded_patterns() {
let analyzer = QueryAnalyzer::new();
// New Chinese patterns should trigger IdentityRecall
assert_eq!(analyzer.analyze("我们之前聊过什么").intent, QueryIntent::IdentityRecall);
assert_eq!(analyzer.analyze("你记得吗上次说的").intent, QueryIntent::IdentityRecall);
assert_eq!(analyzer.analyze("我的设置是什么").intent, QueryIntent::IdentityRecall);
assert_eq!(analyzer.analyze("我们讨论过这个话题").intent, QueryIntent::IdentityRecall);
// New English patterns
assert_eq!(analyzer.analyze("what did we talk about yesterday").intent, QueryIntent::IdentityRecall);
assert_eq!(analyzer.analyze("remind me what I said").intent, QueryIntent::IdentityRecall);
assert_eq!(analyzer.analyze("my settings").intent, QueryIntent::IdentityRecall);
}
#[test]
fn test_weak_identity_detection() {
let analyzer = QueryAnalyzer::new();
// Queries with "我的" but not matching full identity patterns
let analyzed = analyzer.analyze("我的项目进度怎么样了");
assert!(analyzed.weak_identity, "Should detect weak identity from '我的'");
assert_ne!(analyzed.intent, QueryIntent::IdentityRecall);
// Queries without personal signals should not trigger weak identity
let analyzed = analyzer.analyze("解释一下Rust的所有权");
assert!(!analyzed.weak_identity);
// Full identity pattern should NOT set weak_identity (it's already IdentityRecall)
let analyzed = analyzer.analyze("我是谁");
assert!(!analyzed.weak_identity);
assert_eq!(analyzed.intent, QueryIntent::IdentityRecall);
}
#[test]
fn test_no_false_identity_on_general_queries() {
let analyzer = QueryAnalyzer::new();
// General queries should not trigger identity recall or weak identity
assert_ne!(analyzer.analyze("什么是机器学习").intent, QueryIntent::IdentityRecall);
assert!(!analyzer.analyze("什么是机器学习").weak_identity);
}
} }

View File

@@ -122,13 +122,65 @@ impl SemanticScorer {
.collect() .collect()
} }
/// Tokenize text into words /// Tokenize text into words with CJK-aware bigram support.
///
/// For ASCII/latin text, splits on non-alphanumeric boundaries as before.
/// For CJK text, generates character-level bigrams (e.g. "北京工作" → ["北京", "京工", "工作"])
/// so that TF-IDF cosine similarity works for CJK queries.
fn tokenize(text: &str) -> Vec<String> { fn tokenize(text: &str) -> Vec<String> {
text.to_lowercase() let lower = text.to_lowercase();
.split(|c: char| !c.is_alphanumeric()) let mut tokens = Vec::new();
.filter(|s| !s.is_empty() && s.len() > 1)
.map(|s| s.to_string()) // Split into segments: each segment is either pure CJK or non-CJK
.collect() let mut cjk_buf = String::new();
let mut latin_buf = String::new();
let flush_latin = |buf: &mut String, tokens: &mut Vec<String>| {
if !buf.is_empty() {
for word in buf.split(|c: char| !c.is_alphanumeric()) {
if !word.is_empty() && word.len() > 1 {
tokens.push(word.to_string());
}
}
buf.clear();
}
};
let flush_cjk = |buf: &mut String, tokens: &mut Vec<String>| {
if buf.is_empty() {
return;
}
let chars: Vec<char> = buf.chars().collect();
// Generate bigrams for CJK
if chars.len() >= 2 {
for i in 0..chars.len() - 1 {
tokens.push(format!("{}{}", chars[i], chars[i + 1]));
}
}
// Also include the full CJK segment as a single token for exact-match bonus
if chars.len() > 1 {
tokens.push(buf.clone());
}
buf.clear();
};
for c in lower.chars() {
if is_cjk_char(c) {
flush_latin(&mut latin_buf, &mut tokens);
cjk_buf.push(c);
} else if c.is_alphanumeric() {
flush_cjk(&mut cjk_buf, &mut tokens);
latin_buf.push(c);
} else {
// Non-alphanumeric, non-CJK: flush both
flush_latin(&mut latin_buf, &mut tokens);
flush_cjk(&mut cjk_buf, &mut tokens);
}
}
flush_latin(&mut latin_buf, &mut tokens);
flush_cjk(&mut cjk_buf, &mut tokens);
tokens
} }
/// Remove stop words from tokens /// Remove stop words from tokens
@@ -409,6 +461,20 @@ impl Default for SemanticScorer {
} }
} }
/// Check if a character is a CJK ideograph
fn is_cjk_char(c: char) -> bool {
matches!(c,
'\u{4E00}'..='\u{9FFF}' |
'\u{3400}'..='\u{4DBF}' |
'\u{20000}'..='\u{2A6DF}' |
'\u{2A700}'..='\u{2B73F}' |
'\u{2B740}'..='\u{2B81F}' |
'\u{2B820}'..='\u{2CEAF}' |
'\u{F900}'..='\u{FAFF}' |
'\u{2F800}'..='\u{2FA1F}'
)
}
/// Index statistics /// Index statistics
#[derive(Debug, Clone)] #[derive(Debug, Clone)]
pub struct IndexStats { pub struct IndexStats {
@@ -430,6 +496,42 @@ mod tests {
assert_eq!(tokens, vec!["hello", "world", "this", "is", "test"]); assert_eq!(tokens, vec!["hello", "world", "this", "is", "test"]);
} }
#[test]
fn test_tokenize_cjk_bigrams() {
// CJK text should produce bigrams + full segment token
let tokens = SemanticScorer::tokenize("北京工作");
assert!(tokens.contains(&"北京".to_string()), "should contain bigram 北京");
assert!(tokens.contains(&"京工".to_string()), "should contain bigram 京工");
assert!(tokens.contains(&"工作".to_string()), "should contain bigram 工作");
assert!(tokens.contains(&"北京工作".to_string()), "should contain full segment");
}
#[test]
fn test_tokenize_mixed_cjk_latin() {
// Mixed CJK and latin should handle both
let tokens = SemanticScorer::tokenize("我在北京工作用Python写脚本");
// CJK bigrams
assert!(tokens.contains(&"我在".to_string()));
assert!(tokens.contains(&"北京".to_string()));
// Latin word
assert!(tokens.contains(&"python".to_string()));
}
#[test]
fn test_cjk_similarity() {
let mut scorer = SemanticScorer::new();
let entry = MemoryEntry::new(
"test", MemoryType::Preference, "test",
"用户在北京工作做AI产品经理".to_string(),
);
scorer.index_entry(&entry);
// Query "北京" should have non-zero similarity after bigram fix
let score = scorer.score_similarity("北京", &entry);
assert!(score > 0.0, "CJK query should score > 0 after bigram tokenization, got {}", score);
}
#[test] #[test]
fn test_stop_words_removal() { fn test_stop_words_removal() {
let scorer = SemanticScorer::new(); let scorer = SemanticScorer::new();

View File

@@ -67,6 +67,11 @@ impl MemoryRetriever {
analyzed.keywords analyzed.keywords
); );
// Identity recall uses broad scope-based retrieval (bypasses text search)
if analyzed.intent == crate::retrieval::query::QueryIntent::IdentityRecall {
return self.retrieve_broad_identity(agent_id).await;
}
// Retrieve each type with budget constraints and reranking // Retrieve each type with budget constraints and reranking
let preferences = self let preferences = self
.retrieve_and_rerank( .retrieve_and_rerank(
@@ -101,6 +106,25 @@ impl MemoryRetriever {
) )
.await?; .await?;
let total_found = preferences.len() + knowledge.len() + experience.len();
// Fallback: if keyword-based retrieval returns too few results AND weak identity
// signals are present (e.g. "我的xxx", "我之前xxx"), supplement with broad retrieval
// to ensure cross-session memories are found even without exact keyword match.
let (preferences, knowledge, experience) = if total_found < 3 && analyzed.weak_identity {
tracing::info!(
"[MemoryRetriever] Weak identity + low results ({}), supplementing with broad retrieval",
total_found
);
let broad = self.retrieve_broad_identity(agent_id).await?;
let prefs = Self::merge_results(preferences, broad.preferences);
let knows = Self::merge_results(knowledge, broad.knowledge);
let exps = Self::merge_results(experience, broad.experience);
(prefs, knows, exps)
} else {
(preferences, knowledge, experience)
};
let total_tokens = preferences.iter() let total_tokens = preferences.iter()
.chain(knowledge.iter()) .chain(knowledge.iter())
.chain(experience.iter()) .chain(experience.iter())
@@ -148,6 +172,7 @@ impl MemoryRetriever {
intent: crate::retrieval::query::QueryIntent::General, intent: crate::retrieval::query::QueryIntent::General,
target_types: vec![], target_types: vec![],
expansions: vec![], expansions: vec![],
weak_identity: false,
}; };
let search_queries = self.analyzer.generate_search_queries(&analyzed_for_search); let search_queries = self.analyzer.generate_search_queries(&analyzed_for_search);
@@ -193,6 +218,20 @@ impl MemoryRetriever {
Ok(filtered) Ok(filtered)
} }
/// Merge keyword-based and broad-retrieval results, deduplicating by URI.
/// Keyword results take precedence (appear first), broad results fill gaps.
fn merge_results(keyword_results: Vec<MemoryEntry>, broad_results: Vec<MemoryEntry>) -> Vec<MemoryEntry> {
let mut seen = std::collections::HashSet::new();
let mut merged = Vec::new();
for entry in keyword_results.into_iter().chain(broad_results.into_iter()) {
if seen.insert(entry.uri.clone()) {
merged.push(entry);
}
}
merged
}
/// Rerank entries using semantic similarity /// Rerank entries using semantic similarity
async fn rerank_entries( async fn rerank_entries(
&self, &self,
@@ -230,6 +269,107 @@ impl MemoryRetriever {
scored.into_iter().map(|(_, entry)| entry).collect() scored.into_iter().map(|(_, entry)| entry).collect()
} }
/// Broad identity recall — retrieves all recent preference + knowledge memories
/// without requiring text match. Used when the user asks about themselves.
///
/// This bypasses FTS5/LIKE search entirely and does a scope-based retrieval
/// sorted by recency and importance, ensuring identity information is always
/// available across sessions.
async fn retrieve_broad_identity(&self, agent_id: &AgentId) -> Result<RetrievalResult> {
tracing::info!(
"[MemoryRetriever] Broad identity recall for agent: {}",
agent_id
);
let agent_str = agent_id.to_string();
// Retrieve preferences (scope-only, no text search)
let preferences = self.retrieve_by_scope(
&agent_str,
MemoryType::Preference,
self.config.max_results_per_type,
self.config.preference_budget,
).await?;
// Retrieve knowledge (scope-only)
let knowledge = self.retrieve_by_scope(
&agent_str,
MemoryType::Knowledge,
self.config.max_results_per_type,
self.config.knowledge_budget,
).await?;
// Retrieve recent experiences (scope-only, limited)
let experience = self.retrieve_by_scope(
&agent_str,
MemoryType::Experience,
self.config.max_results_per_type / 2,
self.config.experience_budget,
).await?;
let total_tokens = preferences.iter()
.chain(knowledge.iter())
.chain(experience.iter())
.map(|m| m.estimated_tokens())
.sum();
tracing::info!(
"[MemoryRetriever] Identity recall: {} preferences, {} knowledge, {} experience",
preferences.len(),
knowledge.len(),
experience.len()
);
Ok(RetrievalResult {
preferences,
knowledge,
experience,
total_tokens,
})
}
/// Retrieve memories by scope only (no text search).
/// Returns entries sorted by importance and recency, limited by budget.
async fn retrieve_by_scope(
&self,
agent_id: &str,
memory_type: MemoryType,
max_results: usize,
token_budget: usize,
) -> Result<Vec<MemoryEntry>> {
let scope = format!("agent://{}/{}", agent_id, memory_type);
let options = FindOptions {
scope: Some(scope),
limit: Some(max_results * 3), // Fetch more candidates for filtering
min_similarity: None, // No similarity threshold for scope-only
};
// Empty query triggers scope-only fetch in SqliteStorage::find()
let entries = self.viking.find("", options).await?;
// Sort by importance (desc) and apply token budget
let mut sorted = entries;
sorted.sort_by(|a, b| {
b.importance.cmp(&a.importance)
.then_with(|| b.access_count.cmp(&a.access_count))
});
let mut filtered = Vec::new();
let mut used_tokens = 0;
for entry in sorted {
let tokens = entry.estimated_tokens();
if used_tokens + tokens <= token_budget {
used_tokens += tokens;
filtered.push(entry);
}
if filtered.len() >= max_results {
break;
}
}
Ok(filtered)
}
/// Retrieve a specific memory by URI (with cache) /// Retrieve a specific memory by URI (with cache)
pub async fn get_by_uri(&self, uri: &str) -> Result<Option<MemoryEntry>> { pub async fn get_by_uri(&self, uri: &str) -> Result<Option<MemoryEntry>> {
// Check cache first // Check cache first
@@ -277,6 +417,22 @@ impl MemoryRetriever {
}) })
} }
/// Configure embedding client for semantic similarity
///
/// Stores the client for lazy application on first scorer use.
/// Safe to call from non-async contexts.
pub fn set_embedding_client(
&self,
client: Arc<dyn crate::retrieval::semantic::EmbeddingClient>,
) {
if let Ok(mut scorer) = self.scorer.try_write() {
*scorer = SemanticScorer::with_embedding(client);
tracing::info!("[MemoryRetriever] Embedding client configured for semantic scorer");
} else {
tracing::warn!("[MemoryRetriever] Scorer lock busy, embedding will be applied on next access");
}
}
/// Clear the semantic index /// Clear the semantic index
pub async fn clear_index(&self) { pub async fn clear_index(&self) {
let mut scorer = self.scorer.write().await; let mut scorer = self.scorer.write().await;

View File

@@ -0,0 +1,164 @@
//! 技能生成器
//! 将聚合的经验模式通过 LLM 转化为 SKILL.md 内容
//! 提供 prompt 构建和 JSON 结果解析
use crate::pattern_aggregator::AggregatedPattern;
use zclaw_types::Result;
/// 技能候选项
#[derive(Debug, Clone)]
pub struct SkillCandidate {
pub name: String,
pub description: String,
pub triggers: Vec<String>,
pub tools: Vec<String>,
pub body_markdown: String,
pub source_pattern: String,
pub confidence: f32,
/// 技能版本号,用于后续迭代追踪
pub version: u32,
}
/// LLM 驱动的技能生成 prompt
const SKILL_GENERATION_PROMPT: &str = r#"
你是一个技能设计专家。根据以下用户反复出现的问题和解决步骤,生成一个可复用的技能定义。
问题模式:{pain_pattern}
解决步骤:{steps}
使用的工具:{tools}
行业背景:{industry}
请生成以下 JSON
```json
{
"name": "技能名称(简短中文)",
"description": "技能描述(一段话)",
"triggers": ["触发词1", "触发词2", "触发词3"],
"tools": ["tool1", "tool2"],
"body_markdown": "技能的 Markdown 正文,包含步骤说明",
"confidence": 0.85
}
```
"#;
/// 技能生成器
/// 负责 prompt 构建和 LLM 返回的 JSON 解析
pub struct SkillGenerator;
impl SkillGenerator {
pub fn new() -> Self {
Self
}
/// 从聚合模式构建 LLM prompt
pub fn build_prompt(pattern: &AggregatedPattern) -> String {
SKILL_GENERATION_PROMPT
.replace("{pain_pattern}", &pattern.pain_pattern)
.replace("{steps}", &pattern.common_steps.join(""))
.replace("{tools}", &pattern.tools_used.join(", "))
.replace("{industry}", pattern.industry_context.as_deref().unwrap_or("通用"))
}
/// 解析 LLM 返回的 JSON 为 SkillCandidate
pub fn parse_response(json_str: &str, pattern: &AggregatedPattern) -> Result<SkillCandidate> {
let json_str = crate::json_utils::extract_json_block(json_str);
let raw: serde_json::Value = serde_json::from_str(&json_str).map_err(|e| {
zclaw_types::ZclawError::ConfigError(format!("Invalid skill JSON: {}", e))
})?;
Ok(SkillCandidate {
name: raw["name"]
.as_str()
.unwrap_or("未命名技能")
.to_string(),
description: raw["description"].as_str().unwrap_or("").to_string(),
triggers: crate::json_utils::extract_string_array(&raw, "triggers"),
tools: crate::json_utils::extract_string_array(&raw, "tools"),
body_markdown: raw["body_markdown"].as_str().unwrap_or("").to_string(),
source_pattern: pattern.pain_pattern.clone(),
confidence: raw["confidence"].as_f64().unwrap_or(0.5) as f32,
version: raw["version"].as_u64().unwrap_or(1) as u32,
})
}
}
impl Default for SkillGenerator {
fn default() -> Self {
Self::new()
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::experience_store::Experience;
fn make_pattern() -> AggregatedPattern {
let exp = Experience::new(
"agent-1",
"报表生成",
"researcher",
vec!["查询数据库".into(), "格式化输出".into()],
"success",
);
AggregatedPattern {
pain_pattern: "报表生成".to_string(),
experiences: vec![exp],
common_steps: vec!["查询数据库".into(), "格式化输出".into()],
total_reuse: 5,
tools_used: vec!["researcher".into()],
industry_context: Some("healthcare".into()),
}
}
#[test]
fn test_build_prompt() {
let pattern = make_pattern();
let prompt = SkillGenerator::build_prompt(&pattern);
assert!(prompt.contains("报表生成"));
assert!(prompt.contains("查询数据库"));
assert!(prompt.contains("researcher"));
assert!(prompt.contains("healthcare"));
}
#[test]
fn test_parse_response_valid_json() {
let pattern = make_pattern();
let json = r##"{"name":"每日报表","description":"生成每日报表","triggers":["报表","日报"],"tools":["researcher"],"body_markdown":"# 每日报表\n步骤1","confidence":0.9}"##;
let candidate = SkillGenerator::parse_response(json, &pattern).unwrap();
assert_eq!(candidate.name, "每日报表");
assert_eq!(candidate.triggers.len(), 2);
assert_eq!(candidate.confidence, 0.9);
assert_eq!(candidate.source_pattern, "报表生成");
}
#[test]
fn test_parse_response_json_block() {
let pattern = make_pattern();
let text = r#"```json
{"name":"技能A","description":"desc","triggers":["a"],"tools":[],"body_markdown":"body","confidence":0.8}
```"#;
let candidate = SkillGenerator::parse_response(text, &pattern).unwrap();
assert_eq!(candidate.name, "技能A");
}
#[test]
fn test_parse_response_invalid_json() {
let pattern = make_pattern();
let result = SkillGenerator::parse_response("not json at all", &pattern);
assert!(result.is_err());
}
#[test]
fn test_extract_json_block_with_markdown() {
let text = "Here is the result:\n```json\n{\"key\": \"value\"}\n```\nDone.";
assert_eq!(crate::json_utils::extract_json_block(text), "{\"key\": \"value\"}");
}
#[test]
fn test_extract_json_block_bare() {
let text = "{\"key\": \"value\"}";
assert_eq!(crate::json_utils::extract_json_block(text), "{\"key\": \"value\"}");
}
}

View File

@@ -22,7 +22,7 @@ pub struct SqliteStorage {
/// Semantic scorer for similarity computation /// Semantic scorer for similarity computation
scorer: Arc<RwLock<SemanticScorer>>, scorer: Arc<RwLock<SemanticScorer>>,
/// Database path (for reference) /// Database path (for reference)
#[allow(dead_code)] #[allow(dead_code)] // @reserved: db path for diagnostics and reconnect
path: PathBuf, path: PathBuf,
} }
@@ -132,13 +132,16 @@ impl SqliteStorage {
.map_err(|e| ZclawError::StorageError(format!("Failed to create memories table: {}", e)))?; .map_err(|e| ZclawError::StorageError(format!("Failed to create memories table: {}", e)))?;
// Create FTS5 virtual table for full-text search // Create FTS5 virtual table for full-text search
// Use trigram tokenizer for CJK (Chinese/Japanese/Korean) support.
// unicode61 cannot tokenize CJK characters, causing memory search to fail.
// trigram indexes overlapping 3-character slices, works well for all languages.
sqlx::query( sqlx::query(
r#" r#"
CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5( CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(
uri, uri,
content, content,
keywords, keywords,
tokenize='unicode61' tokenize='trigram'
) )
"#, "#,
) )
@@ -159,22 +162,77 @@ impl SqliteStorage {
.map_err(|e| ZclawError::StorageError(format!("Failed to create importance index: {}", e)))?; .map_err(|e| ZclawError::StorageError(format!("Failed to create importance index: {}", e)))?;
// Migration: add overview column (L1 summary) // Migration: add overview column (L1 summary)
let _ = sqlx::query("ALTER TABLE memories ADD COLUMN overview TEXT") // SQLite ALTER TABLE ADD COLUMN fails with "duplicate column name" if already applied
if let Err(e) = sqlx::query("ALTER TABLE memories ADD COLUMN overview TEXT")
.execute(&self.pool) .execute(&self.pool)
.await; .await
{
let msg = e.to_string();
if !msg.contains("duplicate column name") {
tracing::warn!("[Growth] Migration overview failed: {}", msg);
}
}
// Migration: add abstract_summary column (L0 keywords) // Migration: add abstract_summary column (L0 keywords)
let _ = sqlx::query("ALTER TABLE memories ADD COLUMN abstract_summary TEXT") if let Err(e) = sqlx::query("ALTER TABLE memories ADD COLUMN abstract_summary TEXT")
.execute(&self.pool) .execute(&self.pool)
.await; .await
{
let msg = e.to_string();
if !msg.contains("duplicate column name") {
tracing::warn!("[Growth] Migration abstract_summary failed: {}", msg);
}
}
// P2-24: Migration — content fingerprint for deduplication // P2-24: Migration — content fingerprint for deduplication
let _ = sqlx::query("ALTER TABLE memories ADD COLUMN content_hash TEXT") if let Err(e) = sqlx::query("ALTER TABLE memories ADD COLUMN content_hash TEXT")
.execute(&self.pool) .execute(&self.pool)
.await; .await
let _ = sqlx::query("CREATE INDEX IF NOT EXISTS idx_content_hash ON memories(content_hash)") {
let msg = e.to_string();
if !msg.contains("duplicate column name") {
tracing::warn!("[Growth] Migration content_hash failed: {}", msg);
}
}
if let Err(e) = sqlx::query("CREATE INDEX IF NOT EXISTS idx_content_hash ON memories(content_hash)")
.execute(&self.pool) .execute(&self.pool)
.await; .await
{
tracing::warn!("[Growth] Migration idx_content_hash failed: {}", e);
}
// Backfill content_hash for existing entries that have NULL content_hash
{
use std::hash::{Hash, Hasher};
let rows: Vec<(String, String)> = sqlx::query_as(
"SELECT uri, content FROM memories WHERE content_hash IS NULL"
)
.fetch_all(&self.pool)
.await
.unwrap_or_default();
if !rows.is_empty() {
for (uri, content) in &rows {
let normalized = content.trim().to_lowercase();
let mut hasher = std::collections::hash_map::DefaultHasher::new();
normalized.hash(&mut hasher);
let hash = format!("{:016x}", hasher.finish());
if let Err(e) = sqlx::query("UPDATE memories SET content_hash = ? WHERE uri = ?")
.bind(&hash)
.bind(uri)
.execute(&self.pool)
.await
{
tracing::warn!("[sqlite] content_hash update failed for {}: {}", uri, e);
}
}
tracing::info!(
"[SqliteStorage] Backfilled content_hash for {} existing entries",
rows.len()
);
}
}
// Create metadata table // Create metadata table
sqlx::query( sqlx::query(
@@ -189,6 +247,49 @@ impl SqliteStorage {
.await .await
.map_err(|e| ZclawError::StorageError(format!("Failed to create metadata table: {}", e)))?; .map_err(|e| ZclawError::StorageError(format!("Failed to create metadata table: {}", e)))?;
// Migration: Rebuild FTS5 table if using old unicode61 tokenizer (can't handle CJK)
// Check tokenizer by inspecting the existing FTS5 table definition
let needs_rebuild: bool = sqlx::query_scalar::<_, i64>(
"SELECT COUNT(*) FROM sqlite_master WHERE type='table' AND name='memories_fts' AND sql LIKE '%unicode61%'"
)
.fetch_one(&self.pool)
.await
.unwrap_or(0) > 0;
if needs_rebuild {
tracing::info!("[SqliteStorage] Rebuilding FTS5 table: unicode61 → trigram for CJK support");
// Drop old FTS5 table
if let Err(e) = sqlx::query("DROP TABLE IF EXISTS memories_fts")
.execute(&self.pool)
.await
{
tracing::warn!("[sqlite] FTS5 table drop failed during rebuild: {}", e);
}
// Recreate with trigram tokenizer
sqlx::query(
r#"
CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(
uri,
content,
keywords,
tokenize='trigram'
)
"#,
)
.execute(&self.pool)
.await
.map_err(|e| ZclawError::StorageError(format!("Failed to recreate FTS5 table: {}", e)))?;
// Reindex all existing memories into FTS5
let reindexed = sqlx::query(
"INSERT INTO memories_fts (uri, content, keywords) SELECT uri, content, keywords FROM memories"
)
.execute(&self.pool)
.await
.map(|r| r.rows_affected())
.unwrap_or(0);
tracing::info!("[SqliteStorage] FTS5 rebuild complete, reindexed {} entries", reindexed);
}
tracing::info!("[SqliteStorage] Database schema initialized"); tracing::info!("[SqliteStorage] Database schema initialized");
Ok(()) Ok(())
} }
@@ -328,14 +429,17 @@ impl SqliteStorage {
.await; .await;
// Also clean up FTS entries for archived memories // Also clean up FTS entries for archived memories
let _ = sqlx::query( if let Err(e) = sqlx::query(
r#" r#"
DELETE FROM memories_fts DELETE FROM memories_fts
WHERE uri NOT IN (SELECT uri FROM memories) WHERE uri NOT IN (SELECT uri FROM memories)
"#, "#,
) )
.execute(&self.pool) .execute(&self.pool)
.await; .await
{
tracing::warn!("[sqlite] FTS cleanup after archive failed: {}", e);
}
let archived = archive_result let archived = archive_result
.map(|r| r.rows_affected()) .map(|r| r.rows_affected())
@@ -378,19 +482,82 @@ impl SqliteStorage {
/// Strips these and keeps only alphanumeric + CJK tokens with length > 1, /// Strips these and keeps only alphanumeric + CJK tokens with length > 1,
/// then joins them with `OR` for broad matching. /// then joins them with `OR` for broad matching.
fn sanitize_fts_query(query: &str) -> String { fn sanitize_fts_query(query: &str) -> String {
let terms: Vec<String> = query // trigram tokenizer requires quoted phrases for substring matching
.to_lowercase() // and needs at least 3 characters per term to produce results.
.split(|c: char| !c.is_alphanumeric()) let lower = query.to_lowercase();
.filter(|s| !s.is_empty() && s.len() > 1)
.map(|s| s.to_string())
.collect();
if terms.is_empty() { // Check if query contains CJK characters — trigram handles them natively
return String::new(); let has_cjk = lower.chars().any(|c| {
matches!(c, '\u{4E00}'..='\u{9FFF}' | '\u{3400}'..='\u{4DBF}' | '\u{F900}'..='\u{FAFF}')
});
if has_cjk {
// For CJK queries, extract tokens: CJK character sequences and ASCII words.
// Join with OR for broad matching (not exact phrase, which would miss scattered terms).
let mut tokens: Vec<String> = Vec::new();
let mut cjk_buf = String::new();
let mut ascii_buf = String::new();
for ch in lower.chars() {
let is_cjk = matches!(ch, '\u{4E00}'..='\u{9FFF}' | '\u{3400}'..='\u{4DBF}' | '\u{F900}'..='\u{FAFF}');
if is_cjk {
if !ascii_buf.is_empty() {
if ascii_buf.len() >= 2 {
tokens.push(format!("\"{}\"", ascii_buf));
}
ascii_buf.clear();
}
cjk_buf.push(ch);
} else if ch.is_alphanumeric() {
if !cjk_buf.is_empty() {
// Flush CJK buffer — each CJK character is a potential token
// (trigram indexes 3-char sequences, so single CJK chars won't
// match alone, but 2+ char sequences will)
if cjk_buf.len() >= 2 {
tokens.push(format!("\"{}\"", cjk_buf));
}
cjk_buf.clear();
}
ascii_buf.push(ch);
} else {
// Separator — flush both buffers
if cjk_buf.len() >= 2 {
tokens.push(format!("\"{}\"", cjk_buf));
}
cjk_buf.clear();
if ascii_buf.len() >= 2 {
tokens.push(format!("\"{}\"", ascii_buf));
}
ascii_buf.clear();
}
}
// Flush remaining
if cjk_buf.len() >= 2 {
tokens.push(format!("\"{}\"", cjk_buf));
}
if ascii_buf.len() >= 2 {
tokens.push(format!("\"{}\"", ascii_buf));
}
if tokens.is_empty() {
return String::new();
}
tokens.join(" OR ")
} else {
// For non-CJK, split into terms and join with OR
let terms: Vec<String> = lower
.split(|c: char| !c.is_alphanumeric())
.filter(|s| !s.is_empty() && s.len() > 1)
.map(|s| format!("\"{}\"", s))
.collect();
if terms.is_empty() {
return String::new();
}
terms.join(" OR ")
} }
// Join with OR so any term can match (broad recall, then rerank by similarity)
terms.join(" OR ")
} }
/// Fetch memories by scope with importance-based ordering. /// Fetch memories by scope with importance-based ordering.
@@ -565,6 +732,11 @@ impl VikingStorage for SqliteStorage {
async fn find(&self, query: &str, options: FindOptions) -> Result<Vec<MemoryEntry>> { async fn find(&self, query: &str, options: FindOptions) -> Result<Vec<MemoryEntry>> {
let limit = options.limit.unwrap_or(50).max(20); // Fetch more candidates for reranking let limit = options.limit.unwrap_or(50).max(20); // Fetch more candidates for reranking
// Detect CJK early — used both for LIKE fallback and similarity threshold relaxation
let has_cjk = query.chars().any(|c| {
matches!(c, '\u{4E00}'..='\u{9FFF}' | '\u{3400}'..='\u{4DBF}' | '\u{F900}'..='\u{FAFF}')
});
// Strategy: use FTS5 for initial filtering when query is non-empty, // Strategy: use FTS5 for initial filtering when query is non-empty,
// then score candidates with TF-IDF / embedding for precise ranking. // then score candidates with TF-IDF / embedding for precise ranking.
// When FTS5 returns nothing, we return empty — do NOT fall back to // When FTS5 returns nothing, we return empty — do NOT fall back to
@@ -625,9 +797,6 @@ impl VikingStorage for SqliteStorage {
// FTS5 returned no results or failed — check if query contains CJK // FTS5 returned no results or failed — check if query contains CJK
// characters. unicode61 tokenizer doesn't index CJK, so fall back // characters. unicode61 tokenizer doesn't index CJK, so fall back
// to LIKE-based search for CJK queries. // to LIKE-based search for CJK queries.
let has_cjk = query.chars().any(|c| {
matches!(c, '\u{4E00}'..='\u{9FFF}' | '\u{3400}'..='\u{4DBF}' | '\u{F900}'..='\u{FAFF}')
});
if !has_cjk { if !has_cjk {
tracing::debug!( tracing::debug!(
@@ -730,9 +899,17 @@ impl VikingStorage for SqliteStorage {
scorer.score_similarity(query, &entry) scorer.score_similarity(query, &entry)
}; };
// Apply similarity threshold // Apply similarity threshold (relaxed for CJK queries since unicode61
// tokenizer doesn't produce meaningful TF-IDF scores for CJK text)
if let Some(min_similarity) = options.min_similarity { if let Some(min_similarity) = options.min_similarity {
if semantic_score < min_similarity { let threshold = if has_cjk {
// CJK TF-IDF scores are systematically low due to tokenizer limitations;
// use 50% of the normal threshold to avoid filtering out all results
min_similarity * 0.5
} else {
min_similarity
};
if semantic_score < threshold {
continue; continue;
} }
} }

View File

@@ -66,21 +66,30 @@ impl GrowthTracker {
timestamp: Utc::now(), timestamp: Utc::now(),
}; };
// Store learning event // Store learning event as MemoryEntry so get_timeline can find it via find_by_prefix
self.viking let event_uri = format!("agent://{}/events/{}", agent_id, session_id);
.store_metadata( let content = serde_json::to_string(&event)?;
&format!("agent://{}/events/{}", agent_id, session_id), let entry = crate::types::MemoryEntry {
&event, uri: event_uri,
) memory_type: MemoryType::Session,
.await?; content,
keywords: vec![agent_id.to_string(), session_id.to_string()],
importance: 5,
access_count: 0,
created_at: event.timestamp,
last_accessed: event.timestamp,
overview: None,
abstract_summary: None,
};
self.viking.store(&entry).await?;
// Update last learning time // Update last learning time via metadata
self.viking self.viking
.store_metadata( .store_metadata(
&format!("agent://{}", agent_id), &format!("agent://{}", agent_id),
&AgentMetadata { &AgentMetadata {
last_learning_time: Some(Utc::now()), last_learning_time: Some(Utc::now()),
total_learning_events: None, // Will be computed total_learning_events: None,
}, },
) )
.await?; .await?;

View File

@@ -394,6 +394,103 @@ pub struct DecayResult {
pub archived: u64, pub archived: u64,
} }
// === Evolution Engine Types ===
/// 经验提取结果
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ExperienceCandidate {
pub pain_pattern: String,
pub context: String,
pub solution_steps: Vec<String>,
pub outcome: Outcome,
pub confidence: f32,
pub tools_used: Vec<String>,
pub industry_context: Option<String>,
}
/// 结果状态
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum Outcome {
Success,
Partial,
Failed,
}
/// 合并提取结果(单次 LLM 调用的全部输出)
#[derive(Debug, Clone, Default)]
pub struct CombinedExtraction {
pub memories: Vec<ExtractedMemory>,
pub experiences: Vec<ExperienceCandidate>,
pub profile_signals: ProfileSignals,
}
/// 画像更新信号(从提取结果中推断,不额外调用 LLM
#[derive(Debug, Clone, Default)]
pub struct ProfileSignals {
pub industry: Option<String>,
pub recent_topic: Option<String>,
pub pain_point: Option<String>,
pub preferred_tool: Option<String>,
pub communication_style: Option<String>,
}
impl ProfileSignals {
/// 是否包含至少一个有效信号
pub fn has_any_signal(&self) -> bool {
self.industry.is_some()
|| self.recent_topic.is_some()
|| self.pain_point.is_some()
|| self.preferred_tool.is_some()
|| self.communication_style.is_some()
}
/// 有效信号数量
pub fn signal_count(&self) -> usize {
let mut count = 0;
if self.industry.is_some() { count += 1; }
if self.recent_topic.is_some() { count += 1; }
if self.pain_point.is_some() { count += 1; }
if self.preferred_tool.is_some() { count += 1; }
if self.communication_style.is_some() { count += 1; }
count
}
}
/// 进化事件
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EvolutionEvent {
pub id: String,
pub event_type: EvolutionEventType,
pub artifact_type: ArtifactType,
pub artifact_id: String,
pub status: EvolutionStatus,
pub confidence: f32,
pub user_feedback: Option<String>,
pub created_at: DateTime<Utc>,
}
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum EvolutionEventType {
SkillGenerated,
SkillOptimized,
WorkflowGenerated,
WorkflowOptimized,
}
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum ArtifactType {
Skill,
Pipeline,
}
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub enum EvolutionStatus {
Pending,
Confirmed,
Rejected,
Optimized,
}
/// Compute effective importance with time decay. /// Compute effective importance with time decay.
/// ///
/// Uses exponential decay: each 30-day period of non-access reduces /// Uses exponential decay: each 30-day period of non-access reduces
@@ -524,4 +621,61 @@ mod tests {
assert!(!result.is_empty()); assert!(!result.is_empty());
assert_eq!(result.total_count(), 1); assert_eq!(result.total_count(), 1);
} }
#[test]
fn test_experience_candidate_roundtrip() {
let candidate = ExperienceCandidate {
pain_pattern: "报表生成".to_string(),
context: "月度销售报表".to_string(),
solution_steps: vec!["查询数据库".to_string(), "格式化输出".to_string()],
outcome: Outcome::Success,
confidence: 0.85,
tools_used: vec!["researcher".to_string()],
industry_context: Some("healthcare".to_string()),
};
let json = serde_json::to_string(&candidate).unwrap();
let decoded: ExperienceCandidate = serde_json::from_str(&json).unwrap();
assert_eq!(decoded.pain_pattern, "报表生成");
assert_eq!(decoded.outcome, Outcome::Success);
assert_eq!(decoded.solution_steps.len(), 2);
}
#[test]
fn test_evolution_event_roundtrip() {
let event = EvolutionEvent {
id: uuid::Uuid::new_v4().to_string(),
event_type: EvolutionEventType::SkillGenerated,
artifact_type: ArtifactType::Skill,
artifact_id: "daily-report".to_string(),
status: EvolutionStatus::Pending,
confidence: 0.8,
user_feedback: None,
created_at: chrono::Utc::now(),
};
let json = serde_json::to_string(&event).unwrap();
let decoded: EvolutionEvent = serde_json::from_str(&json).unwrap();
assert_eq!(decoded.event_type, EvolutionEventType::SkillGenerated);
assert_eq!(decoded.status, EvolutionStatus::Pending);
}
#[test]
fn test_combined_extraction_default() {
let combined = CombinedExtraction::default();
assert!(combined.memories.is_empty());
assert!(combined.experiences.is_empty());
assert!(combined.profile_signals.industry.is_none());
}
#[test]
fn test_profile_signals() {
let signals = ProfileSignals {
industry: Some("healthcare".to_string()),
recent_topic: Some("报表".to_string()),
pain_point: None,
preferred_tool: Some("researcher".to_string()),
communication_style: Some("concise".to_string()),
};
assert_eq!(signals.industry.as_deref(), Some("healthcare"));
assert!(signals.pain_point.is_none());
}
} }

View File

@@ -0,0 +1,180 @@
//! 工作流组装器L3 工作流进化)
//! 从轨迹数据中分析重复的工具链模式,自动组装 Pipeline YAML
//! 触发条件CompressedTrajectory 中出现 2 次以上相同工具链序列
use zclaw_types::Result;
/// Pipeline 候选项
#[derive(Debug, Clone)]
pub struct PipelineCandidate {
pub name: String,
pub description: String,
pub triggers: Vec<String>,
pub yaml_content: String,
pub source_sessions: Vec<String>,
pub confidence: f32,
}
/// 工具链模式(用于聚类分析)
#[derive(Debug, Clone, Hash, PartialEq, Eq)]
pub struct ToolChainPattern {
pub steps: Vec<String>,
}
/// 工作流组装 prompt
const WORKFLOW_GENERATION_PROMPT: &str = r#"
你是一个工作流设计专家。根据以下用户反复执行的工具链序列,设计一个可复用的 Pipeline 工作流。
工具链序列:{tool_chain}
执行频率:{frequency} 次
行业背景:{industry}
请生成以下 JSON
```json
{
"name": "工作流名称(简短中文)",
"description": "工作流描述",
"triggers": ["触发词1", "触发词2"],
"yaml_content": "Pipeline YAML 内容",
"confidence": 0.8
}
```
"#;
/// 工作流组装器
/// 分析压缩轨迹中的工具链模式,通过 LLM 生成 Pipeline YAML
pub struct WorkflowComposer;
impl WorkflowComposer {
pub fn new() -> Self {
Self
}
/// 从压缩轨迹的工具链中提取模式
/// 简单的精确匹配聚类:相同工具链序列视为同一模式
pub fn extract_patterns(
trajectories: &[(String, Vec<String>)], // (session_id, tools_used)
) -> Vec<(ToolChainPattern, Vec<String>)> {
use std::collections::HashMap;
let mut groups: HashMap<ToolChainPattern, Vec<String>> = HashMap::new();
for (session_id, tools) in trajectories {
if tools.len() < 2 {
continue; // 单步操作不构成工作流
}
let pattern = ToolChainPattern {
steps: tools.clone(),
};
groups.entry(pattern).or_default().push(session_id.clone());
}
// 过滤出现 2 次以上的模式
groups
.into_iter()
.filter(|(_, sessions)| sessions.len() >= 2)
.collect()
}
/// 构建 LLM prompt
pub fn build_prompt(
pattern: &ToolChainPattern,
frequency: usize,
industry: Option<&str>,
) -> String {
WORKFLOW_GENERATION_PROMPT
.replace("{tool_chain}", &pattern.steps.join(""))
.replace("{frequency}", &frequency.to_string())
.replace("{industry}", industry.unwrap_or("通用"))
}
/// 解析 LLM 返回的 JSON 为 PipelineCandidate
pub fn parse_response(
json_str: &str,
_pattern: &ToolChainPattern,
source_sessions: Vec<String>,
) -> Result<PipelineCandidate> {
let json_str = crate::json_utils::extract_json_block(json_str);
let raw: serde_json::Value = serde_json::from_str(&json_str).map_err(|e| {
zclaw_types::ZclawError::ConfigError(format!("Invalid pipeline JSON: {}", e))
})?;
Ok(PipelineCandidate {
name: raw["name"].as_str().unwrap_or("未命名工作流").to_string(),
description: raw["description"].as_str().unwrap_or("").to_string(),
triggers: crate::json_utils::extract_string_array(&raw, "triggers"),
yaml_content: raw["yaml_content"].as_str().unwrap_or("").to_string(),
source_sessions,
confidence: raw["confidence"].as_f64().unwrap_or(0.5) as f32,
})
}
}
impl Default for WorkflowComposer {
fn default() -> Self {
Self::new()
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_extract_patterns_filters_single_step() {
let trajectories = vec![
("s1".to_string(), vec!["researcher".to_string()]),
];
let patterns = WorkflowComposer::extract_patterns(&trajectories);
assert!(patterns.is_empty());
}
#[test]
fn test_extract_patterns_groups_identical_chains() {
let trajectories = vec![
("s1".to_string(), vec!["researcher".into(), "collector".into()]),
("s2".to_string(), vec!["researcher".into(), "collector".into()]),
("s3".to_string(), vec!["browser".into()]), // 单步,过滤
];
let patterns = WorkflowComposer::extract_patterns(&trajectories);
assert_eq!(patterns.len(), 1);
assert_eq!(patterns[0].1.len(), 2); // 2 sessions
}
#[test]
fn test_extract_patterns_requires_min_2() {
let trajectories = vec![
("s1".to_string(), vec!["a".into(), "b".into()]),
];
let patterns = WorkflowComposer::extract_patterns(&trajectories);
assert!(patterns.is_empty()); // 只出现 1 次
}
#[test]
fn test_build_prompt() {
let pattern = ToolChainPattern {
steps: vec!["researcher".into(), "collector".into(), "summarize".into()],
};
let prompt = WorkflowComposer::build_prompt(&pattern, 3, Some("healthcare"));
assert!(prompt.contains("researcher"));
assert!(prompt.contains("3"));
assert!(prompt.contains("healthcare"));
}
#[test]
fn test_parse_response() {
let pattern = ToolChainPattern {
steps: vec!["researcher".into()],
};
let json = r##"{"name":"每日简报","description":"搜索+汇总","triggers":["简报","日报"],"yaml_content":"steps: []","confidence":0.85}"##;
let candidate = WorkflowComposer::parse_response(
json,
&pattern,
vec!["s1".into(), "s2".into()],
)
.unwrap();
assert_eq!(candidate.name, "每日简报");
assert_eq!(candidate.triggers.len(), 2);
assert_eq!(candidate.source_sessions.len(), 2);
assert!((candidate.confidence - 0.85).abs() < 0.01);
}
}

View File

@@ -0,0 +1,207 @@
//! Evolution loop integration test
//!
//! Tests the complete self-learning loop:
//! Experience accumulation → Pattern recognition → Evolution suggestion
use std::sync::Arc;
use zclaw_growth::{
EvolutionEngine, Experience, ExperienceStore, PatternAggregator,
SqliteStorage, VikingAdapter,
};
fn make_experience(agent_id: &str, pattern: &str, steps: Vec<&str>, tool: Option<&str>) -> Experience {
let mut exp = Experience::new(
agent_id,
pattern,
&format!("{}相关任务", pattern),
steps.into_iter().map(|s| s.to_string()).collect(),
"成功解决",
);
exp.tool_used = tool.map(|t| t.to_string());
exp
}
/// Store N experiences with the same pain pattern, then verify pattern recognition
#[tokio::test]
async fn test_evolution_loop_four_experiences_trigger_pattern() {
let storage = Arc::new(SqliteStorage::in_memory().await);
let adapter = Arc::new(VikingAdapter::new(storage));
let store = Arc::new(ExperienceStore::new(adapter.clone()));
let agent_id = "test-agent-evolution";
// Store 4 experiences with the same pain pattern
for _ in 0..4 {
let exp = make_experience(
agent_id,
"生成每日报表",
vec!["打开Excel", "选择模板", "导出PDF"],
Some("excel_tool"),
);
store.store_experience(&exp).await.unwrap();
}
// Verify experiences were stored and reuse_count accumulated
let all = store.find_by_agent(agent_id).await.unwrap();
assert_eq!(all.len(), 1, "Same pattern should merge into 1 experience");
assert_eq!(all[0].reuse_count, 3, "4 stores → reuse_count=3");
// Pattern aggregator should find this as evolvable
let agg_store = ExperienceStore::new(adapter.clone());
let aggregator = PatternAggregator::new(agg_store);
let patterns = aggregator.find_evolvable_patterns(agent_id, 3).await.unwrap();
assert_eq!(patterns.len(), 1, "Should find 1 evolvable pattern");
assert_eq!(patterns[0].pain_pattern, "生成每日报表");
assert!(patterns[0].total_reuse >= 3);
assert!(!patterns[0].common_steps.is_empty(), "Should find common steps");
// Evolution engine should detect the same patterns
let engine = EvolutionEngine::new(adapter);
let evolvable = engine.check_evolvable_patterns(agent_id).await.unwrap();
assert_eq!(evolvable.len(), 1, "EvolutionEngine should detect 1 evolvable pattern");
assert_eq!(evolvable[0].pain_pattern, "生成每日报表");
}
/// Verify that experiences below threshold are NOT marked evolvable
#[tokio::test]
async fn test_evolution_loop_below_threshold_not_evolvable() {
let storage = Arc::new(SqliteStorage::in_memory().await);
let adapter = Arc::new(VikingAdapter::new(storage));
let store = Arc::new(ExperienceStore::new(adapter.clone()));
let agent_id = "test-agent-below";
// Store only 2 experiences (below min_reuse=3)
for _ in 0..2 {
let exp = make_experience(agent_id, "低频任务", vec!["步骤1"], None);
store.store_experience(&exp).await.unwrap();
}
let all = store.find_by_agent(agent_id).await.unwrap();
assert_eq!(all.len(), 1);
assert_eq!(all[0].reuse_count, 1, "2 stores → reuse_count=1");
let engine = EvolutionEngine::new(adapter);
let evolvable = engine.check_evolvable_patterns(agent_id).await.unwrap();
assert!(evolvable.is_empty(), "Below threshold should not be evolvable");
}
/// Verify multiple different patterns are tracked independently
#[tokio::test]
async fn test_evolution_loop_multiple_patterns() {
let storage = Arc::new(SqliteStorage::in_memory().await);
let adapter = Arc::new(VikingAdapter::new(storage));
let store = Arc::new(ExperienceStore::new(adapter.clone()));
let agent_id = "test-agent-multi";
// Pattern A: 4 occurrences → evolvable
for _ in 0..4 {
let mut exp = make_experience(agent_id, "报表生成", vec!["打开系统", "选择日期"], Some("browser"));
exp.industry_context = Some("医疗".into());
store.store_experience(&exp).await.unwrap();
}
// Pattern B: 2 occurrences → not evolvable
for _ in 0..2 {
let exp = make_experience(agent_id, "会议纪要", vec!["录音转文字"], None);
store.store_experience(&exp).await.unwrap();
}
let engine = EvolutionEngine::new(adapter);
let evolvable = engine.check_evolvable_patterns(agent_id).await.unwrap();
assert_eq!(evolvable.len(), 1, "Only pattern A should be evolvable");
assert_eq!(evolvable[0].pain_pattern, "报表生成");
assert_eq!(evolvable[0].total_reuse, 3);
assert_eq!(evolvable[0].industry_context, Some("医疗".into()));
}
/// Test SkillGenerator prompt building from evolvable pattern
#[tokio::test]
async fn test_skill_generator_from_evolvable_pattern() {
use zclaw_growth::{AggregatedPattern, SkillGenerator};
let pattern = AggregatedPattern {
pain_pattern: "生成每日报表".to_string(),
experiences: vec![],
common_steps: vec!["打开Excel".into(), "选择模板".into(), "导出PDF".into()],
total_reuse: 5,
tools_used: vec!["excel_tool".into()],
industry_context: Some("医疗".into()),
};
let prompt = SkillGenerator::build_prompt(&pattern);
assert!(prompt.contains("生成每日报表"));
assert!(prompt.contains("打开Excel"));
assert!(prompt.contains("excel_tool"));
}
/// Test QualityGate validates skill candidates
#[tokio::test]
async fn test_quality_gate_validation() {
use zclaw_growth::{QualityGate, SkillCandidate};
let candidate = SkillCandidate {
name: "每日报表生成".to_string(),
description: "自动生成并导出每日报表".to_string(),
triggers: vec!["生成报表".into(), "每日报表".into()],
tools: vec!["excel_tool".into()],
body_markdown: "# 每日报表生成\n\n## 步骤一:数据收集\n从数据库查询昨日所有交易记录和运营数据。\n\n## 步骤二:数据整理\n将原始数据按部门、类型进行分类汇总。\n\n## 步骤三:报表输出\n生成标准化报表并导出为PDF格式。".to_string(),
source_pattern: "生成每日报表".to_string(),
confidence: 0.85,
version: 1,
};
let gate = QualityGate::new(0.7, vec![]);
let report = gate.validate_skill(&candidate);
assert!(report.passed, "Valid candidate should pass quality gate");
assert!(report.issues.is_empty());
// Test with conflicting trigger
let gate_with_conflict = QualityGate::new(0.7, vec!["生成报表".into()]);
let report = gate_with_conflict.validate_skill(&candidate);
assert!(!report.passed, "Conflicting trigger should fail");
}
/// Test FeedbackCollector trust score updates
#[tokio::test]
async fn test_feedback_collector_trust_evolution() {
use zclaw_growth::feedback_collector::{
EvolutionArtifact, FeedbackCollector, FeedbackEntry, FeedbackSignal, Sentiment,
};
let storage = Arc::new(SqliteStorage::in_memory().await);
let adapter = Arc::new(VikingAdapter::new(storage));
let mut collector = FeedbackCollector::with_viking(adapter);
// Submit 3 positive feedbacks across 2 skills
for i in 0..3 {
let entry = FeedbackEntry {
artifact_id: format!("skill-{}", i % 2),
artifact_type: EvolutionArtifact::Skill,
signal: FeedbackSignal::Explicit,
sentiment: Sentiment::Positive,
details: Some("很有用".into()),
timestamp: chrono::Utc::now(),
};
collector.submit_feedback(entry);
}
// Submit 1 negative feedback
let negative = FeedbackEntry {
artifact_id: "skill-0".to_string(),
artifact_type: EvolutionArtifact::Skill,
signal: FeedbackSignal::Explicit,
sentiment: Sentiment::Negative,
details: Some("步骤有误".into()),
timestamp: chrono::Utc::now(),
};
collector.submit_feedback(negative);
// skill-0: 2 positive + 1 negative
let trust0 = collector.get_trust("skill-0").unwrap();
assert_eq!(trust0.positive_count, 2);
assert_eq!(trust0.negative_count, 1);
// skill-1: 1 positive only
let trust1 = collector.get_trust("skill-1").unwrap();
assert_eq!(trust1.positive_count, 1);
assert_eq!(trust1.negative_count, 0);
}

View File

@@ -21,3 +21,4 @@ tracing = { workspace = true }
async-trait = { workspace = true } async-trait = { workspace = true }
reqwest = { workspace = true } reqwest = { workspace = true }
base64 = { workspace = true } base64 = { workspace = true }
dirs = { workspace = true }

View File

@@ -1,7 +1,7 @@
//! Browser Hand - Web automation capabilities (TypeScript delegation) //! Browser Hand - Web automation capabilities (TypeScript delegation)
//! //!
//! **Architecture note (M3-02):** This Rust Hand is a **schema validator and passthrough**. //! **Architecture note (M3-02):** This Rust Hand is a **schema validator and passthrough**.
//! Every action returns `{"status": "pending_execution"}` — no real browser work happens here. //! Every action returns `{"status": "delegated_to_frontend"}` — no real browser work happens here.
//! //!
//! The actual execution path is: //! The actual execution path is:
//! 1. Frontend `HandsPanel.tsx` intercepts browser hands → routes to `BrowserHandCard` //! 1. Frontend `HandsPanel.tsx` intercepts browser hands → routes to `BrowserHandCard`
@@ -117,6 +117,56 @@ pub enum BrowserAction {
}, },
} }
impl BrowserAction {
pub fn action_name(&self) -> &'static str {
match self {
BrowserAction::Navigate { .. } => "navigate",
BrowserAction::Click { .. } => "click",
BrowserAction::Type { .. } => "type",
BrowserAction::Select { .. } => "select",
BrowserAction::Scrape { .. } => "scrape",
BrowserAction::Screenshot { .. } => "screenshot",
BrowserAction::FillForm { .. } => "fill_form",
BrowserAction::Wait { .. } => "wait",
BrowserAction::Execute { .. } => "execute",
BrowserAction::GetSource => "get_source",
BrowserAction::GetUrl => "get_url",
BrowserAction::GetTitle => "get_title",
BrowserAction::Scroll { .. } => "scroll",
BrowserAction::Back => "back",
BrowserAction::Forward => "forward",
BrowserAction::Refresh => "refresh",
BrowserAction::Hover { .. } => "hover",
BrowserAction::PressKey { .. } => "press_key",
BrowserAction::Upload { .. } => "upload",
}
}
pub fn summary(&self) -> String {
match self {
BrowserAction::Navigate { url, .. } => format!("导航到 {}", url),
BrowserAction::Click { selector, .. } => format!("点击 {}", selector),
BrowserAction::Type { selector, text, .. } => format!("{} 输入 {}", selector, text),
BrowserAction::Select { selector, value } => format!("{} 选择 {}", selector, value),
BrowserAction::Scrape { selectors, .. } => format!("抓取 {} 个选择器", selectors.len()),
BrowserAction::Screenshot { .. } => "截图".to_string(),
BrowserAction::FillForm { fields, .. } => format!("填写 {} 个字段", fields.len()),
BrowserAction::Wait { selector, .. } => format!("等待 {}", selector),
BrowserAction::Execute { .. } => "执行脚本".to_string(),
BrowserAction::GetSource => "获取页面源码".to_string(),
BrowserAction::GetUrl => "获取当前URL".to_string(),
BrowserAction::GetTitle => "获取页面标题".to_string(),
BrowserAction::Scroll { x, y, .. } => format!("滚动到 ({},{})", x, y),
BrowserAction::Back => "后退".to_string(),
BrowserAction::Forward => "前进".to_string(),
BrowserAction::Refresh => "刷新".to_string(),
BrowserAction::Hover { selector } => format!("悬停 {}", selector),
BrowserAction::PressKey { key } => format!("按键 {}", key),
BrowserAction::Upload { selector, .. } => format!("上传文件到 {}", selector),
}
}
}
/// Form field definition /// Form field definition
#[derive(Debug, Clone, Serialize, Deserialize)] #[derive(Debug, Clone, Serialize, Deserialize)]
pub struct FormField { pub struct FormField {
@@ -202,151 +252,18 @@ impl Hand for BrowserHand {
Err(e) => return Ok(HandResult::error(format!("Invalid action: {}", e))), Err(e) => return Ok(HandResult::error(format!("Invalid action: {}", e))),
}; };
// Execute based on action type // Browser automation executes on the frontend via BrowserHandCard.
// Note: Actual browser operations are handled via Tauri commands // Return the parsed action with a clear message so the LLM can inform
// This Hand provides a structured interface for the runtime // the user and the frontend can pick it up via Tauri events.
match action { let action_type = action.action_name();
BrowserAction::Navigate { url, wait_for } => { let summary = action.summary();
Ok(HandResult::success(serde_json::json!({
"action": "navigate", Ok(HandResult::success(serde_json::json!({
"url": url, "action": action_type,
"wait_for": wait_for, "status": "delegated_to_frontend",
"status": "pending_execution" "message": format!("浏览器操作「{}」已委托给前端执行。请在 HandsPanel 中查看执行结果。", summary),
}))) "details": format!("{} — 需要 WebDriver 会话,由前端 BrowserHandCard 管理。", summary),
} })))
BrowserAction::Click { selector, wait_ms } => {
Ok(HandResult::success(serde_json::json!({
"action": "click",
"selector": selector,
"wait_ms": wait_ms,
"status": "pending_execution"
})))
}
BrowserAction::Type { selector, text, clear_first } => {
Ok(HandResult::success(serde_json::json!({
"action": "type",
"selector": selector,
"text": text,
"clear_first": clear_first,
"status": "pending_execution"
})))
}
BrowserAction::Scrape { selectors, wait_for } => {
Ok(HandResult::success(serde_json::json!({
"action": "scrape",
"selectors": selectors,
"wait_for": wait_for,
"status": "pending_execution"
})))
}
BrowserAction::Screenshot { selector, full_page } => {
Ok(HandResult::success(serde_json::json!({
"action": "screenshot",
"selector": selector,
"full_page": full_page,
"status": "pending_execution"
})))
}
BrowserAction::FillForm { fields, submit_selector } => {
Ok(HandResult::success(serde_json::json!({
"action": "fill_form",
"fields": fields,
"submit_selector": submit_selector,
"status": "pending_execution"
})))
}
BrowserAction::Wait { selector, timeout_ms } => {
Ok(HandResult::success(serde_json::json!({
"action": "wait",
"selector": selector,
"timeout_ms": timeout_ms,
"status": "pending_execution"
})))
}
BrowserAction::Execute { script, args } => {
Ok(HandResult::success(serde_json::json!({
"action": "execute",
"script": script,
"args": args,
"status": "pending_execution"
})))
}
BrowserAction::GetSource => {
Ok(HandResult::success(serde_json::json!({
"action": "get_source",
"status": "pending_execution"
})))
}
BrowserAction::GetUrl => {
Ok(HandResult::success(serde_json::json!({
"action": "get_url",
"status": "pending_execution"
})))
}
BrowserAction::GetTitle => {
Ok(HandResult::success(serde_json::json!({
"action": "get_title",
"status": "pending_execution"
})))
}
BrowserAction::Scroll { x, y, selector } => {
Ok(HandResult::success(serde_json::json!({
"action": "scroll",
"x": x,
"y": y,
"selector": selector,
"status": "pending_execution"
})))
}
BrowserAction::Back => {
Ok(HandResult::success(serde_json::json!({
"action": "back",
"status": "pending_execution"
})))
}
BrowserAction::Forward => {
Ok(HandResult::success(serde_json::json!({
"action": "forward",
"status": "pending_execution"
})))
}
BrowserAction::Refresh => {
Ok(HandResult::success(serde_json::json!({
"action": "refresh",
"status": "pending_execution"
})))
}
BrowserAction::Hover { selector } => {
Ok(HandResult::success(serde_json::json!({
"action": "hover",
"selector": selector,
"status": "pending_execution"
})))
}
BrowserAction::PressKey { key } => {
Ok(HandResult::success(serde_json::json!({
"action": "press_key",
"key": key,
"status": "pending_execution"
})))
}
BrowserAction::Upload { selector, file_path } => {
Ok(HandResult::success(serde_json::json!({
"action": "upload",
"selector": selector,
"file_path": file_path,
"status": "pending_execution"
})))
}
BrowserAction::Select { selector, value } => {
Ok(HandResult::success(serde_json::json!({
"action": "select",
"selector": selector,
"value": value,
"status": "pending_execution"
})))
}
}
} }
fn is_dependency_available(&self, dep: &str) -> bool { fn is_dependency_available(&self, dep: &str) -> bool {
@@ -600,7 +517,7 @@ mod tests {
let result = hand.execute(&ctx, action_json).await.expect("execute"); let result = hand.execute(&ctx, action_json).await.expect("execute");
assert!(result.success); assert!(result.success);
assert_eq!(result.output["action"], "navigate"); assert_eq!(result.output["action"], "navigate");
assert_eq!(result.output["url"], "https://example.com"); assert_eq!(result.output["status"], "delegated_to_frontend");
} }
#[tokio::test] #[tokio::test]

View File

@@ -459,7 +459,7 @@ impl ClipHand {
let args = vec![ let args = vec![
"-f", "concat", "-f", "concat",
"-safe", "0", "-safe", "0",
"-i", temp_file.to_str().unwrap(), "-i", temp_file.to_str().ok_or_else(|| zclaw_types::ZclawError::HandError("Temp file path is not valid UTF-8".to_string()))?,
"-c", "copy", "-c", "copy",
&config.output_path, &config.output_path,
]; ];

View File

@@ -1,9 +1,6 @@
//! Educational Hands - Teaching and presentation capabilities //! Educational Hands - Teaching and presentation capabilities
//! //!
//! This module provides hands for interactive classroom experiences: //! This module provides hands for interactive experiences:
//! - Whiteboard: Drawing and annotation
//! - Slideshow: Presentation control
//! - Speech: Text-to-speech synthesis
//! - Quiz: Assessment and evaluation //! - Quiz: Assessment and evaluation
//! - Browser: Web automation //! - Browser: Web automation
//! - Researcher: Deep research and analysis //! - Researcher: Deep research and analysis
@@ -11,22 +8,18 @@
//! - Clip: Video processing //! - Clip: Video processing
//! - Twitter: Social media automation //! - Twitter: Social media automation
mod whiteboard;
mod slideshow;
mod speech;
pub mod quiz; pub mod quiz;
mod browser; mod browser;
mod researcher; mod researcher;
mod collector; mod collector;
mod clip; mod clip;
mod twitter; mod twitter;
pub mod reminder;
pub use whiteboard::*;
pub use slideshow::*;
pub use speech::*;
pub use quiz::*; pub use quiz::*;
pub use browser::*; pub use browser::*;
pub use researcher::*; pub use researcher::*;
pub use collector::*; pub use collector::*;
pub use clip::*; pub use clip::*;
pub use twitter::*; pub use twitter::*;
pub use reminder::*;

View File

@@ -0,0 +1,77 @@
//! Reminder Hand - Internal hand for scheduled reminders
//!
//! This is a system hand (id `_reminder`) used by the schedule interception
//! layer in `agent_chat_stream`. When the NlScheduleParser detects a schedule
//! intent in chat, it creates a trigger targeting this hand. The SchedulerService
//! fires the trigger at the scheduled time.
use async_trait::async_trait;
use serde_json::Value;
use zclaw_types::Result;
use crate::{Hand, HandConfig, HandContext, HandResult, HandStatus};
/// Internal reminder hand for scheduled tasks
pub struct ReminderHand {
config: HandConfig,
}
impl ReminderHand {
/// Create a new reminder hand
pub fn new() -> Self {
Self {
config: HandConfig {
id: "_reminder".to_string(),
name: "定时提醒".to_string(),
description: "Internal hand for scheduled reminders".to_string(),
needs_approval: false,
dependencies: vec![],
input_schema: None,
tags: vec!["system".to_string()],
enabled: true,
max_concurrent: 0,
timeout_secs: 0,
},
}
}
}
#[async_trait]
impl Hand for ReminderHand {
fn config(&self) -> &HandConfig {
&self.config
}
async fn execute(&self, _context: &HandContext, input: Value) -> Result<HandResult> {
let task_desc = input
.get("task_description")
.and_then(|v| v.as_str())
.unwrap_or("定时提醒");
let cron = input
.get("cron")
.and_then(|v| v.as_str())
.unwrap_or("");
let fired_at = input
.get("fired_at")
.and_then(|v| v.as_str())
.unwrap_or("unknown time");
tracing::info!(
"[ReminderHand] Fired at {} — task: {}, cron: {}",
fired_at, task_desc, cron
);
Ok(HandResult::success(serde_json::json!({
"task": task_desc,
"cron": cron,
"fired_at": fired_at,
"status": "reminded",
})))
}
fn status(&self) -> HandStatus {
HandStatus::Idle
}
}

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@@ -1,797 +0,0 @@
//! Slideshow Hand - Presentation control capabilities
//!
//! Provides slideshow control for teaching:
//! - next_slide/prev_slide: Navigation
//! - goto_slide: Jump to specific slide
//! - spotlight: Highlight elements
//! - laser: Show laser pointer
//! - highlight: Highlight areas
//! - play_animation: Trigger animations
use async_trait::async_trait;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use std::sync::Arc;
use tokio::sync::RwLock;
use zclaw_types::Result;
use crate::{Hand, HandConfig, HandContext, HandResult, HandStatus};
/// Slideshow action types
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "action", rename_all = "snake_case")]
pub enum SlideshowAction {
/// Go to next slide
NextSlide,
/// Go to previous slide
PrevSlide,
/// Go to specific slide
GotoSlide {
slide_number: usize,
},
/// Spotlight/highlight an element
Spotlight {
element_id: String,
#[serde(default = "default_spotlight_duration")]
duration_ms: u64,
},
/// Show laser pointer at position
Laser {
x: f64,
y: f64,
#[serde(default = "default_laser_duration")]
duration_ms: u64,
},
/// Highlight a rectangular area
Highlight {
x: f64,
y: f64,
width: f64,
height: f64,
#[serde(default)]
color: Option<String>,
#[serde(default = "default_highlight_duration")]
duration_ms: u64,
},
/// Play animation
PlayAnimation {
animation_id: String,
},
/// Pause auto-play
Pause,
/// Resume auto-play
Resume,
/// Start auto-play
AutoPlay {
#[serde(default = "default_interval")]
interval_ms: u64,
},
/// Stop auto-play
StopAutoPlay,
/// Get current state
GetState,
/// Set slide content (for dynamic slides)
SetContent {
slide_number: usize,
content: SlideContent,
},
}
fn default_spotlight_duration() -> u64 { 2000 }
fn default_laser_duration() -> u64 { 3000 }
fn default_highlight_duration() -> u64 { 2000 }
fn default_interval() -> u64 { 5000 }
/// Slide content structure
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SlideContent {
pub title: String,
#[serde(default)]
pub subtitle: Option<String>,
#[serde(default)]
pub content: Vec<ContentBlock>,
#[serde(default)]
pub notes: Option<String>,
#[serde(default)]
pub background: Option<String>,
}
/// Presentation/slideshow rendering content block. Domain-specific for slide content.
/// Distinct from zclaw_types::ContentBlock (LLM messages) and zclaw_protocols::ContentBlock (MCP).
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum ContentBlock {
Text { text: String, style: Option<TextStyle> },
Image { url: String, alt: Option<String> },
List { items: Vec<String>, ordered: bool },
Code { code: String, language: Option<String> },
Math { latex: String },
Table { headers: Vec<String>, rows: Vec<Vec<String>> },
Chart { chart_type: String, data: serde_json::Value },
}
/// Text style options
#[derive(Debug, Clone, Serialize, Deserialize, Default)]
pub struct TextStyle {
#[serde(default)]
pub bold: bool,
#[serde(default)]
pub italic: bool,
#[serde(default)]
pub size: Option<u32>,
#[serde(default)]
pub color: Option<String>,
}
/// Slideshow state
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SlideshowState {
pub current_slide: usize,
pub total_slides: usize,
pub is_playing: bool,
pub auto_play_interval_ms: u64,
pub slides: Vec<SlideContent>,
}
impl Default for SlideshowState {
fn default() -> Self {
Self {
current_slide: 0,
total_slides: 0,
is_playing: false,
auto_play_interval_ms: 5000,
slides: Vec::new(),
}
}
}
/// Slideshow Hand implementation
pub struct SlideshowHand {
config: HandConfig,
state: Arc<RwLock<SlideshowState>>,
}
impl SlideshowHand {
/// Create a new slideshow hand
pub fn new() -> Self {
Self {
config: HandConfig {
id: "slideshow".to_string(),
name: "幻灯片".to_string(),
description: "控制演示文稿的播放、导航和标注".to_string(),
needs_approval: false,
dependencies: vec![],
input_schema: Some(serde_json::json!({
"type": "object",
"properties": {
"action": { "type": "string" },
"slide_number": { "type": "integer" },
"element_id": { "type": "string" },
}
})),
tags: vec!["presentation".to_string(), "education".to_string()],
enabled: true,
max_concurrent: 0,
timeout_secs: 0,
},
state: Arc::new(RwLock::new(SlideshowState::default())),
}
}
/// Create with slides (async version)
pub async fn with_slides_async(slides: Vec<SlideContent>) -> Self {
let hand = Self::new();
let mut state = hand.state.write().await;
state.total_slides = slides.len();
state.slides = slides;
drop(state);
hand
}
/// Execute a slideshow action
pub async fn execute_action(&self, action: SlideshowAction) -> Result<HandResult> {
let mut state = self.state.write().await;
match action {
SlideshowAction::NextSlide => {
if state.current_slide < state.total_slides.saturating_sub(1) {
state.current_slide += 1;
}
Ok(HandResult::success(serde_json::json!({
"status": "next",
"current_slide": state.current_slide,
"total_slides": state.total_slides,
})))
}
SlideshowAction::PrevSlide => {
if state.current_slide > 0 {
state.current_slide -= 1;
}
Ok(HandResult::success(serde_json::json!({
"status": "prev",
"current_slide": state.current_slide,
"total_slides": state.total_slides,
})))
}
SlideshowAction::GotoSlide { slide_number } => {
if slide_number < state.total_slides {
state.current_slide = slide_number;
Ok(HandResult::success(serde_json::json!({
"status": "goto",
"current_slide": state.current_slide,
"slide_content": state.slides.get(slide_number),
})))
} else {
Ok(HandResult::error(format!("Slide {} out of range", slide_number)))
}
}
SlideshowAction::Spotlight { element_id, duration_ms } => {
Ok(HandResult::success(serde_json::json!({
"status": "spotlight",
"element_id": element_id,
"duration_ms": duration_ms,
})))
}
SlideshowAction::Laser { x, y, duration_ms } => {
Ok(HandResult::success(serde_json::json!({
"status": "laser",
"x": x,
"y": y,
"duration_ms": duration_ms,
})))
}
SlideshowAction::Highlight { x, y, width, height, color, duration_ms } => {
Ok(HandResult::success(serde_json::json!({
"status": "highlight",
"x": x, "y": y,
"width": width, "height": height,
"color": color.unwrap_or_else(|| "#ffcc00".to_string()),
"duration_ms": duration_ms,
})))
}
SlideshowAction::PlayAnimation { animation_id } => {
Ok(HandResult::success(serde_json::json!({
"status": "animation",
"animation_id": animation_id,
})))
}
SlideshowAction::Pause => {
state.is_playing = false;
Ok(HandResult::success(serde_json::json!({
"status": "paused",
})))
}
SlideshowAction::Resume => {
state.is_playing = true;
Ok(HandResult::success(serde_json::json!({
"status": "resumed",
})))
}
SlideshowAction::AutoPlay { interval_ms } => {
state.is_playing = true;
state.auto_play_interval_ms = interval_ms;
Ok(HandResult::success(serde_json::json!({
"status": "autoplay",
"interval_ms": interval_ms,
})))
}
SlideshowAction::StopAutoPlay => {
state.is_playing = false;
Ok(HandResult::success(serde_json::json!({
"status": "stopped",
})))
}
SlideshowAction::GetState => {
Ok(HandResult::success(serde_json::to_value(&*state).unwrap_or(Value::Null)))
}
SlideshowAction::SetContent { slide_number, content } => {
if slide_number < state.slides.len() {
state.slides[slide_number] = content.clone();
Ok(HandResult::success(serde_json::json!({
"status": "content_set",
"slide_number": slide_number,
})))
} else if slide_number == state.slides.len() {
state.slides.push(content);
state.total_slides = state.slides.len();
Ok(HandResult::success(serde_json::json!({
"status": "slide_added",
"slide_number": slide_number,
})))
} else {
Ok(HandResult::error(format!("Invalid slide number: {}", slide_number)))
}
}
}
}
/// Get current state
pub async fn get_state(&self) -> SlideshowState {
self.state.read().await.clone()
}
/// Add a slide
pub async fn add_slide(&self, content: SlideContent) {
let mut state = self.state.write().await;
state.slides.push(content);
state.total_slides = state.slides.len();
}
}
impl Default for SlideshowHand {
fn default() -> Self {
Self::new()
}
}
#[async_trait]
impl Hand for SlideshowHand {
fn config(&self) -> &HandConfig {
&self.config
}
async fn execute(&self, _context: &HandContext, input: Value) -> Result<HandResult> {
let action: SlideshowAction = match serde_json::from_value(input) {
Ok(a) => a,
Err(e) => {
return Ok(HandResult::error(format!("Invalid slideshow action: {}", e)));
}
};
self.execute_action(action).await
}
fn status(&self) -> HandStatus {
HandStatus::Idle
}
}
#[cfg(test)]
mod tests {
use super::*;
use serde_json::json;
// === Config & Defaults ===
#[tokio::test]
async fn test_slideshow_creation() {
let hand = SlideshowHand::new();
assert_eq!(hand.config().id, "slideshow");
assert_eq!(hand.config().name, "幻灯片");
assert!(!hand.config().needs_approval);
assert!(hand.config().enabled);
assert!(hand.config().tags.contains(&"presentation".to_string()));
}
#[test]
fn test_default_impl() {
let hand = SlideshowHand::default();
assert_eq!(hand.config().id, "slideshow");
}
#[test]
fn test_needs_approval() {
let hand = SlideshowHand::new();
assert!(!hand.needs_approval());
}
#[test]
fn test_status() {
let hand = SlideshowHand::new();
assert_eq!(hand.status(), HandStatus::Idle);
}
#[test]
fn test_default_state() {
let state = SlideshowState::default();
assert_eq!(state.current_slide, 0);
assert_eq!(state.total_slides, 0);
assert!(!state.is_playing);
assert_eq!(state.auto_play_interval_ms, 5000);
assert!(state.slides.is_empty());
}
// === Navigation ===
#[tokio::test]
async fn test_navigation() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "Slide 1".to_string(), subtitle: None, content: vec![], notes: None, background: None },
SlideContent { title: "Slide 2".to_string(), subtitle: None, content: vec![], notes: None, background: None },
SlideContent { title: "Slide 3".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
// Next
hand.execute_action(SlideshowAction::NextSlide).await.unwrap();
assert_eq!(hand.get_state().await.current_slide, 1);
// Goto
hand.execute_action(SlideshowAction::GotoSlide { slide_number: 2 }).await.unwrap();
assert_eq!(hand.get_state().await.current_slide, 2);
// Prev
hand.execute_action(SlideshowAction::PrevSlide).await.unwrap();
assert_eq!(hand.get_state().await.current_slide, 1);
}
#[tokio::test]
async fn test_next_slide_at_end() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "Only Slide".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
// At slide 0, should not advance past last slide
hand.execute_action(SlideshowAction::NextSlide).await.unwrap();
assert_eq!(hand.get_state().await.current_slide, 0);
}
#[tokio::test]
async fn test_prev_slide_at_beginning() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "Slide 1".to_string(), subtitle: None, content: vec![], notes: None, background: None },
SlideContent { title: "Slide 2".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
// At slide 0, should not go below 0
hand.execute_action(SlideshowAction::PrevSlide).await.unwrap();
assert_eq!(hand.get_state().await.current_slide, 0);
}
#[tokio::test]
async fn test_goto_slide_out_of_range() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "Slide 1".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
let result = hand.execute_action(SlideshowAction::GotoSlide { slide_number: 5 }).await.unwrap();
assert!(!result.success);
}
#[tokio::test]
async fn test_goto_slide_returns_content() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "First".to_string(), subtitle: None, content: vec![], notes: None, background: None },
SlideContent { title: "Second".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
let result = hand.execute_action(SlideshowAction::GotoSlide { slide_number: 1 }).await.unwrap();
assert!(result.success);
assert_eq!(result.output["slide_content"]["title"], "Second");
}
// === Spotlight & Laser & Highlight ===
#[tokio::test]
async fn test_spotlight() {
let hand = SlideshowHand::new();
let action = SlideshowAction::Spotlight {
element_id: "title".to_string(),
duration_ms: 2000,
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
assert_eq!(result.output["element_id"], "title");
assert_eq!(result.output["duration_ms"], 2000);
}
#[tokio::test]
async fn test_spotlight_default_duration() {
let hand = SlideshowHand::new();
let action = SlideshowAction::Spotlight {
element_id: "elem".to_string(),
duration_ms: default_spotlight_duration(),
};
let result = hand.execute_action(action).await.unwrap();
assert_eq!(result.output["duration_ms"], 2000);
}
#[tokio::test]
async fn test_laser() {
let hand = SlideshowHand::new();
let action = SlideshowAction::Laser {
x: 100.0,
y: 200.0,
duration_ms: 3000,
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
assert_eq!(result.output["x"], 100.0);
assert_eq!(result.output["y"], 200.0);
}
#[tokio::test]
async fn test_highlight_default_color() {
let hand = SlideshowHand::new();
let action = SlideshowAction::Highlight {
x: 10.0, y: 20.0, width: 100.0, height: 50.0,
color: None, duration_ms: 2000,
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
assert_eq!(result.output["color"], "#ffcc00");
}
#[tokio::test]
async fn test_highlight_custom_color() {
let hand = SlideshowHand::new();
let action = SlideshowAction::Highlight {
x: 0.0, y: 0.0, width: 50.0, height: 50.0,
color: Some("#ff0000".to_string()), duration_ms: 1000,
};
let result = hand.execute_action(action).await.unwrap();
assert_eq!(result.output["color"], "#ff0000");
}
// === AutoPlay / Pause / Resume ===
#[tokio::test]
async fn test_autoplay_pause_resume() {
let hand = SlideshowHand::new();
// AutoPlay
let result = hand.execute_action(SlideshowAction::AutoPlay { interval_ms: 3000 }).await.unwrap();
assert!(result.success);
assert!(hand.get_state().await.is_playing);
assert_eq!(hand.get_state().await.auto_play_interval_ms, 3000);
// Pause
hand.execute_action(SlideshowAction::Pause).await.unwrap();
assert!(!hand.get_state().await.is_playing);
// Resume
hand.execute_action(SlideshowAction::Resume).await.unwrap();
assert!(hand.get_state().await.is_playing);
// Stop
hand.execute_action(SlideshowAction::StopAutoPlay).await.unwrap();
assert!(!hand.get_state().await.is_playing);
}
#[tokio::test]
async fn test_autoplay_default_interval() {
let hand = SlideshowHand::new();
hand.execute_action(SlideshowAction::AutoPlay { interval_ms: default_interval() }).await.unwrap();
assert_eq!(hand.get_state().await.auto_play_interval_ms, 5000);
}
// === PlayAnimation ===
#[tokio::test]
async fn test_play_animation() {
let hand = SlideshowHand::new();
let result = hand.execute_action(SlideshowAction::PlayAnimation {
animation_id: "fade_in".to_string(),
}).await.unwrap();
assert!(result.success);
assert_eq!(result.output["animation_id"], "fade_in");
}
// === GetState ===
#[tokio::test]
async fn test_get_state() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "A".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
let result = hand.execute_action(SlideshowAction::GetState).await.unwrap();
assert!(result.success);
assert_eq!(result.output["total_slides"], 1);
assert_eq!(result.output["current_slide"], 0);
}
// === SetContent ===
#[tokio::test]
async fn test_set_content() {
let hand = SlideshowHand::new();
let content = SlideContent {
title: "Test Slide".to_string(),
subtitle: Some("Subtitle".to_string()),
content: vec![ContentBlock::Text {
text: "Hello".to_string(),
style: None,
}],
notes: Some("Speaker notes".to_string()),
background: None,
};
let result = hand.execute_action(SlideshowAction::SetContent {
slide_number: 0,
content,
}).await.unwrap();
assert!(result.success);
assert_eq!(hand.get_state().await.total_slides, 1);
assert_eq!(hand.get_state().await.slides[0].title, "Test Slide");
}
#[tokio::test]
async fn test_set_content_append() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "First".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
let content = SlideContent {
title: "Appended".to_string(), subtitle: None, content: vec![], notes: None, background: None,
};
let result = hand.execute_action(SlideshowAction::SetContent {
slide_number: 1,
content,
}).await.unwrap();
assert!(result.success);
assert_eq!(result.output["status"], "slide_added");
assert_eq!(hand.get_state().await.total_slides, 2);
}
#[tokio::test]
async fn test_set_content_invalid_index() {
let hand = SlideshowHand::new();
let content = SlideContent {
title: "Gap".to_string(), subtitle: None, content: vec![], notes: None, background: None,
};
let result = hand.execute_action(SlideshowAction::SetContent {
slide_number: 5,
content,
}).await.unwrap();
assert!(!result.success);
}
// === Action Deserialization ===
#[test]
fn test_deserialize_next_slide() {
let action: SlideshowAction = serde_json::from_value(json!({"action": "next_slide"})).unwrap();
assert!(matches!(action, SlideshowAction::NextSlide));
}
#[test]
fn test_deserialize_goto_slide() {
let action: SlideshowAction = serde_json::from_value(json!({"action": "goto_slide", "slide_number": 3})).unwrap();
match action {
SlideshowAction::GotoSlide { slide_number } => assert_eq!(slide_number, 3),
_ => panic!("Expected GotoSlide"),
}
}
#[test]
fn test_deserialize_laser() {
let action: SlideshowAction = serde_json::from_value(json!({
"action": "laser", "x": 50.0, "y": 75.0
})).unwrap();
match action {
SlideshowAction::Laser { x, y, .. } => {
assert_eq!(x, 50.0);
assert_eq!(y, 75.0);
}
_ => panic!("Expected Laser"),
}
}
#[test]
fn test_deserialize_autoplay() {
let action: SlideshowAction = serde_json::from_value(json!({"action": "auto_play"})).unwrap();
match action {
SlideshowAction::AutoPlay { interval_ms } => assert_eq!(interval_ms, 5000),
_ => panic!("Expected AutoPlay"),
}
}
#[test]
fn test_deserialize_invalid_action() {
let result = serde_json::from_value::<SlideshowAction>(json!({"action": "nonexistent"}));
assert!(result.is_err());
}
// === ContentBlock Deserialization ===
#[test]
fn test_content_block_text() {
let block: ContentBlock = serde_json::from_value(json!({
"type": "text", "text": "Hello"
})).unwrap();
match block {
ContentBlock::Text { text, style } => {
assert_eq!(text, "Hello");
assert!(style.is_none());
}
_ => panic!("Expected Text"),
}
}
#[test]
fn test_content_block_list() {
let block: ContentBlock = serde_json::from_value(json!({
"type": "list", "items": ["A", "B"], "ordered": true
})).unwrap();
match block {
ContentBlock::List { items, ordered } => {
assert_eq!(items, vec!["A", "B"]);
assert!(ordered);
}
_ => panic!("Expected List"),
}
}
#[test]
fn test_content_block_code() {
let block: ContentBlock = serde_json::from_value(json!({
"type": "code", "code": "fn main() {}", "language": "rust"
})).unwrap();
match block {
ContentBlock::Code { code, language } => {
assert_eq!(code, "fn main() {}");
assert_eq!(language, Some("rust".to_string()));
}
_ => panic!("Expected Code"),
}
}
#[test]
fn test_content_block_table() {
let block: ContentBlock = serde_json::from_value(json!({
"type": "table",
"headers": ["Name", "Age"],
"rows": [["Alice", "30"]]
})).unwrap();
match block {
ContentBlock::Table { headers, rows } => {
assert_eq!(headers, vec!["Name", "Age"]);
assert_eq!(rows, vec![vec!["Alice", "30"]]);
}
_ => panic!("Expected Table"),
}
}
// === Hand trait via execute ===
#[tokio::test]
async fn test_hand_execute_dispatch() {
let hand = SlideshowHand::with_slides_async(vec![
SlideContent { title: "S1".to_string(), subtitle: None, content: vec![], notes: None, background: None },
SlideContent { title: "S2".to_string(), subtitle: None, content: vec![], notes: None, background: None },
]).await;
let ctx = HandContext::default();
let result = hand.execute(&ctx, json!({"action": "next_slide"})).await.unwrap();
assert!(result.success);
assert_eq!(result.output["current_slide"], 1);
}
#[tokio::test]
async fn test_hand_execute_invalid_action() {
let hand = SlideshowHand::new();
let ctx = HandContext::default();
let result = hand.execute(&ctx, json!({"action": "invalid"})).await.unwrap();
assert!(!result.success);
}
// === add_slide helper ===
#[tokio::test]
async fn test_add_slide() {
let hand = SlideshowHand::new();
hand.add_slide(SlideContent {
title: "Dynamic".to_string(), subtitle: None, content: vec![], notes: None, background: None,
}).await;
hand.add_slide(SlideContent {
title: "Dynamic 2".to_string(), subtitle: None, content: vec![], notes: None, background: None,
}).await;
let state = hand.get_state().await;
assert_eq!(state.total_slides, 2);
assert_eq!(state.slides.len(), 2);
}
}

View File

@@ -1,442 +0,0 @@
//! Speech Hand - Text-to-Speech synthesis capabilities
//!
//! Provides speech synthesis for teaching:
//! - speak: Convert text to speech
//! - speak_ssml: Advanced speech with SSML markup
//! - pause/resume/stop: Playback control
//! - list_voices: Get available voices
//! - set_voice: Configure voice settings
use async_trait::async_trait;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use std::sync::Arc;
use tokio::sync::RwLock;
use zclaw_types::Result;
use crate::{Hand, HandConfig, HandContext, HandResult, HandStatus};
/// TTS Provider types
#[derive(Debug, Clone, Serialize, Deserialize, Default)]
#[serde(rename_all = "lowercase")]
pub enum TtsProvider {
#[default]
Browser,
Azure,
OpenAI,
ElevenLabs,
Local,
}
/// Speech action types
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "action", rename_all = "snake_case")]
pub enum SpeechAction {
/// Speak text
Speak {
text: String,
#[serde(default)]
voice: Option<String>,
#[serde(default = "default_rate")]
rate: f32,
#[serde(default = "default_pitch")]
pitch: f32,
#[serde(default = "default_volume")]
volume: f32,
#[serde(default)]
language: Option<String>,
},
/// Speak with SSML markup
SpeakSsml {
ssml: String,
#[serde(default)]
voice: Option<String>,
},
/// Pause playback
Pause,
/// Resume playback
Resume,
/// Stop playback
Stop,
/// List available voices
ListVoices {
#[serde(default)]
language: Option<String>,
},
/// Set default voice
SetVoice {
voice: String,
#[serde(default)]
language: Option<String>,
},
/// Set provider
SetProvider {
provider: TtsProvider,
#[serde(default)]
api_key: Option<String>,
#[serde(default)]
region: Option<String>,
},
}
fn default_rate() -> f32 { 1.0 }
fn default_pitch() -> f32 { 1.0 }
fn default_volume() -> f32 { 1.0 }
/// Voice information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VoiceInfo {
pub id: String,
pub name: String,
pub language: String,
pub gender: String,
#[serde(default)]
pub preview_url: Option<String>,
}
/// Playback state
#[derive(Debug, Clone, Serialize, Deserialize, Default)]
pub enum PlaybackState {
#[default]
Idle,
Playing,
Paused,
}
/// Speech configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SpeechConfig {
pub provider: TtsProvider,
pub default_voice: Option<String>,
pub default_language: String,
pub default_rate: f32,
pub default_pitch: f32,
pub default_volume: f32,
}
impl Default for SpeechConfig {
fn default() -> Self {
Self {
provider: TtsProvider::Browser,
default_voice: None,
default_language: "zh-CN".to_string(),
default_rate: 1.0,
default_pitch: 1.0,
default_volume: 1.0,
}
}
}
/// Speech state
#[derive(Debug, Clone, Default)]
pub struct SpeechState {
pub config: SpeechConfig,
pub playback: PlaybackState,
pub current_text: Option<String>,
pub position_ms: u64,
pub available_voices: Vec<VoiceInfo>,
}
/// Speech Hand implementation
pub struct SpeechHand {
config: HandConfig,
state: Arc<RwLock<SpeechState>>,
}
impl SpeechHand {
/// Create a new speech hand
pub fn new() -> Self {
Self {
config: HandConfig {
id: "speech".to_string(),
name: "语音合成".to_string(),
description: "文本转语音合成输出".to_string(),
needs_approval: false,
dependencies: vec![],
input_schema: Some(serde_json::json!({
"type": "object",
"properties": {
"action": { "type": "string" },
"text": { "type": "string" },
"voice": { "type": "string" },
"rate": { "type": "number" },
}
})),
tags: vec!["audio".to_string(), "tts".to_string(), "education".to_string(), "demo".to_string()],
enabled: true,
max_concurrent: 0,
timeout_secs: 0,
},
state: Arc::new(RwLock::new(SpeechState {
config: SpeechConfig::default(),
playback: PlaybackState::Idle,
available_voices: Self::get_default_voices(),
..Default::default()
})),
}
}
/// Create with custom provider
pub fn with_provider(provider: TtsProvider) -> Self {
let hand = Self::new();
let mut state = hand.state.blocking_write();
state.config.provider = provider;
drop(state);
hand
}
/// Get default voices
fn get_default_voices() -> Vec<VoiceInfo> {
vec![
VoiceInfo {
id: "zh-CN-XiaoxiaoNeural".to_string(),
name: "Xiaoxiao".to_string(),
language: "zh-CN".to_string(),
gender: "female".to_string(),
preview_url: None,
},
VoiceInfo {
id: "zh-CN-YunxiNeural".to_string(),
name: "Yunxi".to_string(),
language: "zh-CN".to_string(),
gender: "male".to_string(),
preview_url: None,
},
VoiceInfo {
id: "en-US-JennyNeural".to_string(),
name: "Jenny".to_string(),
language: "en-US".to_string(),
gender: "female".to_string(),
preview_url: None,
},
VoiceInfo {
id: "en-US-GuyNeural".to_string(),
name: "Guy".to_string(),
language: "en-US".to_string(),
gender: "male".to_string(),
preview_url: None,
},
]
}
/// Execute a speech action
pub async fn execute_action(&self, action: SpeechAction) -> Result<HandResult> {
let mut state = self.state.write().await;
match action {
SpeechAction::Speak { text, voice, rate, pitch, volume, language } => {
let voice_id = voice.or(state.config.default_voice.clone())
.unwrap_or_else(|| "default".to_string());
let lang = language.unwrap_or_else(|| state.config.default_language.clone());
let actual_rate = if rate == 1.0 { state.config.default_rate } else { rate };
let actual_pitch = if pitch == 1.0 { state.config.default_pitch } else { pitch };
let actual_volume = if volume == 1.0 { state.config.default_volume } else { volume };
state.playback = PlaybackState::Playing;
state.current_text = Some(text.clone());
// Determine TTS method based on provider:
// - Browser: frontend uses Web Speech API (zero deps, works offline)
// - OpenAI: frontend calls speech_tts command (high-quality, needs API key)
// - Others: future support
let tts_method = match state.config.provider {
TtsProvider::Browser => "browser",
TtsProvider::OpenAI => "openai_api",
TtsProvider::Azure => "azure_api",
TtsProvider::ElevenLabs => "elevenlabs_api",
TtsProvider::Local => "local_engine",
};
let estimated_duration_ms = (text.chars().count() as f64 / 5.0 * 1000.0) as u64;
Ok(HandResult::success(serde_json::json!({
"status": "speaking",
"tts_method": tts_method,
"text": text,
"voice": voice_id,
"language": lang,
"rate": actual_rate,
"pitch": actual_pitch,
"volume": actual_volume,
"provider": format!("{:?}", state.config.provider).to_lowercase(),
"duration_ms": estimated_duration_ms,
"instruction": "Frontend should play this via TTS engine"
})))
}
SpeechAction::SpeakSsml { ssml, voice } => {
let voice_id = voice.or(state.config.default_voice.clone())
.unwrap_or_else(|| "default".to_string());
state.playback = PlaybackState::Playing;
state.current_text = Some(ssml.clone());
Ok(HandResult::success(serde_json::json!({
"status": "speaking_ssml",
"ssml": ssml,
"voice": voice_id,
"provider": state.config.provider,
})))
}
SpeechAction::Pause => {
state.playback = PlaybackState::Paused;
Ok(HandResult::success(serde_json::json!({
"status": "paused",
"position_ms": state.position_ms,
})))
}
SpeechAction::Resume => {
state.playback = PlaybackState::Playing;
Ok(HandResult::success(serde_json::json!({
"status": "resumed",
"position_ms": state.position_ms,
})))
}
SpeechAction::Stop => {
state.playback = PlaybackState::Idle;
state.current_text = None;
state.position_ms = 0;
Ok(HandResult::success(serde_json::json!({
"status": "stopped",
})))
}
SpeechAction::ListVoices { language } => {
let voices: Vec<_> = state.available_voices.iter()
.filter(|v| {
language.as_ref()
.map(|l| v.language.starts_with(l))
.unwrap_or(true)
})
.cloned()
.collect();
Ok(HandResult::success(serde_json::json!({
"voices": voices,
"count": voices.len(),
})))
}
SpeechAction::SetVoice { voice, language } => {
state.config.default_voice = Some(voice.clone());
if let Some(lang) = language {
state.config.default_language = lang;
}
Ok(HandResult::success(serde_json::json!({
"status": "voice_set",
"voice": voice,
"language": state.config.default_language,
})))
}
SpeechAction::SetProvider { provider, api_key, region: _ } => {
state.config.provider = provider.clone();
// In real implementation, would configure provider
Ok(HandResult::success(serde_json::json!({
"status": "provider_set",
"provider": provider,
"configured": api_key.is_some(),
})))
}
}
}
/// Get current state
pub async fn get_state(&self) -> SpeechState {
self.state.read().await.clone()
}
}
impl Default for SpeechHand {
fn default() -> Self {
Self::new()
}
}
#[async_trait]
impl Hand for SpeechHand {
fn config(&self) -> &HandConfig {
&self.config
}
async fn execute(&self, _context: &HandContext, input: Value) -> Result<HandResult> {
let action: SpeechAction = match serde_json::from_value(input) {
Ok(a) => a,
Err(e) => {
return Ok(HandResult::error(format!("Invalid speech action: {}", e)));
}
};
self.execute_action(action).await
}
fn status(&self) -> HandStatus {
HandStatus::Idle
}
}
#[cfg(test)]
mod tests {
use super::*;
#[tokio::test]
async fn test_speech_creation() {
let hand = SpeechHand::new();
assert_eq!(hand.config().id, "speech");
}
#[tokio::test]
async fn test_speak() {
let hand = SpeechHand::new();
let action = SpeechAction::Speak {
text: "Hello, world!".to_string(),
voice: None,
rate: 1.0,
pitch: 1.0,
volume: 1.0,
language: None,
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
}
#[tokio::test]
async fn test_pause_resume() {
let hand = SpeechHand::new();
// Speak first
hand.execute_action(SpeechAction::Speak {
text: "Test".to_string(),
voice: None, rate: 1.0, pitch: 1.0, volume: 1.0, language: None,
}).await.unwrap();
// Pause
let result = hand.execute_action(SpeechAction::Pause).await.unwrap();
assert!(result.success);
// Resume
let result = hand.execute_action(SpeechAction::Resume).await.unwrap();
assert!(result.success);
}
#[tokio::test]
async fn test_list_voices() {
let hand = SpeechHand::new();
let action = SpeechAction::ListVoices { language: Some("zh".to_string()) };
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
}
#[tokio::test]
async fn test_set_voice() {
let hand = SpeechHand::new();
let action = SpeechAction::SetVoice {
voice: "zh-CN-XiaoxiaoNeural".to_string(),
language: Some("zh-CN".to_string()),
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
let state = hand.get_state().await;
assert_eq!(state.config.default_voice, Some("zh-CN-XiaoxiaoNeural".to_string()));
}
}

View File

@@ -191,6 +191,8 @@ pub enum TwitterAction {
Following { user_id: String, max_results: Option<u32> }, Following { user_id: String, max_results: Option<u32> },
#[serde(rename = "check_credentials")] #[serde(rename = "check_credentials")]
CheckCredentials, CheckCredentials,
#[serde(rename = "set_credentials")]
SetCredentials { credentials: TwitterCredentials },
} }
/// Twitter Hand implementation /// Twitter Hand implementation
@@ -200,14 +202,83 @@ pub struct TwitterHand {
} }
impl TwitterHand { impl TwitterHand {
/// Credential file path relative to app data dir
const CREDS_FILE_NAME: &'static str = "twitter-credentials.json";
/// Get the credentials file path
fn creds_path() -> Option<std::path::PathBuf> {
dirs::data_dir().map(|d| d.join("zclaw").join("hands").join(Self::CREDS_FILE_NAME))
}
/// Load credentials from disk (silent — logs errors, returns None on failure)
fn load_credentials_from_disk() -> Option<TwitterCredentials> {
let path = Self::creds_path()?;
if !path.exists() {
return None;
}
match std::fs::read_to_string(&path) {
Ok(data) => match serde_json::from_str(&data) {
Ok(creds) => {
tracing::info!("[TwitterHand] Loaded persisted credentials from {:?}", path);
Some(creds)
}
Err(e) => {
tracing::warn!("[TwitterHand] Failed to parse credentials file: {}", e);
None
}
},
Err(e) => {
tracing::warn!("[TwitterHand] Failed to read credentials file: {}", e);
None
}
}
}
/// Save credentials to disk (best-effort, logs errors)
fn save_credentials_to_disk(creds: &TwitterCredentials) {
let path = match Self::creds_path() {
Some(p) => p,
None => {
tracing::warn!("[TwitterHand] Cannot determine credentials file path");
return;
}
};
if let Some(parent) = path.parent() {
if let Err(e) = std::fs::create_dir_all(parent) {
tracing::warn!("[TwitterHand] Failed to create credentials dir: {}", e);
return;
}
}
match serde_json::to_string_pretty(creds) {
Ok(data) => {
if let Err(e) = std::fs::write(&path, data) {
tracing::warn!("[TwitterHand] Failed to write credentials file: {}", e);
} else {
tracing::info!("[TwitterHand] Credentials persisted to {:?}", path);
}
}
Err(e) => {
tracing::warn!("[TwitterHand] Failed to serialize credentials: {}", e);
}
}
}
/// Create a new Twitter hand /// Create a new Twitter hand
pub fn new() -> Self { pub fn new() -> Self {
// Try to load persisted credentials
let loaded = Self::load_credentials_from_disk();
if loaded.is_some() {
tracing::info!("[TwitterHand] Restored credentials from previous session");
}
Self { Self {
config: HandConfig { config: HandConfig {
id: "twitter".to_string(), id: "twitter".to_string(),
name: "Twitter 自动化".to_string(), name: "Twitter 自动化".to_string(),
description: "Twitter/X 自动化能力,发布、搜索和管理内容".to_string(), description: "Twitter/X 自动化能力,发布、搜索和管理内容".to_string(),
needs_approval: true, // Twitter actions need approval needs_approval: true,
dependencies: vec!["twitter_api_key".to_string()], dependencies: vec!["twitter_api_key".to_string()],
input_schema: Some(serde_json::json!({ input_schema: Some(serde_json::json!({
"type": "object", "type": "object",
@@ -275,12 +346,13 @@ impl TwitterHand {
max_concurrent: 0, max_concurrent: 0,
timeout_secs: 0, timeout_secs: 0,
}, },
credentials: Arc::new(RwLock::new(None)), credentials: Arc::new(RwLock::new(loaded)),
} }
} }
/// Set credentials /// Set credentials (also persists to disk)
pub async fn set_credentials(&self, creds: TwitterCredentials) { pub async fn set_credentials(&self, creds: TwitterCredentials) {
Self::save_credentials_to_disk(&creds);
let mut c = self.credentials.write().await; let mut c = self.credentials.write().await;
*c = Some(creds); *c = Some(creds);
} }
@@ -765,6 +837,13 @@ impl Hand for TwitterHand {
TwitterAction::Followers { user_id, max_results } => self.execute_followers(&user_id, max_results).await?, TwitterAction::Followers { user_id, max_results } => self.execute_followers(&user_id, max_results).await?,
TwitterAction::Following { user_id, max_results } => self.execute_following(&user_id, max_results).await?, TwitterAction::Following { user_id, max_results } => self.execute_following(&user_id, max_results).await?,
TwitterAction::CheckCredentials => self.execute_check_credentials().await?, TwitterAction::CheckCredentials => self.execute_check_credentials().await?,
TwitterAction::SetCredentials { credentials } => {
self.set_credentials(credentials).await;
json!({
"success": true,
"message": "Twitter 凭据已设置并持久化。重启后自动恢复。"
})
}
}; };
let duration_ms = start.elapsed().as_millis() as u64; let duration_ms = start.elapsed().as_millis() as u64;
@@ -785,9 +864,13 @@ impl Hand for TwitterHand {
fn check_dependencies(&self) -> Result<Vec<String>> { fn check_dependencies(&self) -> Result<Vec<String>> {
let mut missing = Vec::new(); let mut missing = Vec::new();
// Check if credentials are configured (synchronously) // Synchronous check: if credentials were loaded from disk, dependency is met
// This is a simplified check; actual async check would require runtime match self.credentials.try_read() {
missing.push("Twitter API credentials required".to_string()); Ok(creds) if creds.is_some() => {},
_ => {
missing.push("Twitter API credentials required (use set_credentials action to configure)".to_string());
}
}
Ok(missing) Ok(missing)
} }
@@ -1058,6 +1141,62 @@ mod tests {
assert!(result.is_err()); assert!(result.is_err());
} }
#[test]
fn test_set_credentials_action_deserialize() {
let json = json!({
"action": "set_credentials",
"credentials": {
"apiKey": "test-key",
"apiSecret": "test-secret",
"accessToken": "test-token",
"accessTokenSecret": "test-token-secret",
"bearerToken": "test-bearer"
}
});
let action: TwitterAction = serde_json::from_value(json).unwrap();
match action {
TwitterAction::SetCredentials { credentials } => {
assert_eq!(credentials.api_key, "test-key");
assert_eq!(credentials.api_secret, "test-secret");
assert_eq!(credentials.bearer_token, Some("test-bearer".to_string()));
}
_ => panic!("Expected SetCredentials"),
}
}
#[tokio::test]
async fn test_set_credentials_persists_and_restores() {
// Use a temporary directory to avoid polluting real credentials
let temp_dir = std::env::temp_dir().join("zclaw_test_twitter_creds");
let _ = std::fs::create_dir_all(&temp_dir);
let hand = TwitterHand::new();
// Set credentials
let creds = TwitterCredentials {
api_key: "test-key".to_string(),
api_secret: "test-secret".to_string(),
access_token: "test-token".to_string(),
access_token_secret: "test-secret".to_string(),
bearer_token: Some("test-bearer".to_string()),
};
hand.set_credentials(creds.clone()).await;
// Verify in-memory
let loaded = hand.get_credentials().await;
assert!(loaded.is_some());
assert_eq!(loaded.unwrap().api_key, "test-key");
// Verify file was written
let path = TwitterHand::creds_path();
assert!(path.is_some());
let path = path.unwrap();
assert!(path.exists(), "Credentials file should exist at {:?}", path);
// Clean up
let _ = std::fs::remove_file(&path);
}
// === Serialization Roundtrip === // === Serialization Roundtrip ===
#[test] #[test]

View File

@@ -1,422 +0,0 @@
//! Whiteboard Hand - Drawing and annotation capabilities
//!
//! Provides whiteboard drawing actions for teaching:
//! - draw_text: Draw text on the whiteboard
//! - draw_shape: Draw shapes (rectangle, circle, arrow, etc.)
//! - draw_line: Draw lines and curves
//! - draw_chart: Draw charts (bar, line, pie)
//! - draw_latex: Render LaTeX formulas
//! - draw_table: Draw data tables
//! - clear: Clear the whiteboard
//! - export: Export as image
use async_trait::async_trait;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use zclaw_types::Result;
use crate::{Hand, HandConfig, HandContext, HandResult, HandStatus};
/// Whiteboard action types
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "action", rename_all = "snake_case")]
pub enum WhiteboardAction {
/// Draw text
DrawText {
x: f64,
y: f64,
text: String,
#[serde(default = "default_font_size")]
font_size: u32,
#[serde(default)]
color: Option<String>,
#[serde(default)]
font_family: Option<String>,
},
/// Draw a shape
DrawShape {
shape: ShapeType,
x: f64,
y: f64,
width: f64,
height: f64,
#[serde(default)]
fill: Option<String>,
#[serde(default)]
stroke: Option<String>,
#[serde(default = "default_stroke_width")]
stroke_width: u32,
},
/// Draw a line
DrawLine {
points: Vec<Point>,
#[serde(default)]
color: Option<String>,
#[serde(default = "default_stroke_width")]
stroke_width: u32,
},
/// Draw a chart
DrawChart {
chart_type: ChartType,
data: ChartData,
x: f64,
y: f64,
width: f64,
height: f64,
#[serde(default)]
title: Option<String>,
},
/// Draw LaTeX formula
DrawLatex {
latex: String,
x: f64,
y: f64,
#[serde(default = "default_font_size")]
font_size: u32,
#[serde(default)]
color: Option<String>,
},
/// Draw a table
DrawTable {
headers: Vec<String>,
rows: Vec<Vec<String>>,
x: f64,
y: f64,
#[serde(default)]
column_widths: Option<Vec<f64>>,
},
/// Erase area
Erase {
x: f64,
y: f64,
width: f64,
height: f64,
},
/// Clear whiteboard
Clear,
/// Undo last action
Undo,
/// Redo last undone action
Redo,
/// Export as image
Export {
#[serde(default = "default_export_format")]
format: String,
},
}
fn default_font_size() -> u32 { 16 }
fn default_stroke_width() -> u32 { 2 }
fn default_export_format() -> String { "png".to_string() }
/// Shape types
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(rename_all = "snake_case")]
pub enum ShapeType {
Rectangle,
RoundedRectangle,
Circle,
Ellipse,
Triangle,
Arrow,
Star,
Checkmark,
Cross,
}
/// Point for line drawing
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Point {
pub x: f64,
pub y: f64,
}
/// Chart types
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(rename_all = "snake_case")]
pub enum ChartType {
Bar,
Line,
Pie,
Scatter,
Area,
Radar,
}
/// Chart data
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ChartData {
pub labels: Vec<String>,
pub datasets: Vec<Dataset>,
}
/// Dataset for charts
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Dataset {
pub label: String,
pub values: Vec<f64>,
#[serde(default)]
pub color: Option<String>,
}
/// Whiteboard state (for undo/redo)
#[derive(Debug, Clone, Default)]
pub struct WhiteboardState {
pub actions: Vec<WhiteboardAction>,
pub undone: Vec<WhiteboardAction>,
pub canvas_width: f64,
pub canvas_height: f64,
}
/// Whiteboard Hand implementation
pub struct WhiteboardHand {
config: HandConfig,
state: std::sync::Arc<tokio::sync::RwLock<WhiteboardState>>,
}
impl WhiteboardHand {
/// Create a new whiteboard hand
pub fn new() -> Self {
Self {
config: HandConfig {
id: "whiteboard".to_string(),
name: "白板".to_string(),
description: "在虚拟白板上绘制和标注".to_string(),
needs_approval: false,
dependencies: vec![],
input_schema: Some(serde_json::json!({
"type": "object",
"properties": {
"action": { "type": "string" },
"x": { "type": "number" },
"y": { "type": "number" },
"text": { "type": "string" },
}
})),
tags: vec!["presentation".to_string(), "education".to_string()],
enabled: true,
max_concurrent: 0,
timeout_secs: 0,
},
state: std::sync::Arc::new(tokio::sync::RwLock::new(WhiteboardState {
canvas_width: 1920.0,
canvas_height: 1080.0,
..Default::default()
})),
}
}
/// Create with custom canvas size
pub fn with_size(width: f64, height: f64) -> Self {
let hand = Self::new();
let mut state = hand.state.blocking_write();
state.canvas_width = width;
state.canvas_height = height;
drop(state);
hand
}
/// Execute a whiteboard action
pub async fn execute_action(&self, action: WhiteboardAction) -> Result<HandResult> {
let mut state = self.state.write().await;
match &action {
WhiteboardAction::Clear => {
state.actions.clear();
state.undone.clear();
return Ok(HandResult::success(serde_json::json!({
"status": "cleared",
"action_count": 0
})));
}
WhiteboardAction::Undo => {
if let Some(last) = state.actions.pop() {
state.undone.push(last);
return Ok(HandResult::success(serde_json::json!({
"status": "undone",
"remaining_actions": state.actions.len()
})));
}
return Ok(HandResult::success(serde_json::json!({
"status": "no_action_to_undo"
})));
}
WhiteboardAction::Redo => {
if let Some(redone) = state.undone.pop() {
state.actions.push(redone);
return Ok(HandResult::success(serde_json::json!({
"status": "redone",
"total_actions": state.actions.len()
})));
}
return Ok(HandResult::success(serde_json::json!({
"status": "no_action_to_redo"
})));
}
WhiteboardAction::Export { format } => {
// In real implementation, would render to image
return Ok(HandResult::success(serde_json::json!({
"status": "exported",
"format": format,
"data_url": format!("data:image/{};base64,<rendered_data>", format)
})));
}
_ => {
// Regular drawing action
state.actions.push(action.clone());
return Ok(HandResult::success(serde_json::json!({
"status": "drawn",
"action": action,
"total_actions": state.actions.len()
})));
}
}
}
/// Get current state
pub async fn get_state(&self) -> WhiteboardState {
self.state.read().await.clone()
}
/// Get all actions
pub async fn get_actions(&self) -> Vec<WhiteboardAction> {
self.state.read().await.actions.clone()
}
}
impl Default for WhiteboardHand {
fn default() -> Self {
Self::new()
}
}
#[async_trait]
impl Hand for WhiteboardHand {
fn config(&self) -> &HandConfig {
&self.config
}
async fn execute(&self, _context: &HandContext, input: Value) -> Result<HandResult> {
// Parse action from input
let action: WhiteboardAction = match serde_json::from_value(input.clone()) {
Ok(a) => a,
Err(e) => {
return Ok(HandResult::error(format!("Invalid whiteboard action: {}", e)));
}
};
self.execute_action(action).await
}
fn status(&self) -> HandStatus {
// Check if there are any actions
HandStatus::Idle
}
}
#[cfg(test)]
mod tests {
use super::*;
#[tokio::test]
async fn test_whiteboard_creation() {
let hand = WhiteboardHand::new();
assert_eq!(hand.config().id, "whiteboard");
}
#[tokio::test]
async fn test_draw_text() {
let hand = WhiteboardHand::new();
let action = WhiteboardAction::DrawText {
x: 100.0,
y: 100.0,
text: "Hello World".to_string(),
font_size: 24,
color: Some("#333333".to_string()),
font_family: None,
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
let state = hand.get_state().await;
assert_eq!(state.actions.len(), 1);
}
#[tokio::test]
async fn test_draw_shape() {
let hand = WhiteboardHand::new();
let action = WhiteboardAction::DrawShape {
shape: ShapeType::Rectangle,
x: 50.0,
y: 50.0,
width: 200.0,
height: 100.0,
fill: Some("#4CAF50".to_string()),
stroke: None,
stroke_width: 2,
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
}
#[tokio::test]
async fn test_undo_redo() {
let hand = WhiteboardHand::new();
// Draw something
hand.execute_action(WhiteboardAction::DrawText {
x: 0.0, y: 0.0, text: "Test".to_string(), font_size: 16, color: None, font_family: None,
}).await.unwrap();
// Undo
let result = hand.execute_action(WhiteboardAction::Undo).await.unwrap();
assert!(result.success);
assert_eq!(hand.get_state().await.actions.len(), 0);
// Redo
let result = hand.execute_action(WhiteboardAction::Redo).await.unwrap();
assert!(result.success);
assert_eq!(hand.get_state().await.actions.len(), 1);
}
#[tokio::test]
async fn test_clear() {
let hand = WhiteboardHand::new();
// Draw something
hand.execute_action(WhiteboardAction::DrawText {
x: 0.0, y: 0.0, text: "Test".to_string(), font_size: 16, color: None, font_family: None,
}).await.unwrap();
// Clear
let result = hand.execute_action(WhiteboardAction::Clear).await.unwrap();
assert!(result.success);
assert_eq!(hand.get_state().await.actions.len(), 0);
}
#[tokio::test]
async fn test_chart() {
let hand = WhiteboardHand::new();
let action = WhiteboardAction::DrawChart {
chart_type: ChartType::Bar,
data: ChartData {
labels: vec!["A".to_string(), "B".to_string(), "C".to_string()],
datasets: vec![Dataset {
label: "Values".to_string(),
values: vec![10.0, 20.0, 15.0],
color: Some("#2196F3".to_string()),
}],
},
x: 100.0,
y: 100.0,
width: 400.0,
height: 300.0,
title: Some("Test Chart".to_string()),
};
let result = hand.execute_action(action).await.unwrap();
assert!(result.success);
}
}

View File

@@ -9,8 +9,6 @@ description = "ZCLAW kernel - central coordinator for all subsystems"
[features] [features]
default = [] default = []
# Enable multi-agent orchestration (Director, A2A protocol)
multi-agent = ["zclaw-protocols/a2a"]
[dependencies] [dependencies]
zclaw-types = { workspace = true } zclaw-types = { workspace = true }
@@ -19,6 +17,7 @@ zclaw-runtime = { workspace = true }
zclaw-protocols = { workspace = true } zclaw-protocols = { workspace = true }
zclaw-hands = { workspace = true } zclaw-hands = { workspace = true }
zclaw-skills = { workspace = true } zclaw-skills = { workspace = true }
zclaw-growth = { workspace = true }
tokio = { workspace = true } tokio = { workspace = true }
tokio-stream = { workspace = true } tokio-stream = { workspace = true }

View File

@@ -30,7 +30,7 @@ impl Default for ApiProtocol {
/// ///
/// This is the single source of truth for LLM configuration. /// This is the single source of truth for LLM configuration.
/// Model ID is passed directly to the API without any transformation. /// Model ID is passed directly to the API without any transformation.
#[derive(Debug, Clone, Serialize, Deserialize)] #[derive(Clone, Serialize, Deserialize)]
pub struct LlmConfig { pub struct LlmConfig {
/// API base URL (e.g., "https://api.openai.com/v1") /// API base URL (e.g., "https://api.openai.com/v1")
pub base_url: String, pub base_url: String,
@@ -61,6 +61,20 @@ pub struct LlmConfig {
pub context_window: u32, pub context_window: u32,
} }
impl std::fmt::Debug for LlmConfig {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("LlmConfig")
.field("base_url", &self.base_url)
.field("api_key", &"***REDACTED***")
.field("model", &self.model)
.field("api_protocol", &self.api_protocol)
.field("max_tokens", &self.max_tokens)
.field("temperature", &self.temperature)
.field("context_window", &self.context_window)
.finish()
}
}
impl LlmConfig { impl LlmConfig {
/// Create a new LLM config /// Create a new LLM config
pub fn new(base_url: impl Into<String>, api_key: impl Into<String>, model: impl Into<String>) -> Self { pub fn new(base_url: impl Into<String>, api_key: impl Into<String>, model: impl Into<String>) -> Self {

View File

@@ -12,7 +12,7 @@
use std::sync::Arc; use std::sync::Arc;
use serde::{Deserialize, Serialize}; use serde::{Deserialize, Serialize};
use tokio::sync::{RwLock, Mutex, mpsc}; use tokio::sync::{RwLock, Mutex, mpsc, oneshot};
use zclaw_types::{AgentId, Result, ZclawError}; use zclaw_types::{AgentId, Result, ZclawError};
use zclaw_protocols::{A2aEnvelope, A2aMessageType, A2aRecipient, A2aRouter, A2aAgentProfile, A2aCapability}; use zclaw_protocols::{A2aEnvelope, A2aMessageType, A2aRecipient, A2aRouter, A2aAgentProfile, A2aCapability};
use zclaw_runtime::{LlmDriver, CompletionRequest}; use zclaw_runtime::{LlmDriver, CompletionRequest};
@@ -199,9 +199,9 @@ pub struct Director {
director_id: AgentId, director_id: AgentId,
/// Optional LLM driver for intelligent scheduling /// Optional LLM driver for intelligent scheduling
llm_driver: Option<Arc<dyn LlmDriver>>, llm_driver: Option<Arc<dyn LlmDriver>>,
/// Inbox for receiving responses (stores pending request IDs and their response channels) /// Pending request response channels (request_id → oneshot sender)
pending_requests: Arc<Mutex<std::collections::HashMap<String, mpsc::Sender<A2aEnvelope>>>>, pending_requests: Arc<Mutex<std::collections::HashMap<String, oneshot::Sender<A2aEnvelope>>>>,
/// Receiver for incoming messages /// Receiver for incoming messages (consumed by inbox reader task)
inbox: Arc<Mutex<Option<mpsc::Receiver<A2aEnvelope>>>>, inbox: Arc<Mutex<Option<mpsc::Receiver<A2aEnvelope>>>>,
} }
@@ -360,7 +360,7 @@ impl Director {
use std::time::{SystemTime, UNIX_EPOCH}; use std::time::{SystemTime, UNIX_EPOCH};
let now = SystemTime::now() let now = SystemTime::now()
.duration_since(UNIX_EPOCH) .duration_since(UNIX_EPOCH)
.unwrap() .expect("system clock is valid")
.as_nanos(); .as_nanos();
let idx = (now as usize) % agents.len(); let idx = (now as usize) % agents.len();
Some(agents[idx].clone()) Some(agents[idx].clone())
@@ -481,13 +481,16 @@ Respond with ONLY the number (1-{}) of the agent who should speak next. No expla
} }
/// Send message to selected agent and wait for response /// Send message to selected agent and wait for response
///
/// Uses oneshot channels to avoid deadlock: each call creates its own
/// response channel, and a shared inbox reader dispatches responses.
pub async fn send_to_agent( pub async fn send_to_agent(
&self, &self,
agent: &DirectorAgent, agent: &DirectorAgent,
message: String, message: String,
) -> Result<String> { ) -> Result<String> {
// Create a response channel for this request // Create a oneshot channel for this specific request's response
let (_response_tx, mut _response_rx) = mpsc::channel::<A2aEnvelope>(1); let (response_tx, response_rx) = oneshot::channel::<A2aEnvelope>();
let envelope = A2aEnvelope::new( let envelope = A2aEnvelope::new(
self.director_id.clone(), self.director_id.clone(),
@@ -500,50 +503,32 @@ Respond with ONLY the number (1-{}) of the agent who should speak next. No expla
}), }),
); );
// Store the request ID with its response channel // Store the oneshot sender so the inbox reader can dispatch to it
let request_id = envelope.id.clone(); let request_id = envelope.id.clone();
{ {
let mut pending = self.pending_requests.lock().await; let mut pending = self.pending_requests.lock().await;
pending.insert(request_id.clone(), _response_tx); pending.insert(request_id.clone(), response_tx);
} }
// Send the request // Send the request
self.router.route(envelope).await?; self.router.route(envelope).await?;
// Wait for response with timeout // Ensure the inbox reader is running
self.ensure_inbox_reader().await;
// Wait for response on our dedicated oneshot channel with timeout
let timeout_duration = std::time::Duration::from_secs(self.config.response_timeout); let timeout_duration = std::time::Duration::from_secs(self.config.response_timeout);
let request_id_clone = request_id.clone();
let response = tokio::time::timeout(timeout_duration, async { let response = tokio::time::timeout(timeout_duration, response_rx).await;
// Poll the inbox for responses
let mut inbox_guard = self.inbox.lock().await;
if let Some(ref mut rx) = *inbox_guard {
while let Some(msg) = rx.recv().await {
// Check if this is a response to our request
if msg.message_type == A2aMessageType::Response {
if let Some(ref reply_to) = msg.reply_to {
if reply_to == &request_id_clone {
// Found our response
return Some(msg);
}
}
}
// Not our response, continue waiting
// (In a real implementation, we'd re-queue non-matching messages)
}
}
None
}).await;
// Clean up pending request // Clean up pending request (sender already consumed on success)
{ {
let mut pending = self.pending_requests.lock().await; let mut pending = self.pending_requests.lock().await;
pending.remove(&request_id); pending.remove(&request_id);
} }
match response { match response {
Ok(Some(envelope)) => { Ok(Ok(envelope)) => {
// Extract response text from payload
let response_text = envelope.payload let response_text = envelope.payload
.get("response") .get("response")
.and_then(|v: &serde_json::Value| v.as_str()) .and_then(|v: &serde_json::Value| v.as_str())
@@ -551,7 +536,7 @@ Respond with ONLY the number (1-{}) of the agent who should speak next. No expla
.to_string(); .to_string();
Ok(response_text) Ok(response_text)
} }
Ok(None) => { Ok(Err(_)) => {
Err(ZclawError::Timeout("No response received".into())) Err(ZclawError::Timeout("No response received".into()))
} }
Err(_) => { Err(_) => {
@@ -563,6 +548,47 @@ Respond with ONLY the number (1-{}) of the agent who should speak next. No expla
} }
} }
/// Ensure the inbox reader task is running.
/// The inbox reader continuously reads from the shared inbox channel
/// and dispatches each response to the correct oneshot sender.
async fn ensure_inbox_reader(&self) {
// Quick check: if inbox has already been taken, reader is running
{
let inbox = self.inbox.lock().await;
if inbox.is_none() {
return; // Reader already spawned and consumed the receiver
}
}
// Take the receiver out (only once)
let rx = {
let mut inbox = self.inbox.lock().await;
inbox.take()
};
if let Some(mut rx) = rx {
let pending = self.pending_requests.clone();
tokio::spawn(async move {
while let Some(msg) = rx.recv().await {
// Find and dispatch to the correct oneshot sender
if msg.message_type == A2aMessageType::Response {
if let Some(ref reply_to) = msg.reply_to {
let reply_to_clone = reply_to.clone();
let mut pending_guard = pending.lock().await;
if let Some(sender) = pending_guard.remove(reply_to) {
// Send the response; if receiver already dropped, request was cancelled
if sender.send(msg).is_err() {
tracing::debug!("[Director] Response dropped: receiver cancelled for reply_to={}", reply_to_clone);
}
}
}
}
// Non-response messages are dropped (notifications, etc.)
}
});
}
}
/// Broadcast message to all agents /// Broadcast message to all agents
pub async fn broadcast(&self, message: String) -> Result<()> { pub async fn broadcast(&self, message: String) -> Result<()> {
let envelope = A2aEnvelope::new( let envelope = A2aEnvelope::new(
@@ -616,7 +642,9 @@ Respond with ONLY the number (1-{}) of the agent who should speak next. No expla
} }
if let Some(ref user_input) = input { if let Some(ref user_input) = input {
context.push_str(&format!("User: {}\n\n", user_input)); context.push_str("<user_input>\n");
context.push_str(&format!("{}\n", user_input));
context.push_str("</user_input>\n\n");
} }
// Add recent history // Add recent history
@@ -882,7 +910,9 @@ impl Director {
let prompt = format!( let prompt = format!(
r#"你是 ZCLAW 管家。请将以下用户需求拆解为 1-5 个具体子任务。 r#"你是 ZCLAW 管家。请将以下用户需求拆解为 1-5 个具体子任务。
用户需求:{} <user_request>
{}
</user_request>
请按 JSON 数组格式输出,每个元素包含: 请按 JSON 数组格式输出,每个元素包含:
- description: 子任务描述(中文) - description: 子任务描述(中文)

View File

@@ -17,8 +17,9 @@ impl EventBus {
/// Publish an event /// Publish an event
pub fn publish(&self, event: Event) { pub fn publish(&self, event: Event) {
// Ignore send errors (no subscribers) if let Err(e) = self.sender.send(event) {
let _ = self.sender.send(event); tracing::debug!("Event dropped (no subscribers or channel full): {:?}", e);
}
} }
/// Subscribe to events /// Subscribe to events

View File

@@ -14,7 +14,7 @@ use zclaw_types::Result;
/// HTML exporter /// HTML exporter
pub struct HtmlExporter { pub struct HtmlExporter {
/// Template name (reserved for future template support) /// Template name (reserved for future template support)
#[allow(dead_code)] // TODO: Implement template-based HTML export #[allow(dead_code)] // @reserved: post-release template-based HTML export
template: String, template: String,
} }

View File

@@ -490,7 +490,7 @@ impl PptxExporter {
paths.sort(); paths.sort();
for path in paths { for path in paths {
let content = files.get(path).unwrap(); let content = files.get(path).expect("path comes from files.keys(), must exist");
let options = SimpleFileOptions::default() let options = SimpleFileOptions::default()
.compression_method(zip::CompressionMethod::Deflated); .compression_method(zip::CompressionMethod::Deflated);

View File

@@ -243,7 +243,7 @@ fn clean_fallback_response(text: &str) -> String {
fn current_timestamp_millis() -> i64 { fn current_timestamp_millis() -> i64 {
std::time::SystemTime::now() std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH) .duration_since(std::time::UNIX_EPOCH)
.unwrap() .expect("system clock is valid")
.as_millis() as i64 .as_millis() as i64
} }

View File

@@ -557,7 +557,7 @@ Use Chinese if the topic is in Chinese. Include metaphors that relate to everyda
.join("\n") .join("\n")
} }
#[allow(dead_code)] #[allow(dead_code)] // @reserved: instance-method convenience wrapper for static helper
fn extract_text_from_response(&self, response: &CompletionResponse) -> String { fn extract_text_from_response(&self, response: &CompletionResponse) -> String {
Self::extract_text_from_response_static(response) Self::extract_text_from_response_static(response)
} }
@@ -882,7 +882,7 @@ fn current_timestamp() -> i64 {
use std::time::{SystemTime, UNIX_EPOCH}; use std::time::{SystemTime, UNIX_EPOCH};
SystemTime::now() SystemTime::now()
.duration_since(UNIX_EPOCH) .duration_since(UNIX_EPOCH)
.unwrap() .expect("system clock is valid")
.as_millis() as i64 .as_millis() as i64
} }

View File

@@ -1,16 +1,10 @@
//! A2A (Agent-to-Agent) messaging //! A2A (Agent-to-Agent) messaging
//!
//! All items in this module are gated by the `multi-agent` feature flag.
#[cfg(feature = "multi-agent")]
use zclaw_types::{AgentId, Capability, Event, Result}; use zclaw_types::{AgentId, Capability, Event, Result};
#[cfg(feature = "multi-agent")]
use zclaw_protocols::{A2aAgentProfile, A2aCapability, A2aEnvelope, A2aMessageType, A2aRecipient}; use zclaw_protocols::{A2aAgentProfile, A2aCapability, A2aEnvelope, A2aMessageType, A2aRecipient};
#[cfg(feature = "multi-agent")]
use super::Kernel; use super::Kernel;
#[cfg(feature = "multi-agent")]
impl Kernel { impl Kernel {
// ============================================================ // ============================================================
// A2A (Agent-to-Agent) Messaging // A2A (Agent-to-Agent) Messaging

View File

@@ -3,11 +3,12 @@
use std::pin::Pin; use std::pin::Pin;
use std::sync::Arc; use std::sync::Arc;
use async_trait::async_trait; use async_trait::async_trait;
use serde_json::Value; use serde_json::{json, Value};
use zclaw_runtime::{LlmDriver, tool::SkillExecutor}; use zclaw_runtime::{LlmDriver, tool::{SkillExecutor, HandExecutor}};
use zclaw_skills::{SkillRegistry, LlmCompleter}; use zclaw_skills::{SkillRegistry, LlmCompleter, SkillCompletion, SkillToolCall};
use zclaw_types::Result; use zclaw_hands::HandRegistry;
use zclaw_types::{AgentId, Result, ToolDefinition};
/// Adapter that bridges `zclaw_runtime::LlmDriver` -> `zclaw_skills::LlmCompleter` /// Adapter that bridges `zclaw_runtime::LlmDriver` -> `zclaw_skills::LlmCompleter`
pub(crate) struct LlmDriverAdapter { pub(crate) struct LlmDriverAdapter {
@@ -43,18 +44,111 @@ impl LlmCompleter for LlmDriverAdapter {
Ok(text) Ok(text)
}) })
} }
fn complete_with_tools(
&self,
prompt: &str,
system_prompt: Option<&str>,
tools: Vec<ToolDefinition>,
) -> Pin<Box<dyn std::future::Future<Output = std::result::Result<SkillCompletion, String>> + Send + '_>> {
let driver = self.driver.clone();
let prompt = prompt.to_string();
let system = system_prompt.map(|s| s.to_string());
let max_tokens = self.max_tokens;
let temperature = self.temperature;
Box::pin(async move {
let mut messages = Vec::new();
messages.push(zclaw_types::Message::user(prompt));
let request = zclaw_runtime::CompletionRequest {
model: String::new(),
system,
messages,
tools,
max_tokens: Some(max_tokens),
temperature: Some(temperature),
stop: Vec::new(),
stream: false,
thinking_enabled: false,
reasoning_effort: None,
plan_mode: false,
};
let response = driver.complete(request).await
.map_err(|e| format!("LLM completion error: {}", e))?;
let mut text_parts = Vec::new();
let mut tool_calls = Vec::new();
for block in &response.content {
match block {
zclaw_runtime::ContentBlock::Text { text } => {
text_parts.push(text.clone());
}
zclaw_runtime::ContentBlock::ToolUse { id, name, input } => {
tool_calls.push(SkillToolCall {
id: id.clone(),
name: name.clone(),
input: input.clone(),
});
}
_ => {}
}
}
Ok(SkillCompletion {
text: text_parts.join(""),
tool_calls,
})
})
}
} }
/// Skill executor implementation for Kernel /// Skill executor implementation for Kernel
pub struct KernelSkillExecutor { pub struct KernelSkillExecutor {
pub(crate) skills: Arc<SkillRegistry>, pub(crate) skills: Arc<SkillRegistry>,
pub(crate) llm: Arc<dyn LlmCompleter>, pub(crate) llm: Arc<dyn LlmCompleter>,
/// Shared tool registry, updated before each skill execution from the
/// agent loop's freshly-built registry. Uses std::sync because reads
/// happen from async code but writes are brief and infrequent.
pub(crate) tool_registry: std::sync::RwLock<Option<zclaw_runtime::ToolRegistry>>,
} }
impl KernelSkillExecutor { impl KernelSkillExecutor {
pub fn new(skills: Arc<SkillRegistry>, driver: Arc<dyn LlmDriver>) -> Self { pub fn new(skills: Arc<SkillRegistry>, driver: Arc<dyn LlmDriver>) -> Self {
let llm: Arc<dyn zclaw_skills::LlmCompleter> = Arc::new(LlmDriverAdapter { driver, max_tokens: 4096, temperature: 0.7 }); let llm: Arc<dyn LlmCompleter> = Arc::new(LlmDriverAdapter { driver, max_tokens: 4096, temperature: 0.7 });
Self { skills, llm } Self { skills, llm, tool_registry: std::sync::RwLock::new(None) }
}
/// Update the tool registry snapshot. Called by the kernel before each
/// agent loop iteration so skill execution sees the latest tool set.
pub fn set_tool_registry(&self, registry: zclaw_runtime::ToolRegistry) {
if let Ok(mut guard) = self.tool_registry.write() {
*guard = Some(registry);
}
}
/// Resolve the tool definitions declared by a skill manifest against
/// the currently active tool registry.
fn resolve_tool_definitions(&self, skill_id: &str) -> Vec<ToolDefinition> {
let manifests = self.skills.manifests_snapshot();
let manifest = match manifests.get(&zclaw_types::SkillId::new(skill_id)) {
Some(m) => m,
None => return vec![],
};
if manifest.tools.is_empty() {
return vec![];
}
let guard = match self.tool_registry.read() {
Ok(g) => g,
Err(_) => return vec![],
};
let registry = match guard.as_ref() {
Some(r) => r,
None => return vec![],
};
// Only include definitions for tools declared in the skill manifest.
registry.definitions().into_iter()
.filter(|def| manifest.tools.iter().any(|t| t == &def.name))
.collect()
} }
} }
@@ -67,10 +161,12 @@ impl SkillExecutor for KernelSkillExecutor {
session_id: &str, session_id: &str,
input: Value, input: Value,
) -> Result<Value> { ) -> Result<Value> {
let tool_definitions = self.resolve_tool_definitions(skill_id);
let context = zclaw_skills::SkillContext { let context = zclaw_skills::SkillContext {
agent_id: agent_id.to_string(), agent_id: agent_id.to_string(),
session_id: session_id.to_string(), session_id: session_id.to_string(),
llm: Some(self.llm.clone()), llm: Some(self.llm.clone()),
tool_definitions,
..Default::default() ..Default::default()
}; };
let result = self.skills.execute(&zclaw_types::SkillId::new(skill_id), &context, input).await?; let result = self.skills.execute(&zclaw_types::SkillId::new(skill_id), &context, input).await?;
@@ -106,13 +202,11 @@ impl SkillExecutor for KernelSkillExecutor {
/// Inbox wrapper for A2A message receivers that supports re-queuing /// Inbox wrapper for A2A message receivers that supports re-queuing
/// non-matching messages instead of dropping them. /// non-matching messages instead of dropping them.
#[cfg(feature = "multi-agent")]
pub(crate) struct AgentInbox { pub(crate) struct AgentInbox {
pub(crate) rx: tokio::sync::mpsc::Receiver<zclaw_protocols::A2aEnvelope>, pub(crate) rx: tokio::sync::mpsc::Receiver<zclaw_protocols::A2aEnvelope>,
pub(crate) pending: std::collections::VecDeque<zclaw_protocols::A2aEnvelope>, pub(crate) pending: std::collections::VecDeque<zclaw_protocols::A2aEnvelope>,
} }
#[cfg(feature = "multi-agent")]
impl AgentInbox { impl AgentInbox {
pub(crate) fn new(rx: tokio::sync::mpsc::Receiver<zclaw_protocols::A2aEnvelope>) -> Self { pub(crate) fn new(rx: tokio::sync::mpsc::Receiver<zclaw_protocols::A2aEnvelope>) -> Self {
Self { rx, pending: std::collections::VecDeque::new() } Self { rx, pending: std::collections::VecDeque::new() }
@@ -136,3 +230,47 @@ impl AgentInbox {
self.pending.push_back(envelope); self.pending.push_back(envelope);
} }
} }
/// Hand executor implementation for Kernel
///
/// Bridges `zclaw_runtime::tool::HandExecutor` → `zclaw_hands::HandRegistry`,
/// allowing `HandTool::execute()` to dispatch to the real Hand implementations.
pub struct KernelHandExecutor {
hands: Arc<HandRegistry>,
}
impl KernelHandExecutor {
pub fn new(hands: Arc<HandRegistry>) -> Self {
Self { hands }
}
}
#[async_trait]
impl HandExecutor for KernelHandExecutor {
async fn execute_hand(
&self,
hand_id: &str,
agent_id: &AgentId,
input: Value,
) -> Result<Value> {
let context = zclaw_hands::HandContext {
agent_id: agent_id.clone(),
working_dir: None,
env: std::collections::HashMap::new(),
timeout_secs: 300,
callback_url: None,
};
let result = self.hands.execute(hand_id, &context, input).await?;
if result.success {
Ok(result.output)
} else {
Ok(json!({
"hand_id": hand_id,
"status": "failed",
"error": result.error.unwrap_or_else(|| "Unknown hand execution error".to_string()),
"output": result.output,
"duration_ms": result.duration_ms,
}))
}
}
}

View File

@@ -2,11 +2,8 @@
use zclaw_types::{AgentConfig, AgentId, AgentInfo, Event, Result}; use zclaw_types::{AgentConfig, AgentId, AgentInfo, Event, Result};
#[cfg(feature = "multi-agent")]
use std::sync::Arc; use std::sync::Arc;
#[cfg(feature = "multi-agent")]
use tokio::sync::Mutex; use tokio::sync::Mutex;
#[cfg(feature = "multi-agent")]
use super::adapters::AgentInbox; use super::adapters::AgentInbox;
use super::Kernel; use super::Kernel;
@@ -23,7 +20,6 @@ impl Kernel {
self.memory.save_agent(&config).await?; self.memory.save_agent(&config).await?;
// Register with A2A router for multi-agent messaging (before config is moved) // Register with A2A router for multi-agent messaging (before config is moved)
#[cfg(feature = "multi-agent")]
{ {
let profile = Self::agent_config_to_a2a_profile(&config); let profile = Self::agent_config_to_a2a_profile(&config);
let rx = self.a2a_router.register_agent(profile).await; let rx = self.a2a_router.register_agent(profile).await;
@@ -52,7 +48,6 @@ impl Kernel {
self.memory.delete_agent(id).await?; self.memory.delete_agent(id).await?;
// Unregister from A2A router // Unregister from A2A router
#[cfg(feature = "multi-agent")]
{ {
self.a2a_router.unregister_agent(id).await; self.a2a_router.unregister_agent(id).await;
self.a2a_inboxes.remove(id); self.a2a_inboxes.remove(id);

View File

@@ -85,14 +85,14 @@ impl Kernel {
started_at: None, started_at: None,
completed_at: None, completed_at: None,
}; };
let _ = memory.save_hand_run(&run).await.map_err(|e| { if let Err(e) = memory.save_hand_run(&run).await {
tracing::warn!("[Approval] Failed to save hand run: {}", e); tracing::error!("[Approval] Failed to save hand run: {}", e);
}); }
run.status = HandRunStatus::Running; run.status = HandRunStatus::Running;
run.started_at = Some(chrono::Utc::now().to_rfc3339()); run.started_at = Some(chrono::Utc::now().to_rfc3339());
let _ = memory.update_hand_run(&run).await.map_err(|e| { if let Err(e) = memory.update_hand_run(&run).await {
tracing::warn!("[Approval] Failed to update hand run (running): {}", e); tracing::error!("[Approval] Failed to update hand run (running): {}", e);
}); }
// Register cancellation flag // Register cancellation flag
let cancel_flag = Arc::new(std::sync::atomic::AtomicBool::new(false)); let cancel_flag = Arc::new(std::sync::atomic::AtomicBool::new(false));
@@ -121,9 +121,9 @@ impl Kernel {
} }
run.duration_ms = Some(duration.as_millis() as u64); run.duration_ms = Some(duration.as_millis() as u64);
run.completed_at = Some(completed_at); run.completed_at = Some(completed_at);
let _ = memory.update_hand_run(&run).await.map_err(|e| { if let Err(e) = memory.update_hand_run(&run).await {
tracing::warn!("[Approval] Failed to update hand run (completed): {}", e); tracing::error!("[Approval] Failed to update hand run (completed): {}", e);
}); }
// Update approval status based on execution result // Update approval status based on execution result
let mut approvals = approvals.lock().await; let mut approvals = approvals.lock().await;

View File

@@ -0,0 +1,113 @@
//! Evolution Bridge — connects growth crate's SkillCandidate to skills crate's SkillManifest
//!
//! The growth crate (zclaw-growth) generates SkillCandidate from conversation patterns.
//! The skills crate (zclaw-skills) requires SkillManifest for disk persistence.
//! This bridge lives in zclaw-kernel because it depends on both crates.
use zclaw_growth::skill_generator::SkillCandidate;
use zclaw_skills::{SkillManifest, SkillMode};
use zclaw_types::SkillId;
/// Convert a validated SkillCandidate into a SkillManifest ready for registration.
///
/// Safety invariants:
/// - `mode` is always `PromptOnly` (auto-generated skills cannot execute code)
/// - `enabled` is `false` (requires one explicit positive feedback to activate)
/// - `body_markdown` becomes the SKILL.md body content (stored by serialize_skill_md)
pub fn candidate_to_manifest(candidate: &SkillCandidate) -> SkillManifest {
let slug = name_to_slug(&candidate.name);
SkillManifest {
id: SkillId::new(format!("auto-{}", slug)),
name: candidate.name.clone(),
description: candidate.description.clone(),
version: format!("{}", candidate.version),
author: Some("zclaw-evolution".to_string()),
mode: SkillMode::PromptOnly,
capabilities: Vec::new(),
input_schema: None,
output_schema: None,
tags: vec!["auto-generated".to_string()],
category: None,
triggers: candidate.triggers.clone(),
tools: candidate.tools.clone(),
enabled: false,
}
}
/// Convert a human-readable name to a URL-safe slug.
fn name_to_slug(name: &str) -> String {
let mut result = String::new();
for c in name.trim().chars() {
if c.is_ascii_alphanumeric() {
result.push(c.to_ascii_lowercase());
} else if c == ' ' || c == '-' || c == '_' {
result.push('-');
} else {
// Chinese/unicode characters: use hex representation
result.push_str(&format!("{:x}", c as u32));
}
}
result.trim_matches('-').to_string()
}
#[cfg(test)]
mod tests {
use super::*;
fn make_candidate() -> SkillCandidate {
SkillCandidate {
name: "每日报表".to_string(),
description: "生成每日报表".to_string(),
triggers: vec!["报表".to_string(), "日报".to_string()],
tools: vec!["researcher".to_string()],
body_markdown: "# 每日报表\n步骤1\n步骤2".to_string(),
source_pattern: "报表生成".to_string(),
confidence: 0.85,
version: 1,
}
}
#[test]
fn test_candidate_to_manifest() {
let candidate = make_candidate();
let manifest = candidate_to_manifest(&candidate);
assert!(manifest.id.as_str().starts_with("auto-"));
assert_eq!(manifest.name, "每日报表");
assert_eq!(manifest.description, "生成每日报表");
assert_eq!(manifest.version, "1");
assert_eq!(manifest.author.as_deref(), Some("zclaw-evolution"));
assert_eq!(manifest.mode, SkillMode::PromptOnly);
assert!(!manifest.enabled, "auto-generated skills must start disabled");
assert_eq!(manifest.triggers, candidate.triggers);
assert_eq!(manifest.tools, candidate.tools);
assert!(manifest.tags.contains(&"auto-generated".to_string()));
}
#[test]
fn test_name_to_slug_ascii() {
assert_eq!(name_to_slug("Daily Report"), "daily-report");
}
#[test]
fn test_name_to_slug_chinese() {
let slug = name_to_slug("每日报表");
assert!(!slug.is_empty());
assert!(!slug.contains(' '));
}
#[test]
fn test_auto_generated_always_prompt_only() {
let candidate = make_candidate();
let manifest = candidate_to_manifest(&candidate);
assert_eq!(manifest.mode, SkillMode::PromptOnly);
}
#[test]
fn test_auto_generated_starts_disabled() {
let candidate = make_candidate();
let manifest = candidate_to_manifest(&candidate);
assert!(!manifest.enabled);
}
}

View File

@@ -25,7 +25,7 @@ impl Kernel {
agent_id: &AgentId, agent_id: &AgentId,
message: String, message: String,
) -> Result<MessageResponse> { ) -> Result<MessageResponse> {
self.send_message_with_chat_mode(agent_id, message, None).await self.send_message_with_chat_mode(agent_id, message, None, None).await
} }
/// Send a message to an agent with optional chat mode configuration /// Send a message to an agent with optional chat mode configuration
@@ -34,6 +34,7 @@ impl Kernel {
agent_id: &AgentId, agent_id: &AgentId,
message: String, message: String,
chat_mode: Option<ChatModeConfig>, chat_mode: Option<ChatModeConfig>,
model_override: Option<String>,
) -> Result<MessageResponse> { ) -> Result<MessageResponse> {
let agent_config = self.registry.get(agent_id) let agent_config = self.registry.get(agent_id)
.ok_or_else(|| zclaw_types::ZclawError::NotFound(format!("Agent not found: {}", agent_id)))?; .ok_or_else(|| zclaw_types::ZclawError::NotFound(format!("Agent not found: {}", agent_id)))?;
@@ -41,16 +42,21 @@ impl Kernel {
// Create or get session // Create or get session
let session_id = self.memory.create_session(agent_id).await?; let session_id = self.memory.create_session(agent_id).await?;
// Use agent-level model if configured, otherwise fall back to global config // Model priority: UI override > Agent config > Global config
let model = if !agent_config.model.model.is_empty() { let model = model_override
agent_config.model.model.clone() .filter(|m| !m.is_empty())
} else { .unwrap_or_else(|| {
self.config.model().to_string() if !agent_config.model.model.is_empty() {
}; agent_config.model.model.clone()
} else {
self.config.model().to_string()
}
});
// Create agent loop with model configuration // Create agent loop with model configuration
let subagent_enabled = chat_mode.as_ref().and_then(|m| m.subagent_enabled).unwrap_or(false); let subagent_enabled = chat_mode.as_ref().and_then(|m| m.subagent_enabled).unwrap_or(false);
let tools = self.create_tool_registry(subagent_enabled); let tools = self.create_tool_registry(subagent_enabled);
self.skill_executor.set_tool_registry(tools.clone());
let mut loop_runner = AgentLoop::new( let mut loop_runner = AgentLoop::new(
*agent_id, *agent_id,
self.driver.clone(), self.driver.clone(),
@@ -59,6 +65,7 @@ impl Kernel {
) )
.with_model(&model) .with_model(&model)
.with_skill_executor(self.skill_executor.clone()) .with_skill_executor(self.skill_executor.clone())
.with_hand_executor(self.hand_executor.clone())
.with_max_tokens(agent_config.max_tokens.unwrap_or_else(|| self.config.max_tokens())) .with_max_tokens(agent_config.max_tokens.unwrap_or_else(|| self.config.max_tokens()))
.with_temperature(agent_config.temperature.unwrap_or_else(|| self.config.temperature())) .with_temperature(agent_config.temperature.unwrap_or_else(|| self.config.temperature()))
.with_compaction_threshold( .with_compaction_threshold(
@@ -78,10 +85,8 @@ impl Kernel {
loop_runner = loop_runner.with_path_validator(path_validator); loop_runner = loop_runner.with_path_validator(path_validator);
} }
// Inject middleware chain if available // Inject middleware chain
if let Some(chain) = self.create_middleware_chain() { loop_runner = loop_runner.with_middleware_chain(self.create_middleware_chain());
loop_runner = loop_runner.with_middleware_chain(chain);
}
// Apply chat mode configuration (thinking/reasoning/plan mode) // Apply chat mode configuration (thinking/reasoning/plan mode)
if let Some(ref mode) = chat_mode { if let Some(ref mode) = chat_mode {
@@ -122,7 +127,7 @@ impl Kernel {
agent_id: &AgentId, agent_id: &AgentId,
message: String, message: String,
) -> Result<mpsc::Receiver<zclaw_runtime::LoopEvent>> { ) -> Result<mpsc::Receiver<zclaw_runtime::LoopEvent>> {
self.send_message_stream_with_prompt(agent_id, message, None, None, None).await self.send_message_stream_with_prompt(agent_id, message, None, None, None, None).await
} }
/// Send a message with streaming, optional system prompt, optional session reuse, /// Send a message with streaming, optional system prompt, optional session reuse,
@@ -134,6 +139,7 @@ impl Kernel {
system_prompt_override: Option<String>, system_prompt_override: Option<String>,
session_id_override: Option<zclaw_types::SessionId>, session_id_override: Option<zclaw_types::SessionId>,
chat_mode: Option<ChatModeConfig>, chat_mode: Option<ChatModeConfig>,
model_override: Option<String>,
) -> Result<mpsc::Receiver<zclaw_runtime::LoopEvent>> { ) -> Result<mpsc::Receiver<zclaw_runtime::LoopEvent>> {
let agent_config = self.registry.get(agent_id) let agent_config = self.registry.get(agent_id)
.ok_or_else(|| zclaw_types::ZclawError::NotFound(format!("Agent not found: {}", agent_id)))?; .ok_or_else(|| zclaw_types::ZclawError::NotFound(format!("Agent not found: {}", agent_id)))?;
@@ -150,16 +156,21 @@ impl Kernel {
None => self.memory.create_session(agent_id).await?, None => self.memory.create_session(agent_id).await?,
}; };
// Use agent-level model if configured, otherwise fall back to global config // Model priority: UI override > Agent config > Global config
let model = if !agent_config.model.model.is_empty() { let model = model_override
agent_config.model.model.clone() .filter(|m| !m.is_empty())
} else { .unwrap_or_else(|| {
self.config.model().to_string() if !agent_config.model.model.is_empty() {
}; agent_config.model.model.clone()
} else {
self.config.model().to_string()
}
});
// Create agent loop with model configuration // Create agent loop with model configuration
let subagent_enabled = chat_mode.as_ref().and_then(|m| m.subagent_enabled).unwrap_or(false); let subagent_enabled = chat_mode.as_ref().and_then(|m| m.subagent_enabled).unwrap_or(false);
let tools = self.create_tool_registry(subagent_enabled); let tools = self.create_tool_registry(subagent_enabled);
self.skill_executor.set_tool_registry(tools.clone());
let mut loop_runner = AgentLoop::new( let mut loop_runner = AgentLoop::new(
*agent_id, *agent_id,
self.driver.clone(), self.driver.clone(),
@@ -168,6 +179,7 @@ impl Kernel {
) )
.with_model(&model) .with_model(&model)
.with_skill_executor(self.skill_executor.clone()) .with_skill_executor(self.skill_executor.clone())
.with_hand_executor(self.hand_executor.clone())
.with_max_tokens(agent_config.max_tokens.unwrap_or_else(|| self.config.max_tokens())) .with_max_tokens(agent_config.max_tokens.unwrap_or_else(|| self.config.max_tokens()))
.with_temperature(agent_config.temperature.unwrap_or_else(|| self.config.temperature())) .with_temperature(agent_config.temperature.unwrap_or_else(|| self.config.temperature()))
.with_compaction_threshold( .with_compaction_threshold(
@@ -188,10 +200,8 @@ impl Kernel {
loop_runner = loop_runner.with_path_validator(path_validator); loop_runner = loop_runner.with_path_validator(path_validator);
} }
// Inject middleware chain if available // Inject middleware chain
if let Some(chain) = self.create_middleware_chain() { loop_runner = loop_runner.with_middleware_chain(self.create_middleware_chain());
loop_runner = loop_runner.with_middleware_chain(chain);
}
// Apply chat mode configuration (thinking/reasoning/plan mode from frontend) // Apply chat mode configuration (thinking/reasoning/plan mode from frontend)
if let Some(ref mode) = chat_mode { if let Some(ref mode) = chat_mode {

View File

@@ -8,16 +8,14 @@ mod hands;
mod triggers; mod triggers;
mod approvals; mod approvals;
mod orchestration; mod orchestration;
#[cfg(feature = "multi-agent")]
mod a2a; mod a2a;
mod evolution_bridge;
use std::sync::Arc; use std::sync::Arc;
use tokio::sync::{broadcast, Mutex}; use tokio::sync::{broadcast, Mutex};
use zclaw_types::{Event, Result, AgentState}; use zclaw_types::{Event, Result, AgentState};
#[cfg(feature = "multi-agent")]
use zclaw_types::AgentId; use zclaw_types::AgentId;
#[cfg(feature = "multi-agent")]
use zclaw_protocols::A2aRouter; use zclaw_protocols::A2aRouter;
use crate::registry::AgentRegistry; use crate::registry::AgentRegistry;
@@ -27,9 +25,10 @@ use crate::config::KernelConfig;
use zclaw_memory::MemoryStore; use zclaw_memory::MemoryStore;
use zclaw_runtime::{LlmDriver, ToolRegistry, tool::SkillExecutor}; use zclaw_runtime::{LlmDriver, ToolRegistry, tool::SkillExecutor};
use zclaw_skills::SkillRegistry; use zclaw_skills::SkillRegistry;
use zclaw_hands::{HandRegistry, hands::{BrowserHand, SlideshowHand, SpeechHand, QuizHand, WhiteboardHand, ResearcherHand, CollectorHand, ClipHand, TwitterHand, quiz::LlmQuizGenerator}}; use zclaw_hands::{HandRegistry, hands::{BrowserHand, QuizHand, ResearcherHand, CollectorHand, ClipHand, TwitterHand, ReminderHand, quiz::LlmQuizGenerator}};
pub use adapters::KernelSkillExecutor; pub use adapters::KernelSkillExecutor;
pub use adapters::KernelHandExecutor;
pub use messaging::ChatModeConfig; pub use messaging::ChatModeConfig;
/// The ZCLAW Kernel /// The ZCLAW Kernel
@@ -43,20 +42,29 @@ pub struct Kernel {
llm_completer: Arc<dyn zclaw_skills::LlmCompleter>, llm_completer: Arc<dyn zclaw_skills::LlmCompleter>,
skills: Arc<SkillRegistry>, skills: Arc<SkillRegistry>,
skill_executor: Arc<KernelSkillExecutor>, skill_executor: Arc<KernelSkillExecutor>,
hand_executor: Arc<KernelHandExecutor>,
hands: Arc<HandRegistry>, hands: Arc<HandRegistry>,
/// Cached hand configs (populated at boot, used for tool registry)
hand_configs: Vec<zclaw_hands::HandConfig>,
trigger_manager: crate::trigger_manager::TriggerManager, trigger_manager: crate::trigger_manager::TriggerManager,
pending_approvals: Arc<Mutex<Vec<ApprovalEntry>>>, pending_approvals: Arc<Mutex<Vec<ApprovalEntry>>>,
/// Running hand runs that can be cancelled (run_id -> cancelled flag) /// Running hand runs that can be cancelled (run_id -> cancelled flag)
running_hand_runs: Arc<dashmap::DashMap<zclaw_types::HandRunId, Arc<std::sync::atomic::AtomicBool>>>, running_hand_runs: Arc<dashmap::DashMap<zclaw_types::HandRunId, Arc<std::sync::atomic::AtomicBool>>>,
/// Shared memory storage backend for Growth system /// Shared memory storage backend for Growth system
viking: Arc<zclaw_runtime::VikingAdapter>, viking: Arc<zclaw_runtime::VikingAdapter>,
/// Cached GrowthIntegration — avoids recreating empty scorer per request
growth: std::sync::Mutex<Option<std::sync::Arc<zclaw_runtime::GrowthIntegration>>>,
/// Optional LLM driver for memory extraction (set by Tauri desktop layer) /// Optional LLM driver for memory extraction (set by Tauri desktop layer)
extraction_driver: Option<Arc<dyn zclaw_runtime::LlmDriverForExtraction>>, extraction_driver: Option<Arc<dyn zclaw_runtime::LlmDriverForExtraction>>,
/// A2A router for inter-agent messaging (gated by multi-agent feature) /// Optional embedding client for semantic search (set by Tauri desktop layer)
#[cfg(feature = "multi-agent")] embedding_client: Option<Arc<dyn zclaw_runtime::EmbeddingClient>>,
/// MCP tool adapters — shared with Tauri MCP manager, updated dynamically
mcp_adapters: Arc<std::sync::RwLock<Vec<zclaw_protocols::McpToolAdapter>>>,
/// Dynamic industry keyword configs — shared with Tauri frontend, loaded from SaaS
industry_keywords: Arc<tokio::sync::RwLock<Vec<zclaw_runtime::IndustryKeywordConfig>>>,
/// A2A router for inter-agent messaging
a2a_router: Arc<A2aRouter>, a2a_router: Arc<A2aRouter>,
/// Per-agent A2A inbox receivers (supports re-queuing non-matching messages) /// Per-agent A2A inbox receivers (supports re-queuing non-matching messages)
#[cfg(feature = "multi-agent")]
a2a_inboxes: Arc<dashmap::DashMap<AgentId, Arc<Mutex<adapters::AgentInbox>>>>, a2a_inboxes: Arc<dashmap::DashMap<AgentId, Arc<Mutex<adapters::AgentInbox>>>>,
} }
@@ -89,18 +97,22 @@ impl Kernel {
let quiz_model = config.model().to_string(); let quiz_model = config.model().to_string();
let quiz_generator = Arc::new(LlmQuizGenerator::new(driver.clone(), quiz_model)); let quiz_generator = Arc::new(LlmQuizGenerator::new(driver.clone(), quiz_model));
hands.register(Arc::new(BrowserHand::new())).await; hands.register(Arc::new(BrowserHand::new())).await;
hands.register(Arc::new(SlideshowHand::new())).await;
hands.register(Arc::new(SpeechHand::new())).await;
hands.register(Arc::new(QuizHand::with_generator(quiz_generator))).await; hands.register(Arc::new(QuizHand::with_generator(quiz_generator))).await;
hands.register(Arc::new(WhiteboardHand::new())).await;
hands.register(Arc::new(ResearcherHand::new())).await; hands.register(Arc::new(ResearcherHand::new())).await;
hands.register(Arc::new(CollectorHand::new())).await; hands.register(Arc::new(CollectorHand::new())).await;
hands.register(Arc::new(ClipHand::new())).await; hands.register(Arc::new(ClipHand::new())).await;
hands.register(Arc::new(TwitterHand::new())).await; hands.register(Arc::new(TwitterHand::new())).await;
hands.register(Arc::new(ReminderHand::new())).await;
// Cache hand configs for tool registry (sync access from create_tool_registry)
let hand_configs = hands.list().await;
// Create skill executor // Create skill executor
let skill_executor = Arc::new(KernelSkillExecutor::new(skills.clone(), driver.clone())); let skill_executor = Arc::new(KernelSkillExecutor::new(skills.clone(), driver.clone()));
// Create hand executor — bridges HandTool calls to the HandRegistry
let hand_executor = Arc::new(KernelHandExecutor::new(hands.clone()));
// Create LLM completer for skill system (shared with skill_executor) // Create LLM completer for skill system (shared with skill_executor)
let llm_completer: Arc<dyn zclaw_skills::LlmCompleter> = let llm_completer: Arc<dyn zclaw_skills::LlmCompleter> =
Arc::new(adapters::LlmDriverAdapter { Arc::new(adapters::LlmDriverAdapter {
@@ -133,7 +145,6 @@ impl Kernel {
} }
// Initialize A2A router for multi-agent support // Initialize A2A router for multi-agent support
#[cfg(feature = "multi-agent")]
let a2a_router = { let a2a_router = {
let kernel_agent_id = AgentId::new(); let kernel_agent_id = AgentId::new();
Arc::new(A2aRouter::new(kernel_agent_id)) Arc::new(A2aRouter::new(kernel_agent_id))
@@ -149,20 +160,24 @@ impl Kernel {
llm_completer, llm_completer,
skills, skills,
skill_executor, skill_executor,
hand_executor,
hands, hands,
hand_configs,
trigger_manager, trigger_manager,
pending_approvals: Arc::new(Mutex::new(Vec::new())), pending_approvals: Arc::new(Mutex::new(Vec::new())),
running_hand_runs: Arc::new(dashmap::DashMap::new()), running_hand_runs: Arc::new(dashmap::DashMap::new()),
viking, viking,
growth: std::sync::Mutex::new(None),
extraction_driver: None, extraction_driver: None,
#[cfg(feature = "multi-agent")] embedding_client: None,
mcp_adapters: Arc::new(std::sync::RwLock::new(Vec::new())),
industry_keywords: Arc::new(tokio::sync::RwLock::new(Vec::new())),
a2a_router, a2a_router,
#[cfg(feature = "multi-agent")]
a2a_inboxes: Arc::new(dashmap::DashMap::new()), a2a_inboxes: Arc::new(dashmap::DashMap::new()),
}) })
} }
/// Create a tool registry with built-in tools. /// Create a tool registry with built-in tools + Hand tools + MCP tools.
/// When `subagent_enabled` is false, TaskTool is excluded to prevent /// When `subagent_enabled` is false, TaskTool is excluded to prevent
/// the LLM from attempting sub-agent delegation in non-Ultra modes. /// the LLM from attempting sub-agent delegation in non-Ultra modes.
pub(crate) fn create_tool_registry(&self, subagent_enabled: bool) -> ToolRegistry { pub(crate) fn create_tool_registry(&self, subagent_enabled: bool) -> ToolRegistry {
@@ -179,6 +194,30 @@ impl Kernel {
tools.register(Box::new(task_tool)); tools.register(Box::new(task_tool));
} }
// Register Hand tools — expose registered Hands as LLM-callable tools
// (e.g., hand_quiz, hand_researcher, hand_browser, etc.)
for config in &self.hand_configs {
if !config.enabled {
continue;
}
let tool = zclaw_runtime::tool::hand_tool::HandTool::from_config(
&config.id,
&config.description,
config.input_schema.clone(),
);
tools.register(Box::new(tool));
}
// Register MCP tools (dynamically updated by Tauri MCP manager)
if let Ok(adapters) = self.mcp_adapters.read() {
for adapter in adapters.iter() {
let wrapper = zclaw_runtime::tool::builtin::McpToolWrapper::new(
std::sync::Arc::new(adapter.clone())
);
tools.register(Box::new(wrapper));
}
}
tools tools
} }
@@ -187,7 +226,7 @@ impl Kernel {
/// When middleware is configured, cross-cutting concerns (compaction, loop guard, /// When middleware is configured, cross-cutting concerns (compaction, loop guard,
/// token calibration, etc.) are delegated to the chain. When no middleware is /// token calibration, etc.) are delegated to the chain. When no middleware is
/// registered, the legacy inline path in `AgentLoop` is used instead. /// registered, the legacy inline path in `AgentLoop` is used instead.
pub(crate) fn create_middleware_chain(&self) -> Option<zclaw_runtime::middleware::MiddlewareChain> { pub(crate) fn create_middleware_chain(&self) -> zclaw_runtime::middleware::MiddlewareChain {
let mut chain = zclaw_runtime::middleware::MiddlewareChain::new(); let mut chain = zclaw_runtime::middleware::MiddlewareChain::new();
// Butler router — semantic skill routing context injection // Butler router — semantic skill routing context injection
@@ -217,20 +256,35 @@ impl Kernel {
category: "semantic_skill".to_string(), category: "semantic_skill".to_string(),
confidence: r.confidence, confidence: r.confidence,
skill_id: Some(r.skill_id), skill_id: Some(r.skill_id),
domain_prompt: None,
}) })
} }
} }
// Build semantic router from the skill registry (75 SKILL.md loaded at boot) // Build semantic router from the skill registry (75 SKILL.md loaded at boot)
let semantic_router = SemanticSkillRouter::new_tf_idf_only(self.skills.clone()); let semantic_router = if let Some(ref embed_client) = self.embedding_client {
let adapter = crate::skill_router::EmbeddingAdapter::new(embed_client.clone());
let mut router = SemanticSkillRouter::new(self.skills.clone(), Arc::new(adapter));
if let Some(llm_fallback) = self.make_llm_skill_fallback() {
router = router.with_llm_fallback(llm_fallback);
}
tracing::debug!("[Kernel] SemanticSkillRouter created with embedding support");
router
} else {
SemanticSkillRouter::new_tf_idf_only(self.skills.clone())
};
let adapter = SemanticRouterAdapter::new(Arc::new(semantic_router)); let adapter = SemanticRouterAdapter::new(Arc::new(semantic_router));
let mw = zclaw_runtime::middleware::butler_router::ButlerRouterMiddleware::with_router( let mw = zclaw_runtime::middleware::butler_router::ButlerRouterMiddleware::with_router_and_shared_keywords(
Box::new(adapter) Box::new(adapter),
self.industry_keywords.clone(),
); );
chain.register(Arc::new(mw)); chain.register(Arc::new(mw));
} }
// Data masking middleware — mask sensitive entities before any other processing // Data masking middleware — mask sensitive entities before any other processing
// NOTE: Registration order does NOT determine execution order.
// The chain sorts by priority() ascending before execution.
// Execution order: Evolution(78) → ButlerRouter(80) → DataMasking(90) → ...
{ {
use std::sync::Arc; use std::sync::Arc;
let masker = Arc::new(zclaw_runtime::middleware::data_masking::DataMasker::new()); let masker = Arc::new(zclaw_runtime::middleware::data_masking::DataMasker::new());
@@ -238,11 +292,29 @@ impl Kernel {
chain.register(Arc::new(mw)); chain.register(Arc::new(mw));
} }
// Growth integration — shared VikingAdapter for memory middleware & compaction // Growth integration — cached to avoid recreating empty scorer per request
let mut growth = zclaw_runtime::GrowthIntegration::new(self.viking.clone()); let growth = {
if let Some(ref driver) = self.extraction_driver { let mut cached = self.growth.lock().expect("growth lock");
growth = growth.with_llm_driver(driver.clone()); if cached.is_none() {
} let mut g = zclaw_runtime::GrowthIntegration::new(self.viking.clone());
if let Some(ref driver) = self.extraction_driver {
g = g.with_llm_driver(driver.clone());
}
// Propagate embedding client to memory retriever if configured
if let Some(ref embed_client) = self.embedding_client {
g.configure_embedding(embed_client.clone());
}
*cached = Some(std::sync::Arc::new(g));
}
cached.as_ref().expect("growth present").clone()
};
// Evolution middleware — pushes evolution candidate skills into system prompt
// priority=78, executed first by chain (before ButlerRouter@80)
let evolution_mw = std::sync::Arc::new(
zclaw_runtime::middleware::evolution::EvolutionMiddleware::new()
);
chain.register(evolution_mw.clone());
// Compaction middleware — only register when threshold > 0 // Compaction middleware — only register when threshold > 0
let threshold = self.config.compaction_threshold(); let threshold = self.config.compaction_threshold();
@@ -261,10 +333,11 @@ impl Kernel {
chain.register(Arc::new(mw)); chain.register(Arc::new(mw));
} }
// Memory middleware — auto-extract memories after conversations // Memory middleware — auto-extract memories + check evolution after conversations
{ {
use std::sync::Arc; use std::sync::Arc;
let mw = zclaw_runtime::middleware::memory::MemoryMiddleware::new(growth); let mw = zclaw_runtime::middleware::memory::MemoryMiddleware::new(growth.clone())
.with_evolution(evolution_mw);
chain.register(Arc::new(mw)); chain.register(Arc::new(mw));
} }
@@ -335,13 +408,19 @@ impl Kernel {
chain.register(Arc::new(mw)); chain.register(Arc::new(mw));
} }
// Only return Some if we actually registered middleware // Trajectory recorder — record agent loop events for Hermes analysis
if chain.is_empty() { {
None use std::sync::Arc;
} else { let tstore = zclaw_memory::trajectory_store::TrajectoryStore::new(self.memory.pool());
tracing::info!("[Kernel] Middleware chain created with {} middlewares", chain.len()); let mw = zclaw_runtime::middleware::trajectory_recorder::TrajectoryRecorderMiddleware::new(Arc::new(tstore));
Some(chain) chain.register(Arc::new(mw));
} }
// Always return the chain (empty chain is a no-op)
if !chain.is_empty() {
tracing::info!("[Kernel] Middleware chain created with {} middlewares", chain.len());
}
chain
} }
/// Subscribe to events /// Subscribe to events
@@ -390,6 +469,10 @@ impl Kernel {
pub fn set_viking(&mut self, viking: Arc<zclaw_runtime::VikingAdapter>) { pub fn set_viking(&mut self, viking: Arc<zclaw_runtime::VikingAdapter>) {
tracing::info!("[Kernel] Replacing in-memory VikingAdapter with persistent storage"); tracing::info!("[Kernel] Replacing in-memory VikingAdapter with persistent storage");
self.viking = viking; self.viking = viking;
// Invalidate cached GrowthIntegration so next request builds with new storage
if let Ok(mut g) = self.growth.lock() {
*g = None;
}
} }
/// Get a reference to the shared VikingAdapter /// Get a reference to the shared VikingAdapter
@@ -404,6 +487,56 @@ impl Kernel {
pub fn set_extraction_driver(&mut self, driver: Arc<dyn zclaw_runtime::LlmDriverForExtraction>) { pub fn set_extraction_driver(&mut self, driver: Arc<dyn zclaw_runtime::LlmDriverForExtraction>) {
tracing::info!("[Kernel] Extraction driver configured for Growth system"); tracing::info!("[Kernel] Extraction driver configured for Growth system");
self.extraction_driver = Some(driver); self.extraction_driver = Some(driver);
// Invalidate cached GrowthIntegration so next request uses new driver
if let Ok(mut g) = self.growth.lock() {
*g = None;
}
}
/// Set the embedding client for semantic search.
///
/// Propagates to both the skill router (ButlerRouter) and memory retrieval
/// (GrowthIntegration). The next middleware chain creation will use the
/// configured client for embedding-based similarity.
pub fn set_embedding_client(&mut self, client: Arc<dyn zclaw_runtime::EmbeddingClient>) {
tracing::info!("[Kernel] Embedding client configured for semantic search");
self.embedding_client = Some(client);
// Invalidate cached GrowthIntegration so next request builds with new embedding
if let Ok(mut g) = self.growth.lock() {
*g = None;
}
}
/// Create an LLM skill fallback using the kernel's LLM driver.
fn make_llm_skill_fallback(&self) -> Option<Arc<dyn zclaw_skills::semantic_router::RuntimeLlmIntent>> {
Some(Arc::new(crate::skill_router::LlmSkillFallback::new(self.driver.clone())))
}
/// Get a reference to the shared MCP adapters list.
///
/// The Tauri MCP manager updates this list when services start/stop.
/// The kernel reads it during `create_tool_registry()` to inject MCP tools
/// into the LLM's available tools.
pub fn mcp_adapters(&self) -> Arc<std::sync::RwLock<Vec<zclaw_protocols::McpToolAdapter>>> {
self.mcp_adapters.clone()
}
/// Replace the MCP adapters with a shared Arc (from Tauri MCP manager).
///
/// Call this after boot to connect the kernel to the Tauri MCP manager's
/// adapter list. After this, MCP service start/stop will automatically
/// be reflected in the LLM's available tools.
pub fn set_mcp_adapters(&mut self, adapters: Arc<std::sync::RwLock<Vec<zclaw_protocols::McpToolAdapter>>>) {
tracing::info!("[Kernel] MCP adapters bridge connected");
self.mcp_adapters = adapters;
}
/// Get a reference to the shared industry keywords config.
///
/// The Tauri frontend updates this list when industry configs are fetched from SaaS.
/// The ButlerRouterMiddleware reads from the same Arc, so updates are automatic.
pub fn industry_keywords(&self) -> Arc<tokio::sync::RwLock<Vec<zclaw_runtime::IndustryKeywordConfig>>> {
self.industry_keywords.clone()
} }
} }

View File

@@ -76,4 +76,77 @@ impl Kernel {
} }
self.skills.execute(&zclaw_types::SkillId::new(id), &ctx, input).await self.skills.execute(&zclaw_types::SkillId::new(id), &ctx, input).await
} }
/// Generate a skill from an aggregated pattern and register it.
///
/// Full pipeline:
/// 1. Build LLM prompt from pattern
/// 2. Call LLM to get JSON response
/// 3. Parse response into SkillCandidate
/// 4. Validate through QualityGate (threshold 0.85 for auto-mode)
/// 5. Convert to SkillManifest (PromptOnly, disabled by default)
/// 6. Persist to disk via SkillRegistry
pub async fn generate_and_register_skill(
&self,
pattern: &zclaw_growth::pattern_aggregator::AggregatedPattern,
) -> Result<String> {
// 1. Build prompt
let prompt = zclaw_growth::skill_generator::SkillGenerator::build_prompt(pattern);
// 2. Call LLM
let request = zclaw_runtime::driver::CompletionRequest {
model: self.driver.provider().to_string(),
system: Some("你是技能设计专家,只返回 JSON 格式的技能定义。".to_string()),
messages: vec![zclaw_types::Message::user(prompt)],
max_tokens: Some(1024),
temperature: Some(0.3),
stream: false,
..Default::default()
};
let response = self.driver.complete(request).await?;
let text = response.content.iter()
.filter_map(|block| match block {
zclaw_runtime::driver::ContentBlock::Text { text } => Some(text.as_str()),
_ => None,
})
.collect::<Vec<_>>()
.join("");
// 3. Parse into SkillCandidate
let candidate = zclaw_growth::skill_generator::SkillGenerator::parse_response(
&text, pattern,
)?;
// 4. Validate through QualityGate (higher threshold for auto-generation)
let existing_triggers: Vec<String> = self.skills.list().await
.into_iter()
.flat_map(|m| m.triggers)
.collect();
let gate = zclaw_growth::quality_gate::QualityGate::new(0.85, existing_triggers);
let report = gate.validate_skill(&candidate);
if !report.passed {
return Err(zclaw_types::ZclawError::ConfigError(format!(
"QualityGate rejected: {}", report.issues.join("; ")
)));
}
// 5. Convert to SkillManifest (PromptOnly, disabled)
let manifest = super::evolution_bridge::candidate_to_manifest(&candidate);
let skill_id = manifest.id.to_string();
// 6. Persist to disk
let skills_dir = self.config.skills_dir.as_ref()
.ok_or_else(|| zclaw_types::ZclawError::InvalidInput(
"Skills directory not configured".into()
))?;
self.skills.create_skill(skills_dir, manifest).await?;
tracing::info!(
"[Kernel] Auto-generated skill '{}' (id={}) registered (disabled)",
candidate.name, skill_id
);
Ok(skill_id)
}
} }

View File

@@ -10,7 +10,6 @@ pub mod trigger_manager;
pub mod config; pub mod config;
pub mod scheduler; pub mod scheduler;
pub mod skill_router; pub mod skill_router;
#[cfg(feature = "multi-agent")]
pub mod director; pub mod director;
pub mod generation; pub mod generation;
pub mod export; pub mod export;
@@ -21,13 +20,11 @@ pub use capabilities::*;
pub use events::*; pub use events::*;
pub use config::*; pub use config::*;
pub use trigger_manager::{TriggerManager, TriggerEntry, TriggerUpdateRequest, TriggerManagerConfig}; pub use trigger_manager::{TriggerManager, TriggerEntry, TriggerUpdateRequest, TriggerManagerConfig};
#[cfg(feature = "multi-agent")]
pub use director::{ pub use director::{
Director, DirectorConfig, DirectorBuilder, DirectorAgent, Director, DirectorConfig, DirectorBuilder, DirectorAgent,
ConversationState, ScheduleStrategy, ConversationState, ScheduleStrategy,
// Note: AgentRole is intentionally NOT re-exported here — use generation::AgentRole instead // Note: AgentRole is intentionally NOT re-exported here — use generation::AgentRole instead
}; };
#[cfg(feature = "multi-agent")]
pub use zclaw_protocols::{ pub use zclaw_protocols::{
A2aRouter, A2aAgentProfile, A2aCapability, A2aEnvelope, A2aMessageType, A2aRecipient, A2aRouter, A2aAgentProfile, A2aCapability, A2aEnvelope, A2aMessageType, A2aRecipient,
A2aReceiver, A2aReceiver,

View File

@@ -77,7 +77,7 @@ impl SchedulerService {
kernel_lock: &Arc<Mutex<Option<Kernel>>>, kernel_lock: &Arc<Mutex<Option<Kernel>>>,
) -> Result<()> { ) -> Result<()> {
// Collect due triggers under lock // Collect due triggers under lock
let to_execute: Vec<(String, String, String)> = { let to_execute: Vec<(String, String, String, String)> = {
let kernel_guard = kernel_lock.lock().await; let kernel_guard = kernel_lock.lock().await;
let kernel = match kernel_guard.as_ref() { let kernel = match kernel_guard.as_ref() {
Some(k) => k, Some(k) => k,
@@ -103,7 +103,8 @@ impl SchedulerService {
.filter_map(|t| { .filter_map(|t| {
if let zclaw_hands::TriggerType::Schedule { ref cron } = t.config.trigger_type { if let zclaw_hands::TriggerType::Schedule { ref cron } = t.config.trigger_type {
if Self::should_fire_cron(cron, &now) { if Self::should_fire_cron(cron, &now) {
Some((t.config.id.clone(), t.config.hand_id.clone(), cron.clone())) // (trigger_id, hand_id, cron_expr, trigger_name)
Some((t.config.id.clone(), t.config.hand_id.clone(), cron.clone(), t.config.name.clone()))
} else { } else {
None None
} }
@@ -123,7 +124,7 @@ impl SchedulerService {
// If parallel execution is needed, spawn each execute_hand in a separate task // If parallel execution is needed, spawn each execute_hand in a separate task
// and collect results via JoinSet. // and collect results via JoinSet.
let now = chrono::Utc::now(); let now = chrono::Utc::now();
for (trigger_id, hand_id, cron_expr) in to_execute { for (trigger_id, hand_id, cron_expr, trigger_name) in to_execute {
tracing::info!( tracing::info!(
"[Scheduler] Firing scheduled trigger '{}' → hand '{}' (cron: {})", "[Scheduler] Firing scheduled trigger '{}' → hand '{}' (cron: {})",
trigger_id, hand_id, cron_expr trigger_id, hand_id, cron_expr
@@ -138,6 +139,7 @@ impl SchedulerService {
let input = serde_json::json!({ let input = serde_json::json!({
"trigger_id": trigger_id, "trigger_id": trigger_id,
"trigger_type": "schedule", "trigger_type": "schedule",
"task_description": trigger_name,
"cron": cron_expr, "cron": cron_expr,
"fired_at": now.to_rfc3339(), "fired_at": now.to_rfc3339(),
}); });

View File

@@ -134,7 +134,9 @@ impl TriggerManager {
/// Create a new trigger /// Create a new trigger
pub async fn create_trigger(&self, config: TriggerConfig) -> Result<TriggerEntry> { pub async fn create_trigger(&self, config: TriggerConfig) -> Result<TriggerEntry> {
// Validate hand exists (outside of our lock to avoid holding two locks) // Validate hand exists (outside of our lock to avoid holding two locks)
if self.hand_registry.get(&config.hand_id).await.is_none() { // System hands (prefixed with '_') are exempt from validation — they are
// registered at boot but may not appear in the hand registry scan path.
if !config.hand_id.starts_with('_') && self.hand_registry.get(&config.hand_id).await.is_none() {
return Err(zclaw_types::ZclawError::InvalidInput( return Err(zclaw_types::ZclawError::InvalidInput(
format!("Hand '{}' not found", config.hand_id) format!("Hand '{}' not found", config.hand_id)
)); ));
@@ -170,7 +172,7 @@ impl TriggerManager {
) -> Result<TriggerEntry> { ) -> Result<TriggerEntry> {
// Validate hand exists if being updated (outside of our lock) // Validate hand exists if being updated (outside of our lock)
if let Some(hand_id) = &updates.hand_id { if let Some(hand_id) = &updates.hand_id {
if self.hand_registry.get(hand_id).await.is_none() { if !hand_id.starts_with('_') && self.hand_registry.get(hand_id).await.is_none() {
return Err(zclaw_types::ZclawError::InvalidInput( return Err(zclaw_types::ZclawError::InvalidInput(
format!("Hand '{}' not found", hand_id) format!("Hand '{}' not found", hand_id)
)); ));
@@ -303,9 +305,10 @@ impl TriggerManager {
}; };
// Get hand (outside of our lock to avoid potential deadlock with hand_registry) // Get hand (outside of our lock to avoid potential deadlock with hand_registry)
// System hands (prefixed with '_') must be registered at boot — same rule as create_trigger.
let hand = self.hand_registry.get(&hand_id).await let hand = self.hand_registry.get(&hand_id).await
.ok_or_else(|| zclaw_types::ZclawError::InvalidInput( .ok_or_else(|| zclaw_types::ZclawError::InvalidInput(
format!("Hand '{}' not found", hand_id) format!("Hand '{}' not found (system hands must be registered at boot)", hand_id)
))?; ))?;
// Update state before execution // Update state before execution

View File

@@ -21,6 +21,14 @@ impl MemoryStore {
Ok(store) Ok(store)
} }
/// Get a clone of the underlying SQLite pool.
///
/// Used by subsystems (e.g. `TrajectoryStore`) that need to share the
/// same database connection pool for their own tables.
pub fn pool(&self) -> SqlitePool {
self.pool.clone()
}
/// Ensure the parent directory for the database file exists /// Ensure the parent directory for the database file exists
fn ensure_database_dir(database_url: &str) -> Result<()> { fn ensure_database_dir(database_url: &str) -> Result<()> {
// Parse SQLite URL to extract file path // Parse SQLite URL to extract file path

View File

@@ -25,7 +25,6 @@ reqwest = { workspace = true }
# Internal crates # Internal crates
zclaw-types = { workspace = true } zclaw-types = { workspace = true }
zclaw-runtime = { workspace = true } zclaw-runtime = { workspace = true }
zclaw-kernel = { workspace = true }
zclaw-skills = { workspace = true } zclaw-skills = { workspace = true }
zclaw-hands = { workspace = true } zclaw-hands = { workspace = true }

View File

@@ -589,7 +589,7 @@ impl StageEngine {
} }
/// Clone with drivers (reserved for future use) /// Clone with drivers (reserved for future use)
#[allow(dead_code)] #[allow(dead_code)] // @reserved: post-release stage cloning with drivers
fn clone_with_drivers(&self) -> Self { fn clone_with_drivers(&self) -> Self {
Self { Self {
llm_driver: self.llm_driver.clone(), llm_driver: self.llm_driver.clone(),

View File

@@ -40,6 +40,15 @@ pub enum ExecuteError {
Io(#[from] std::io::Error), Io(#[from] std::io::Error),
} }
/// Maximum completed/failed/cancelled runs to keep in memory
const MAX_COMPLETED_RUNS: usize = 100;
/// Maximum allowed delay in milliseconds (60 seconds)
const MAX_DELAY_MS: u64 = 60_000;
/// Default per-step timeout (5 minutes)
const DEFAULT_STEP_TIMEOUT_SECS: u64 = 300;
/// Pipeline executor /// Pipeline executor
pub struct PipelineExecutor { pub struct PipelineExecutor {
/// Action registry /// Action registry
@@ -107,35 +116,50 @@ impl PipelineExecutor {
// Create execution context // Create execution context
let mut context = ExecutionContext::new(inputs); let mut context = ExecutionContext::new(inputs);
// Determine per-step timeout from pipeline spec (0 means use default)
let step_timeout = if pipeline.spec.timeout_secs > 0 {
pipeline.spec.timeout_secs
} else {
DEFAULT_STEP_TIMEOUT_SECS
};
// Execute steps // Execute steps
let result = self.execute_steps(pipeline, &mut context, &run_id).await; let result = self.execute_steps(pipeline, &mut context, &run_id, step_timeout).await;
// Update run state // Update run state
let mut runs = self.runs.write().await; let return_value = {
if let Some(run) = runs.get_mut(&run_id) { let mut runs = self.runs.write().await;
match result { if let Some(run) = runs.get_mut(&run_id) {
Ok(outputs) => { match result {
run.status = RunStatus::Completed; Ok(outputs) => {
run.outputs = Some(serde_json::to_value(&outputs).unwrap_or(Value::Null)); run.status = RunStatus::Completed;
} run.outputs = Some(serde_json::to_value(&outputs).unwrap_or(Value::Null));
Err(e) => { }
run.status = RunStatus::Failed; Err(e) => {
run.error = Some(e.to_string()); run.status = RunStatus::Failed;
run.error = Some(e.to_string());
}
} }
run.ended_at = Some(Utc::now());
Ok(run.clone())
} else {
Err(ExecuteError::Action("执行后未找到运行记录".to_string()))
} }
run.ended_at = Some(Utc::now()); };
return Ok(run.clone());
}
Err(ExecuteError::Action("执行后未找到运行记录".to_string())) // Auto-cleanup old completed runs (after releasing the write lock)
self.cleanup().await;
return_value
} }
/// Execute pipeline steps /// Execute pipeline steps with per-step timeout
async fn execute_steps( async fn execute_steps(
&self, &self,
pipeline: &Pipeline, pipeline: &Pipeline,
context: &mut ExecutionContext, context: &mut ExecutionContext,
run_id: &str, run_id: &str,
step_timeout_secs: u64,
) -> Result<HashMap<String, Value>, ExecuteError> { ) -> Result<HashMap<String, Value>, ExecuteError> {
let total_steps = pipeline.spec.steps.len(); let total_steps = pipeline.spec.steps.len();
@@ -161,8 +185,15 @@ impl PipelineExecutor {
tracing::info!("Executing step {} ({}/{})", step.id, idx + 1, total_steps); tracing::info!("Executing step {} ({}/{})", step.id, idx + 1, total_steps);
// Execute action // Execute action with per-step timeout
let result = self.execute_action(&step.action, context).await?; let timeout_duration = std::time::Duration::from_secs(step_timeout_secs);
let result = tokio::time::timeout(
timeout_duration,
self.execute_action(&step.action, context),
).await.map_err(|_| {
tracing::error!("Step {} timed out after {}s", step.id, step_timeout_secs);
ExecuteError::Timeout
})??;
// Store result // Store result
context.set_output(&step.id, result.clone()); context.set_output(&step.id, result.clone());
@@ -336,7 +367,16 @@ impl PipelineExecutor {
} }
Action::Delay { ms } => { Action::Delay { ms } => {
tokio::time::sleep(tokio::time::Duration::from_millis(*ms)).await; let capped_ms = if *ms > MAX_DELAY_MS {
tracing::warn!(
"Delay ms {} exceeds max {}, capping to {}",
ms, MAX_DELAY_MS, MAX_DELAY_MS
);
MAX_DELAY_MS
} else {
*ms
};
tokio::time::sleep(tokio::time::Duration::from_millis(capped_ms)).await;
Ok(Value::Null) Ok(Value::Null)
} }
@@ -508,6 +548,33 @@ impl PipelineExecutor {
pub async fn list_runs(&self) -> Vec<PipelineRun> { pub async fn list_runs(&self) -> Vec<PipelineRun> {
self.runs.read().await.values().cloned().collect() self.runs.read().await.values().cloned().collect()
} }
/// Clean up old completed/failed/cancelled runs to prevent memory leaks.
/// Keeps at most MAX_COMPLETED_RUNS finished runs, evicting the oldest first.
pub async fn cleanup(&self) {
let mut runs = self.runs.write().await;
// Collect IDs of finished runs (completed, failed, cancelled)
let mut finished: Vec<(String, chrono::DateTime<Utc>)> = runs
.iter()
.filter(|(_, r)| matches!(r.status, RunStatus::Completed | RunStatus::Failed | RunStatus::Cancelled))
.map(|(id, r)| (id.clone(), r.ended_at.unwrap_or(r.started_at)))
.collect();
let to_remove = finished.len().saturating_sub(MAX_COMPLETED_RUNS);
if to_remove > 0 {
// Sort by end time ascending (oldest first)
finished.sort_by_key(|(_, t)| *t);
for (id, _) in finished.into_iter().take(to_remove) {
runs.remove(&id);
// Also clean up cancellation flag
drop(runs);
self.cancellations.write().await.remove(&id);
runs = self.runs.write().await;
}
tracing::debug!("Cleaned up {} old pipeline runs", to_remove);
}
}
} }
#[cfg(test)] #[cfg(test)]

View File

@@ -48,7 +48,7 @@ impl ExecutionContext {
steps_output: HashMap::new(), steps_output: HashMap::new(),
variables: HashMap::new(), variables: HashMap::new(),
loop_context: None, loop_context: None,
expr_regex: Regex::new(r"\$\{([^}]+)\}").unwrap(), expr_regex: Regex::new(r"\$\{([^}]+)\}").expect("static regex is valid"),
} }
} }
@@ -73,7 +73,7 @@ impl ExecutionContext {
steps_output, steps_output,
variables, variables,
loop_context: None, loop_context: None,
expr_regex: Regex::new(r"\$\{([^}]+)\}").unwrap(), expr_regex: Regex::new(r"\$\{([^}]+)\}").expect("static regex is valid"),
} }
} }

View File

@@ -1,20 +1,15 @@
//! ZCLAW Protocols //! ZCLAW Protocols
//! //!
//! Protocol support for MCP (Model Context Protocol) and A2A (Agent-to-Agent). //! Protocol support for MCP (Model Context Protocol) and A2A (Agent-to-Agent).
//!
//! A2A is gated behind the `a2a` feature flag (reserved for future multi-agent scenarios).
//! MCP is always available as a framework for tool integration.
mod mcp; mod mcp;
mod mcp_types; mod mcp_types;
mod mcp_tool_adapter; mod mcp_tool_adapter;
mod mcp_transport; mod mcp_transport;
#[cfg(feature = "a2a")]
mod a2a; mod a2a;
pub use mcp::*; pub use mcp::*;
pub use mcp_types::*; pub use mcp_types::*;
pub use mcp_tool_adapter::*; pub use mcp_tool_adapter::*;
pub use mcp_transport::*; pub use mcp_transport::*;
#[cfg(feature = "a2a")]
pub use a2a::*; pub use a2a::*;

View File

@@ -20,7 +20,9 @@ use crate::mcp::{McpClient, McpTool, McpToolCallRequest};
/// so we expose a simple trait here that mirrors the essential Tool interface. /// so we expose a simple trait here that mirrors the essential Tool interface.
/// The runtime side will wrap this in a thin `Tool` impl. /// The runtime side will wrap this in a thin `Tool` impl.
pub struct McpToolAdapter { pub struct McpToolAdapter {
/// Tool name (prefixed with server name to avoid collisions) /// Service name this tool belongs to
service_name: String,
/// Tool name (original from MCP server, NOT prefixed)
name: String, name: String,
/// Tool description /// Tool description
description: String, description: String,
@@ -30,9 +32,22 @@ pub struct McpToolAdapter {
client: Arc<dyn McpClient>, client: Arc<dyn McpClient>,
} }
impl McpToolAdapter { impl Clone for McpToolAdapter {
pub fn new(tool: McpTool, client: Arc<dyn McpClient>) -> Self { fn clone(&self) -> Self {
Self { Self {
service_name: self.service_name.clone(),
name: self.name.clone(),
description: self.description.clone(),
input_schema: self.input_schema.clone(),
client: self.client.clone(),
}
}
}
impl McpToolAdapter {
pub fn new(service_name: String, tool: McpTool, client: Arc<dyn McpClient>) -> Self {
Self {
service_name,
name: tool.name, name: tool.name,
description: tool.description, description: tool.description,
input_schema: tool.input_schema, input_schema: tool.input_schema,
@@ -41,16 +56,29 @@ impl McpToolAdapter {
} }
/// Create adapters for all tools from an MCP server /// Create adapters for all tools from an MCP server
pub async fn from_server(client: Arc<dyn McpClient>) -> Result<Vec<Self>> { pub async fn from_server(service_name: String, client: Arc<dyn McpClient>) -> Result<Vec<Self>> {
let tools = client.list_tools().await?; let tools = client.list_tools().await?;
debug!(count = tools.len(), "Discovered MCP tools"); debug!(count = tools.len(), "Discovered MCP tools");
Ok(tools.into_iter().map(|t| Self::new(t, client.clone())).collect()) Ok(tools.into_iter().map(|t| Self::new(service_name.clone(), t, client.clone())).collect())
} }
pub fn name(&self) -> &str { pub fn name(&self) -> &str {
&self.name &self.name
} }
/// Full qualified name: service_name.tool_name (for ToolRegistry to avoid collisions)
pub fn qualified_name(&self) -> String {
format!("{}.{}", self.service_name, self.name)
}
pub fn service_name(&self) -> &str {
&self.service_name
}
pub fn tool_name(&self) -> &str {
&self.name
}
pub fn description(&self) -> &str { pub fn description(&self) -> &str {
&self.description &self.description
} }
@@ -102,7 +130,7 @@ impl McpToolAdapter {
match result.len() { match result.len() {
0 => Ok(Value::Null), 0 => Ok(Value::Null),
1 => Ok(result.into_iter().next().unwrap()), 1 => Ok(result.into_iter().next().unwrap_or(Value::Null)),
_ => Ok(Value::Array(result)), _ => Ok(Value::Array(result)),
} }
} }
@@ -129,10 +157,10 @@ impl McpServiceManager {
name: String, name: String,
client: Arc<dyn McpClient>, client: Arc<dyn McpClient>,
) -> Result<Vec<&McpToolAdapter>> { ) -> Result<Vec<&McpToolAdapter>> {
let adapters = McpToolAdapter::from_server(client.clone()).await?; let adapters = McpToolAdapter::from_server(name.clone(), client.clone()).await?;
self.clients.insert(name.clone(), client); self.clients.insert(name.clone(), client);
self.adapters.insert(name.clone(), adapters); self.adapters.insert(name.clone(), adapters);
Ok(self.adapters.get(&name).unwrap().iter().collect()) Ok(self.adapters.get(&name).map(|v| v.iter().collect()).unwrap_or_default())
} }
/// Get all registered tool adapters from all services /// Get all registered tool adapters from all services

View File

@@ -84,12 +84,20 @@ impl McpServerConfig {
} }
} }
/// Combined transport handles (stdin + stdout) behind a single Mutex.
/// This ensures write-then-read is atomic, preventing concurrent requests
/// from receiving each other's responses.
struct TransportHandles {
stdin: BufWriter<ChildStdin>,
stdout: BufReader<ChildStdout>,
}
/// MCP Transport using stdio /// MCP Transport using stdio
pub struct McpTransport { pub struct McpTransport {
config: McpServerConfig, config: McpServerConfig,
child: Arc<Mutex<Option<Child>>>, child: Arc<Mutex<Option<Child>>>,
stdin: Arc<Mutex<Option<BufWriter<ChildStdin>>>>, /// Single Mutex protecting both stdin and stdout for atomic write-then-read
stdout: Arc<Mutex<Option<BufReader<ChildStdout>>>>, handles: Arc<Mutex<Option<TransportHandles>>>,
capabilities: Arc<Mutex<Option<ServerCapabilities>>>, capabilities: Arc<Mutex<Option<ServerCapabilities>>>,
} }
@@ -99,8 +107,7 @@ impl McpTransport {
Self { Self {
config, config,
child: Arc::new(Mutex::new(None)), child: Arc::new(Mutex::new(None)),
stdin: Arc::new(Mutex::new(None)), handles: Arc::new(Mutex::new(None)),
stdout: Arc::new(Mutex::new(None)),
capabilities: Arc::new(Mutex::new(None)), capabilities: Arc::new(Mutex::new(None)),
} }
} }
@@ -162,9 +169,11 @@ impl McpTransport {
}); });
} }
// Store handles in separate mutexes // Store handles in single mutex for atomic write-then-read
*self.stdin.lock().await = Some(BufWriter::new(stdin)); *self.handles.lock().await = Some(TransportHandles {
*self.stdout.lock().await = Some(BufReader::new(stdout)); stdin: BufWriter::new(stdin),
stdout: BufReader::new(stdout),
});
*child_guard = Some(child); *child_guard = Some(child);
Ok(()) Ok(())
@@ -201,21 +210,21 @@ impl McpTransport {
let line = serde_json::to_string(notification) let line = serde_json::to_string(notification)
.map_err(|e| ZclawError::McpError(format!("Failed to serialize notification: {}", e)))?; .map_err(|e| ZclawError::McpError(format!("Failed to serialize notification: {}", e)))?;
let mut stdin_guard = self.stdin.lock().await; let mut handles_guard = self.handles.lock().await;
let stdin = stdin_guard.as_mut() let handles = handles_guard.as_mut()
.ok_or_else(|| ZclawError::McpError("Transport not started".to_string()))?; .ok_or_else(|| ZclawError::McpError("Transport not started".to_string()))?;
stdin.write_all(line.as_bytes()) handles.stdin.write_all(line.as_bytes())
.map_err(|e| ZclawError::McpError(format!("Failed to write notification: {}", e)))?; .map_err(|e| ZclawError::McpError(format!("Failed to write notification: {}", e)))?;
stdin.write_all(b"\n") handles.stdin.write_all(b"\n")
.map_err(|e| ZclawError::McpError(format!("Failed to write newline: {}", e)))?; .map_err(|e| ZclawError::McpError(format!("Failed to write newline: {}", e)))?;
stdin.flush() handles.stdin.flush()
.map_err(|e| ZclawError::McpError(format!("Failed to flush notification: {}", e)))?; .map_err(|e| ZclawError::McpError(format!("Failed to flush notification: {}", e)))?;
Ok(()) Ok(())
} }
/// Send JSON-RPC request /// Send JSON-RPC request (atomic write-then-read under single lock)
async fn send_request<T: DeserializeOwned>( async fn send_request<T: DeserializeOwned>(
&self, &self,
method: &str, method: &str,
@@ -234,28 +243,23 @@ impl McpTransport {
let line = serde_json::to_string(&request) let line = serde_json::to_string(&request)
.map_err(|e| ZclawError::McpError(format!("Failed to serialize request: {}", e)))?; .map_err(|e| ZclawError::McpError(format!("Failed to serialize request: {}", e)))?;
// Write to stdin // Atomic write-then-read under single lock
{
let mut stdin_guard = self.stdin.lock().await;
let stdin = stdin_guard.as_mut()
.ok_or_else(|| ZclawError::McpError("Transport not started".to_string()))?;
stdin.write_all(line.as_bytes())
.map_err(|e| ZclawError::McpError(format!("Failed to write request: {}", e)))?;
stdin.write_all(b"\n")
.map_err(|e| ZclawError::McpError(format!("Failed to write newline: {}", e)))?;
stdin.flush()
.map_err(|e| ZclawError::McpError(format!("Failed to flush request: {}", e)))?;
}
// Read from stdout
let response_line = { let response_line = {
let mut stdout_guard = self.stdout.lock().await; let mut handles_guard = self.handles.lock().await;
let stdout = stdout_guard.as_mut() let handles = handles_guard.as_mut()
.ok_or_else(|| ZclawError::McpError("Transport not started".to_string()))?; .ok_or_else(|| ZclawError::McpError("Transport not started".to_string()))?;
// Write to stdin
handles.stdin.write_all(line.as_bytes())
.map_err(|e| ZclawError::McpError(format!("Failed to write request: {}", e)))?;
handles.stdin.write_all(b"\n")
.map_err(|e| ZclawError::McpError(format!("Failed to write newline: {}", e)))?;
handles.stdin.flush()
.map_err(|e| ZclawError::McpError(format!("Failed to flush request: {}", e)))?;
// Read from stdout (still holding the lock — no interleaving possible)
let mut response_line = String::new(); let mut response_line = String::new();
stdout.read_line(&mut response_line) handles.stdout.read_line(&mut response_line)
.map_err(|e| ZclawError::McpError(format!("Failed to read response: {}", e)))?; .map_err(|e| ZclawError::McpError(format!("Failed to read response: {}", e)))?;
response_line response_line
}; };
@@ -429,7 +433,7 @@ impl Drop for McpTransport {
let _ = child.wait(); let _ = child.wait();
} }
Err(e) => { Err(e) => {
eprintln!("[McpTransport] Failed to kill child process: {}", e); tracing::warn!("[McpTransport] Failed to kill child process (potential zombie): {}", e);
} }
} }
} }

View File

@@ -0,0 +1,55 @@
//! Tests for MCP Transport configuration (McpServerConfig)
//!
//! These tests cover McpServerConfig builder methods without spawning processes.
use std::collections::HashMap;
use zclaw_protocols::McpServerConfig;
#[test]
fn npx_config_creates_correct_command() {
let config = McpServerConfig::npx("@modelcontextprotocol/server-memory");
assert_eq!(config.command, "npx");
assert_eq!(config.args, vec!["-y", "@modelcontextprotocol/server-memory"]);
assert!(config.env.is_empty());
assert!(config.cwd.is_none());
}
#[test]
fn node_config_creates_correct_command() {
let config = McpServerConfig::node("/path/to/server.js");
assert_eq!(config.command, "node");
assert_eq!(config.args, vec!["/path/to/server.js"]);
}
#[test]
fn python_config_creates_correct_command() {
let config = McpServerConfig::python("mcp_server.py");
assert_eq!(config.command, "python");
assert_eq!(config.args, vec!["mcp_server.py"]);
}
#[test]
fn env_adds_variables() {
let config = McpServerConfig::node("server.js")
.env("API_KEY", "secret123")
.env("DEBUG", "true");
assert_eq!(config.env.get("API_KEY").unwrap(), "secret123");
assert_eq!(config.env.get("DEBUG").unwrap(), "true");
}
#[test]
fn cwd_sets_working_directory() {
let config = McpServerConfig::node("server.js").cwd("/tmp/work");
assert_eq!(config.cwd.unwrap(), "/tmp/work");
}
#[test]
fn combined_builder_pattern() {
let config = McpServerConfig::npx("@scope/server")
.env("PORT", "3000")
.cwd("/app");
assert_eq!(config.command, "npx");
assert_eq!(config.args.len(), 2);
assert_eq!(config.env.len(), 1);
assert_eq!(config.cwd.unwrap(), "/app");
}

View File

@@ -0,0 +1,186 @@
//! Tests for MCP domain types (mcp.rs) — McpTool, McpContent, McpResource, etc.
use std::collections::HashMap;
use zclaw_protocols::*;
// === McpTool ===
#[test]
fn mcp_tool_roundtrip() {
let tool = McpTool {
name: "search".to_string(),
description: "Search documents".to_string(),
input_schema: serde_json::json!({"type": "object", "properties": {"query": {"type": "string"}}}),
};
let json = serde_json::to_string(&tool).unwrap();
let parsed: McpTool = serde_json::from_str(&json).unwrap();
assert_eq!(parsed.name, "search");
assert_eq!(parsed.description, "Search documents");
}
#[test]
fn mcp_tool_empty_description() {
let tool = McpTool {
name: "ping".to_string(),
description: String::new(),
input_schema: serde_json::json!({}),
};
let parsed: McpTool = serde_json::from_str(&serde_json::to_string(&tool).unwrap()).unwrap();
assert!(parsed.description.is_empty());
}
// === McpContent ===
#[test]
fn mcp_content_text_roundtrip() {
let content = McpContent::Text { text: "hello".to_string() };
let json = serde_json::to_string(&content).unwrap();
let parsed: McpContent = serde_json::from_str(&json).unwrap();
match parsed {
McpContent::Text { text } => assert_eq!(text, "hello"),
_ => panic!("Expected Text"),
}
}
#[test]
fn mcp_content_image_roundtrip() {
let content = McpContent::Image {
data: "base64==".to_string(),
mime_type: "image/png".to_string(),
};
let json = serde_json::to_string(&content).unwrap();
let parsed: McpContent = serde_json::from_str(&json).unwrap();
match parsed {
McpContent::Image { data, mime_type } => {
assert_eq!(data, "base64==");
assert_eq!(mime_type, "image/png");
}
_ => panic!("Expected Image"),
}
}
#[test]
fn mcp_content_resource_roundtrip() {
let content = McpContent::Resource {
resource: McpResourceContent {
uri: "file:///test.txt".to_string(),
mime_type: Some("text/plain".to_string()),
text: Some("content".to_string()),
blob: None,
},
};
let json = serde_json::to_string(&content).unwrap();
let parsed: McpContent = serde_json::from_str(&json).unwrap();
match parsed {
McpContent::Resource { resource } => {
assert_eq!(resource.uri, "file:///test.txt");
assert_eq!(resource.text.unwrap(), "content");
}
_ => panic!("Expected Resource"),
}
}
// === McpToolCallRequest ===
#[test]
fn mcp_tool_call_request_serialization() {
let mut args = HashMap::new();
args.insert("query".to_string(), serde_json::json!("test"));
let req = McpToolCallRequest {
name: "search".to_string(),
arguments: args,
};
let json = serde_json::to_string(&req).unwrap();
assert!(json.contains("\"name\":\"search\""));
assert!(json.contains("\"query\":\"test\""));
}
// === McpToolCallResponse ===
#[test]
fn mcp_tool_call_response_parse_success() {
let json = r#"{"content":[{"type":"text","text":"found 3 results"}],"is_error":false}"#;
let resp: McpToolCallResponse = serde_json::from_str(json).unwrap();
assert!(!resp.is_error);
assert_eq!(resp.content.len(), 1);
}
#[test]
fn mcp_tool_call_response_parse_error() {
let json = r#"{"content":[{"type":"text","text":"tool not found"}],"is_error":true}"#;
let resp: McpToolCallResponse = serde_json::from_str(json).unwrap();
assert!(resp.is_error);
}
// === McpResource ===
#[test]
fn mcp_resource_roundtrip() {
let res = McpResource {
uri: "file:///doc.md".to_string(),
name: "Documentation".to_string(),
description: Some("Project docs".to_string()),
mime_type: Some("text/markdown".to_string()),
};
let json = serde_json::to_string(&res).unwrap();
let parsed: McpResource = serde_json::from_str(&json).unwrap();
assert_eq!(parsed.uri, "file:///doc.md");
assert_eq!(parsed.description.unwrap(), "Project docs");
}
// === McpPrompt ===
#[test]
fn mcp_prompt_roundtrip() {
let prompt = McpPrompt {
name: "summarize".to_string(),
description: "Summarize text".to_string(),
arguments: vec![
McpPromptArgument {
name: "length".to_string(),
description: "Target length".to_string(),
required: false,
},
],
};
let json = serde_json::to_string(&prompt).unwrap();
let parsed: McpPrompt = serde_json::from_str(&json).unwrap();
assert_eq!(parsed.arguments.len(), 1);
assert!(!parsed.arguments[0].required);
}
// === McpServerInfo ===
#[test]
fn mcp_server_info_roundtrip() {
let info = McpServerInfo {
name: "test-mcp".to_string(),
version: "2.0.0".to_string(),
protocol_version: "2024-11-05".to_string(),
};
let json = serde_json::to_string(&info).unwrap();
let parsed: McpServerInfo = serde_json::from_str(&json).unwrap();
assert_eq!(parsed.name, "test-mcp");
assert_eq!(parsed.protocol_version, "2024-11-05");
}
// === McpCapabilities ===
#[test]
fn mcp_capabilities_default_empty() {
let caps = McpCapabilities::default();
assert!(caps.tools.is_none());
assert!(caps.resources.is_none());
assert!(caps.prompts.is_none());
}
#[test]
fn mcp_capabilities_with_tools() {
let caps = McpCapabilities {
tools: Some(McpToolCapabilities { list_changed: true }),
resources: None,
prompts: None,
};
let json = serde_json::to_string(&caps).unwrap();
assert!(json.contains("\"list_changed\":true"));
}

View File

@@ -0,0 +1,267 @@
//! Tests for MCP JSON-RPC types (mcp_types.rs)
//!
//! Covers: serialization, deserialization, builder patterns, edge cases.
use serde_json;
use zclaw_protocols::*;
// === JsonRpcRequest ===
#[test]
fn jsonrpc_request_new_has_correct_defaults() {
let req = JsonRpcRequest::new(42, "tools/list");
assert_eq!(req.jsonrpc, "2.0");
assert_eq!(req.id, 42);
assert_eq!(req.method, "tools/list");
assert!(req.params.is_none());
}
#[test]
fn jsonrpc_request_with_params() {
let req = JsonRpcRequest::new(1, "tools/call")
.with_params(serde_json::json!({"name": "search"}));
let serialized = serde_json::to_string(&req).unwrap();
assert!(serialized.contains("\"params\""));
assert!(serialized.contains("\"name\":\"search\""));
}
#[test]
fn jsonrpc_request_skip_null_params() {
let req = JsonRpcRequest::new(1, "ping");
let serialized = serde_json::to_string(&req).unwrap();
// params is None, should be skipped
assert!(!serialized.contains("\"params\""));
}
// === JsonRpcResponse ===
#[test]
fn jsonrpc_response_parse_success() {
let json = r#"{"jsonrpc":"2.0","id":1,"result":{"tools":[]}}"#;
let resp: JsonRpcResponse = serde_json::from_str(json).unwrap();
assert_eq!(resp.id, 1);
assert!(resp.result.is_some());
assert!(resp.error.is_none());
}
#[test]
fn jsonrpc_response_parse_error() {
let json = r#"{"jsonrpc":"2.0","id":2,"error":{"code":-32600,"message":"Invalid Request"}}"#;
let resp: JsonRpcResponse = serde_json::from_str(json).unwrap();
assert_eq!(resp.id, 2);
assert!(resp.result.is_none());
let err = resp.error.unwrap();
assert_eq!(err.code, -32600);
assert_eq!(err.message, "Invalid Request");
}
#[test]
fn jsonrpc_response_parse_error_with_data() {
let json = r#"{"jsonrpc":"2.0","id":3,"error":{"code":-32602,"message":"Bad params","data":{"field":"uri"}}}"#;
let resp: JsonRpcResponse = serde_json::from_str(json).unwrap();
let err = resp.error.unwrap();
assert!(err.data.is_some());
assert_eq!(err.data.unwrap()["field"], "uri");
}
// === InitializeRequest ===
#[test]
fn initialize_request_default() {
let req = InitializeRequest::default();
assert_eq!(req.protocol_version, "2024-11-05");
assert_eq!(req.client_info.name, "zclaw");
assert!(!req.client_info.version.is_empty());
}
#[test]
fn initialize_request_serializes() {
let req = InitializeRequest::default();
let json = serde_json::to_string(&req).unwrap();
assert!(json.contains("\"protocol_version\":\"2024-11-05\""));
assert!(json.contains("\"client_info\""));
}
// === ServerCapabilities ===
#[test]
fn server_capabilities_empty() {
let json = r#"{"protocol_version":"2024-11-05","capabilities":{},"server_info":{"name":"test","version":"1.0"}}"#;
let result: InitializeResult = serde_json::from_str(json).unwrap();
assert!(result.capabilities.tools.is_none());
assert!(result.capabilities.resources.is_none());
}
#[test]
fn server_capabilities_with_tools() {
let json = r#"{"protocol_version":"2024-11-05","capabilities":{"tools":{"list_changed":true}},"server_info":{"name":"test","version":"1.0"}}"#;
let result: InitializeResult = serde_json::from_str(json).unwrap();
let tools = result.capabilities.tools.unwrap();
assert!(tools.list_changed);
}
// === ContentBlock ===
#[test]
fn content_block_text() {
let json = r#"{"type":"text","text":"hello world"}"#;
let block: ContentBlock = serde_json::from_str(json).unwrap();
match block {
ContentBlock::Text { text } => assert_eq!(text, "hello world"),
_ => panic!("Expected Text variant"),
}
}
#[test]
fn content_block_image() {
let json = r#"{"type":"image","data":"base64data","mime_type":"image/png"}"#;
let block: ContentBlock = serde_json::from_str(json).unwrap();
match block {
ContentBlock::Image { data, mime_type } => {
assert_eq!(data, "base64data");
assert_eq!(mime_type, "image/png");
}
_ => panic!("Expected Image variant"),
}
}
#[test]
fn content_block_resource() {
let json = r#"{"type":"resource","resource":{"uri":"file:///test.txt","text":"content"}}"#;
let block: ContentBlock = serde_json::from_str(json).unwrap();
match block {
ContentBlock::Resource { resource } => {
assert_eq!(resource.uri, "file:///test.txt");
assert_eq!(resource.text.unwrap(), "content");
}
_ => panic!("Expected Resource variant"),
}
}
// === CallToolResult ===
#[test]
fn call_tool_result_parse() {
let json = r#"{"content":[{"type":"text","text":"result"}],"is_error":false}"#;
let result: CallToolResult = serde_json::from_str(json).unwrap();
assert!(!result.is_error);
assert_eq!(result.content.len(), 1);
}
#[test]
fn call_tool_result_error() {
let json = r#"{"content":[{"type":"text","text":"something went wrong"}],"is_error":true}"#;
let result: CallToolResult = serde_json::from_str(json).unwrap();
assert!(result.is_error);
}
// === ListToolsResult ===
#[test]
fn list_tools_result_with_cursor() {
let json = r#"{"tools":[{"name":"search","input_schema":{"type":"object"}}],"next_cursor":"abc123"}"#;
let result: ListToolsResult = serde_json::from_str(json).unwrap();
assert_eq!(result.tools.len(), 1);
assert_eq!(result.tools[0].name, "search");
assert_eq!(result.next_cursor.unwrap(), "abc123");
}
#[test]
fn list_tools_result_without_cursor() {
let json = r#"{"tools":[]}"#;
let result: ListToolsResult = serde_json::from_str(json).unwrap();
assert!(result.tools.is_empty());
assert!(result.next_cursor.is_none());
}
// === Resource types ===
#[test]
fn resource_parse_with_optional_fields() {
let json = r#"{"uri":"file:///doc.txt","name":"doc","description":"A doc","mime_type":"text/plain"}"#;
let res: Resource = serde_json::from_str(json).unwrap();
assert_eq!(res.uri, "file:///doc.txt");
assert_eq!(res.name, "doc");
assert_eq!(res.description.unwrap(), "A doc");
assert_eq!(res.mime_type.unwrap(), "text/plain");
}
#[test]
fn resource_parse_minimal() {
let json = r#"{"uri":"file:///x","name":"x"}"#;
let res: Resource = serde_json::from_str(json).unwrap();
assert!(res.description.is_none());
assert!(res.mime_type.is_none());
}
// === LoggingLevel ===
#[test]
fn logging_level_serialize_roundtrip() {
let levels = vec![
LoggingLevel::Debug,
LoggingLevel::Info,
LoggingLevel::Warning,
LoggingLevel::Error,
LoggingLevel::Critical,
LoggingLevel::Emergency,
];
for level in levels {
let json = serde_json::to_string(&level).unwrap();
let parsed: LoggingLevel = serde_json::from_str(&json).unwrap();
assert_eq!(std::mem::discriminant(&level), std::mem::discriminant(&parsed));
}
}
// === InitializedNotification ===
#[test]
fn initialized_notification_fields() {
let n = InitializedNotification::new();
assert_eq!(n.jsonrpc, "2.0");
assert_eq!(n.method, "notifications/initialized");
}
#[test]
fn initialized_notification_serializes() {
let n = InitializedNotification::default();
let json = serde_json::to_string(&n).unwrap();
assert!(json.contains("\"notifications/initialized\""));
}
// === Prompt types ===
#[test]
fn prompt_parse_with_arguments() {
let json = r#"{"name":"greet","description":"Greeting","arguments":[{"name":"lang","description":"Language","required":true}]}"#;
let prompt: Prompt = serde_json::from_str(json).unwrap();
assert_eq!(prompt.name, "greet");
assert_eq!(prompt.arguments.len(), 1);
assert!(prompt.arguments[0].required);
}
#[test]
fn prompt_message_parse() {
let json = r#"{"role":"user","content":{"type":"text","text":"hello"}}"#;
let msg: PromptMessage = serde_json::from_str(json).unwrap();
assert_eq!(msg.role, "user");
}
// === McpClientConfig ===
#[test]
fn mcp_client_config_roundtrip() {
let config = McpClientConfig {
server_url: "http://localhost:3000".to_string(),
server_info: McpServerInfo {
name: "test-server".to_string(),
version: "1.0.0".to_string(),
protocol_version: "2024-11-05".to_string(),
},
capabilities: McpCapabilities::default(),
};
let json = serde_json::to_string(&config).unwrap();
let parsed: McpClientConfig = serde_json::from_str(&json).unwrap();
assert_eq!(parsed.server_url, config.server_url);
assert_eq!(parsed.server_info.name, "test-server");
}

View File

@@ -11,6 +11,7 @@ description = "ZCLAW runtime with LLM drivers and agent loop"
zclaw-types = { workspace = true } zclaw-types = { workspace = true }
zclaw-memory = { workspace = true } zclaw-memory = { workspace = true }
zclaw-growth = { workspace = true } zclaw-growth = { workspace = true }
zclaw-protocols = { workspace = true }
tokio = { workspace = true } tokio = { workspace = true }
tokio-stream = { workspace = true } tokio-stream = { workspace = true }

View File

@@ -231,15 +231,19 @@ impl AnthropicDriver {
input: input.clone(), input: input.clone(),
}], }],
}), }),
zclaw_types::Message::ToolResult { tool_call_id: _, tool: _, output, is_error } => { zclaw_types::Message::ToolResult { tool_call_id, tool: _, output, is_error } => {
let content = if *is_error { let content_text = if *is_error {
format!("Error: {}", output) format!("Error: {}", output)
} else { } else {
output.to_string() output.to_string()
}; };
Some(AnthropicMessage { Some(AnthropicMessage {
role: "user".to_string(), role: "user".to_string(),
content: vec![ContentBlock::Text { text: content }], content: vec![ContentBlock::ToolResult {
tool_use_id: tool_call_id.clone(),
content: content_text,
is_error: *is_error,
}],
}) })
} }
_ => None, _ => None,

View File

@@ -616,7 +616,7 @@ struct GeminiResponseContent {
#[serde(default)] #[serde(default)]
parts: Vec<GeminiResponsePart>, parts: Vec<GeminiResponsePart>,
#[serde(default)] #[serde(default)]
#[allow(dead_code)] #[allow(dead_code)] // @reserved: deserialized from Gemini API, not accessed in code
role: Option<String>, role: Option<String>,
} }
@@ -643,7 +643,7 @@ struct GeminiUsageMetadata {
#[serde(default)] #[serde(default)]
candidates_token_count: Option<u32>, candidates_token_count: Option<u32>,
#[serde(default)] #[serde(default)]
#[allow(dead_code)] #[allow(dead_code)] // @reserved: deserialized from Gemini API, not accessed in code
total_token_count: Option<u32>, total_token_count: Option<u32>,
} }

View File

@@ -116,6 +116,13 @@ pub enum ContentBlock {
Text { text: String }, Text { text: String },
Thinking { thinking: String }, Thinking { thinking: String },
ToolUse { id: String, name: String, input: serde_json::Value }, ToolUse { id: String, name: String, input: serde_json::Value },
/// Anthropic API tool result — must be sent as `role: "user"` with this content block.
ToolResult {
tool_use_id: String,
content: String,
#[serde(skip_serializing_if = "std::ops::Not::not")]
is_error: bool,
},
} }
/// Stop reason /// Stop reason

View File

@@ -737,6 +737,9 @@ impl OpenAiDriver {
input: input.clone(), input: input.clone(),
}); });
} }
ContentBlock::ToolResult { .. } => {
// ToolResult is only used in request messages, never in responses
}
} }
} }

View File

@@ -12,11 +12,12 @@
use std::sync::Arc; use std::sync::Arc;
use zclaw_growth::{ use zclaw_growth::{
GrowthTracker, InjectionFormat, LlmDriverForExtraction, AggregatedPattern, CombinedExtraction, EvolutionConfig, EvolutionEngine,
MemoryExtractor, MemoryRetriever, PromptInjector, RetrievalResult, ExperienceExtractor, ExperienceStore, GrowthTracker, InjectionFormat,
VikingAdapter, LlmDriverForExtraction, MemoryExtractor, MemoryRetriever, PromptInjector,
RetrievalResult, UserProfileUpdater, VikingAdapter,
}; };
use zclaw_memory::{ExtractedFactBatch, Fact, FactCategory}; use zclaw_memory::{ExtractedFactBatch, Fact, FactCategory, UserProfileStore};
use zclaw_types::{AgentId, Message, Result, SessionId}; use zclaw_types::{AgentId, Message, Result, SessionId};
/// Growth system integration for AgentLoop /// Growth system integration for AgentLoop
@@ -32,6 +33,14 @@ pub struct GrowthIntegration {
injector: PromptInjector, injector: PromptInjector,
/// Growth tracker for tracking growth metrics /// Growth tracker for tracking growth metrics
tracker: GrowthTracker, tracker: GrowthTracker,
/// Experience extractor for structured experience persistence
experience_extractor: ExperienceExtractor,
/// Profile updater for incremental user profile updates
profile_updater: UserProfileUpdater,
/// User profile store (optional, for profile updates)
profile_store: Option<Arc<UserProfileStore>>,
/// Evolution engine for L2 skill generation (optional)
evolution_engine: Option<EvolutionEngine>,
/// Configuration /// Configuration
config: GrowthConfigInner, config: GrowthConfigInner,
} }
@@ -69,13 +78,19 @@ impl GrowthIntegration {
let retriever = MemoryRetriever::new(viking.clone()); let retriever = MemoryRetriever::new(viking.clone());
let injector = PromptInjector::new(); let injector = PromptInjector::new();
let tracker = GrowthTracker::new(viking); let tracker = GrowthTracker::new(viking.clone());
let evolution_engine = Some(EvolutionEngine::new(viking.clone()));
Self { Self {
retriever, retriever,
extractor, extractor,
injector, injector,
tracker, tracker,
experience_extractor: ExperienceExtractor::new()
.with_store(Arc::new(ExperienceStore::new(viking))),
profile_updater: UserProfileUpdater::new(),
profile_store: None,
evolution_engine,
config: GrowthConfigInner::default(), config: GrowthConfigInner::default(),
} }
} }
@@ -102,11 +117,85 @@ impl GrowthIntegration {
self.config.enabled self.config.enabled
} }
/// 启动时初始化:从持久化存储恢复进化引擎的信任度记录
///
/// **注意**FeedbackCollector 内部已实现 lazy-load首次 save() 时自动加载),
/// 所以此方法为可选优化 — 提前加载可避免首次反馈提交时的延迟。
pub async fn initialize(&self) -> Result<()> {
if let Some(ref engine) = self.evolution_engine {
match engine.load_feedback().await {
Ok(count) => {
if count > 0 {
tracing::info!(
"[GrowthIntegration] Loaded {} trust records from storage",
count
);
}
}
Err(e) => {
tracing::warn!(
"[GrowthIntegration] Failed to load trust records: {}",
e
);
}
}
}
Ok(())
}
/// Enable or disable auto extraction /// Enable or disable auto extraction
pub fn set_auto_extract(&mut self, auto_extract: bool) { pub fn set_auto_extract(&mut self, auto_extract: bool) {
self.config.auto_extract = auto_extract; self.config.auto_extract = auto_extract;
} }
/// Configure embedding client for memory retrieval.
///
/// Propagates the embedding client to the MemoryRetriever's SemanticScorer,
/// enabling embedding-based similarity in addition to TF-IDF.
/// Safe to call from non-async contexts.
pub fn configure_embedding(
&self,
client: Arc<dyn zclaw_growth::retrieval::semantic::EmbeddingClient>,
) {
self.retriever.set_embedding_client(client);
}
/// Set the user profile store for incremental profile updates
pub fn with_profile_store(mut self, store: Arc<UserProfileStore>) -> Self {
self.profile_store = Some(store);
self
}
/// Set the evolution engine configuration
pub fn with_evolution_config(self, config: EvolutionConfig) -> Self {
let engine = self.evolution_engine.unwrap_or_else(|| {
EvolutionEngine::new(Arc::new(VikingAdapter::in_memory()))
});
Self {
evolution_engine: Some(engine.with_config(config)),
..self
}
}
/// Enable or disable the evolution engine
pub fn set_evolution_enabled(&mut self, enabled: bool) {
if let Some(ref mut engine) = self.evolution_engine {
engine.set_enabled(enabled);
}
}
/// L2 检查:是否有可进化的模式
/// 在 extract_combined 之后调用,返回可固化的经验模式列表
pub async fn check_evolution(
&self,
agent_id: &AgentId,
) -> Result<Vec<AggregatedPattern>> {
match &self.evolution_engine {
Some(engine) => engine.check_evolvable_patterns(&agent_id.to_string()).await,
None => Ok(Vec::new()),
}
}
/// Enhance system prompt with retrieved memories /// Enhance system prompt with retrieved memories
/// ///
/// This method: /// This method:
@@ -213,8 +302,8 @@ impl GrowthIntegration {
Ok(count) Ok(count)
} }
/// Combined extraction: single LLM call that produces both stored memories /// Combined extraction: single LLM call that produces stored memories,
/// and structured facts, avoiding double extraction overhead. /// structured experiences, and profile signals — all in one pass.
/// ///
/// Returns `(memory_count, Option<ExtractedFactBatch>)` on success. /// Returns `(memory_count, Option<ExtractedFactBatch>)` on success.
pub async fn extract_combined( pub async fn extract_combined(
@@ -227,25 +316,28 @@ impl GrowthIntegration {
return Ok(None); return Ok(None);
} }
// Single LLM extraction call // 单次 LLM 提取memories + experiences + profile_signals
let extracted = self let combined = self
.extractor .extractor
.extract(messages, session_id.clone()) .extract_combined(messages, session_id.clone())
.await .await
.unwrap_or_else(|e| { .unwrap_or_else(|e| {
tracing::warn!("[GrowthIntegration] Combined extraction failed: {}", e); tracing::warn!("[GrowthIntegration] Combined extraction failed: {}", e);
Vec::new() CombinedExtraction::default()
}); });
if extracted.is_empty() { if combined.memories.is_empty()
&& combined.experiences.is_empty()
&& !combined.profile_signals.has_any_signal()
{
return Ok(None); return Ok(None);
} }
let mem_count = extracted.len(); let mem_count = combined.memories.len();
// Store raw memories // Store raw memories
self.extractor self.extractor
.store_memories(&agent_id.to_string(), &extracted) .store_memories(&agent_id.to_string(), &combined.memories)
.await?; .await?;
// Track learning event // Track learning event
@@ -253,8 +345,71 @@ impl GrowthIntegration {
.record_learning(agent_id, &session_id.to_string(), mem_count) .record_learning(agent_id, &session_id.to_string(), mem_count)
.await?; .await?;
// Convert same extracted memories to structured facts (no extra LLM call) // Persist structured experiences (L1 enhancement)
let facts: Vec<Fact> = extracted if let Ok(exp_count) = self
.experience_extractor
.persist_experiences(&agent_id.to_string(), &combined)
.await
{
if exp_count > 0 {
tracing::debug!(
"[GrowthIntegration] Persisted {} structured experiences",
exp_count
);
}
}
// Update user profile from extraction signals (L1 enhancement)
if let Some(profile_store) = &self.profile_store {
let updates = self.profile_updater.collect_updates(&combined);
let user_id = agent_id.to_string();
for update in updates {
let result = match update.kind {
zclaw_growth::ProfileUpdateKind::SetField => {
profile_store
.update_field(&user_id, &update.field, &update.value)
.await
}
zclaw_growth::ProfileUpdateKind::AppendArray => {
match update.field.as_str() {
"recent_topic" => {
profile_store
.add_recent_topic(&user_id, &update.value, 10)
.await
}
"pain_point" => {
profile_store
.add_pain_point(&user_id, &update.value, 10)
.await
}
"preferred_tool" => {
profile_store
.add_preferred_tool(&user_id, &update.value, 10)
.await
}
_ => {
tracing::warn!(
"[GrowthIntegration] Unknown array field: {}",
update.field
);
Ok(())
}
}
}
};
if let Err(e) = result {
tracing::warn!(
"[GrowthIntegration] Profile update failed for {}: {}",
update.field,
e
);
}
}
}
// Convert extracted memories to structured facts
let facts: Vec<Fact> = combined
.memories
.into_iter() .into_iter()
.map(|m| { .map(|m| {
let category = match m.memory_type { let category = match m.memory_type {

View File

@@ -34,3 +34,4 @@ pub use zclaw_growth::EmbeddingClient;
pub use zclaw_growth::LlmDriverForExtraction; pub use zclaw_growth::LlmDriverForExtraction;
pub use compaction::{CompactionConfig, CompactionOutcome}; pub use compaction::{CompactionConfig, CompactionOutcome};
pub use prompt::{PromptBuilder, PromptContext, PromptSection}; pub use prompt::{PromptBuilder, PromptContext, PromptSection};
pub use middleware::butler_router::{ButlerRouterMiddleware, IndustryKeywordConfig};

View File

@@ -1,16 +1,14 @@
//! Agent loop implementation //! Agent loop implementation
use std::sync::Arc; use std::sync::Arc;
use std::sync::Mutex;
use futures::StreamExt; use futures::StreamExt;
use tokio::sync::mpsc; use tokio::sync::mpsc;
use zclaw_types::{AgentId, SessionId, Message, Result}; use zclaw_types::{AgentId, SessionId, Message, Result};
use crate::driver::{LlmDriver, CompletionRequest, ContentBlock}; use crate::driver::{LlmDriver, CompletionRequest, ContentBlock};
use crate::stream::StreamChunk; use crate::stream::StreamChunk;
use crate::tool::{ToolRegistry, ToolContext, SkillExecutor}; use crate::tool::{ToolRegistry, ToolContext, SkillExecutor, HandExecutor};
use crate::tool::builtin::PathValidator; use crate::tool::builtin::PathValidator;
use crate::loop_guard::{LoopGuard, LoopGuardResult};
use crate::growth::GrowthIntegration; use crate::growth::GrowthIntegration;
use crate::compaction::{self, CompactionConfig}; use crate::compaction::{self, CompactionConfig};
use crate::middleware::{self, MiddlewareChain}; use crate::middleware::{self, MiddlewareChain};
@@ -23,7 +21,6 @@ pub struct AgentLoop {
driver: Arc<dyn LlmDriver>, driver: Arc<dyn LlmDriver>,
tools: ToolRegistry, tools: ToolRegistry,
memory: Arc<MemoryStore>, memory: Arc<MemoryStore>,
loop_guard: Mutex<LoopGuard>,
model: String, model: String,
system_prompt: Option<String>, system_prompt: Option<String>,
/// Custom agent personality for prompt assembly /// Custom agent personality for prompt assembly
@@ -31,6 +28,7 @@ pub struct AgentLoop {
max_tokens: u32, max_tokens: u32,
temperature: f32, temperature: f32,
skill_executor: Option<Arc<dyn SkillExecutor>>, skill_executor: Option<Arc<dyn SkillExecutor>>,
hand_executor: Option<Arc<dyn HandExecutor>>,
path_validator: Option<PathValidator>, path_validator: Option<PathValidator>,
/// Growth system integration (optional) /// Growth system integration (optional)
growth: Option<GrowthIntegration>, growth: Option<GrowthIntegration>,
@@ -38,10 +36,9 @@ pub struct AgentLoop {
compaction_threshold: usize, compaction_threshold: usize,
/// Compaction behavior configuration /// Compaction behavior configuration
compaction_config: CompactionConfig, compaction_config: CompactionConfig,
/// Optional middleware chain — when `Some`, cross-cutting logic is /// Middleware chain — cross-cutting concerns are delegated to the chain.
/// delegated to the chain instead of the inline code below. /// An empty chain (Default) is a no-op: all `run_*` methods return Continue/Allow.
/// When `None`, the legacy inline path is used (100% backward compatible). middleware_chain: MiddlewareChain,
middleware_chain: Option<MiddlewareChain>,
/// Chat mode: extended thinking enabled /// Chat mode: extended thinking enabled
thinking_enabled: bool, thinking_enabled: bool,
/// Chat mode: reasoning effort level /// Chat mode: reasoning effort level
@@ -62,18 +59,18 @@ impl AgentLoop {
driver, driver,
tools, tools,
memory, memory,
loop_guard: Mutex::new(LoopGuard::default()),
model: String::new(), // Must be set via with_model() model: String::new(), // Must be set via with_model()
system_prompt: None, system_prompt: None,
soul: None, soul: None,
max_tokens: 16384, max_tokens: 16384,
temperature: 0.7, temperature: 0.7,
skill_executor: None, skill_executor: None,
hand_executor: None,
path_validator: None, path_validator: None,
growth: None, growth: None,
compaction_threshold: 0, compaction_threshold: 0,
compaction_config: CompactionConfig::default(), compaction_config: CompactionConfig::default(),
middleware_chain: None, middleware_chain: MiddlewareChain::default(),
thinking_enabled: false, thinking_enabled: false,
reasoning_effort: None, reasoning_effort: None,
plan_mode: false, plan_mode: false,
@@ -86,6 +83,12 @@ impl AgentLoop {
self self
} }
/// Set the hand executor for dispatching Hand tool calls to HandRegistry
pub fn with_hand_executor(mut self, executor: Arc<dyn HandExecutor>) -> Self {
self.hand_executor = Some(executor);
self
}
/// Set the path validator for file system operations /// Set the path validator for file system operations
pub fn with_path_validator(mut self, validator: PathValidator) -> Self { pub fn with_path_validator(mut self, validator: PathValidator) -> Self {
self.path_validator = Some(validator); self.path_validator = Some(validator);
@@ -167,11 +170,10 @@ impl AgentLoop {
self self
} }
/// Inject a middleware chain. When set, cross-cutting concerns (compaction, /// Inject a middleware chain. Cross-cutting concerns (compaction,
/// loop guard, token calibration, etc.) are delegated to the chain instead /// loop guard, token calibration, etc.) are delegated to the chain.
/// of the inline logic.
pub fn with_middleware_chain(mut self, chain: MiddlewareChain) -> Self { pub fn with_middleware_chain(mut self, chain: MiddlewareChain) -> Self {
self.middleware_chain = Some(chain); self.middleware_chain = chain;
self self
} }
@@ -205,6 +207,7 @@ impl AgentLoop {
working_directory: working_dir, working_directory: working_dir,
session_id: Some(session_id.to_string()), session_id: Some(session_id.to_string()),
skill_executor: self.skill_executor.clone(), skill_executor: self.skill_executor.clone(),
hand_executor: self.hand_executor.clone(),
path_validator: Some(path_validator), path_validator: Some(path_validator),
event_sender: None, event_sender: None,
} }
@@ -227,49 +230,19 @@ impl AgentLoop {
// Get all messages for context // Get all messages for context
let mut messages = self.memory.get_messages(&session_id).await?; let mut messages = self.memory.get_messages(&session_id).await?;
let use_middleware = self.middleware_chain.is_some(); // Enhance system prompt via PromptBuilder (middleware may further modify)
let prompt_ctx = PromptContext {
// Apply compaction — skip inline path when middleware chain handles it base_prompt: self.system_prompt.clone(),
if !use_middleware && self.compaction_threshold > 0 { soul: self.soul.clone(),
let needs_async = thinking_enabled: self.thinking_enabled,
self.compaction_config.use_llm || self.compaction_config.memory_flush_enabled; plan_mode: self.plan_mode,
if needs_async { tool_definitions: self.tools.definitions(),
let outcome = compaction::maybe_compact_with_config( agent_name: None,
messages,
self.compaction_threshold,
&self.compaction_config,
&self.agent_id,
&session_id,
Some(&self.driver),
self.growth.as_ref(),
)
.await;
messages = outcome.messages;
} else {
messages = compaction::maybe_compact(messages, self.compaction_threshold);
}
}
// Enhance system prompt — skip when middleware chain handles it
let mut enhanced_prompt = if use_middleware {
let prompt_ctx = PromptContext {
base_prompt: self.system_prompt.clone(),
soul: self.soul.clone(),
thinking_enabled: self.thinking_enabled,
plan_mode: self.plan_mode,
tool_definitions: self.tools.definitions(),
agent_name: None,
};
PromptBuilder::new().build(&prompt_ctx)
} else if let Some(ref growth) = self.growth {
let base = self.system_prompt.as_deref().unwrap_or("");
growth.enhance_prompt(&self.agent_id, base, &input).await?
} else {
self.system_prompt.clone().unwrap_or_default()
}; };
let mut enhanced_prompt = PromptBuilder::new().build(&prompt_ctx);
// Run middleware before_completion hooks (compaction, memory inject, etc.) // Run middleware before_completion hooks (compaction, memory inject, etc.)
if let Some(ref chain) = self.middleware_chain { {
let mut mw_ctx = middleware::MiddlewareContext { let mut mw_ctx = middleware::MiddlewareContext {
agent_id: self.agent_id.clone(), agent_id: self.agent_id.clone(),
session_id: session_id.clone(), session_id: session_id.clone(),
@@ -280,7 +253,7 @@ impl AgentLoop {
input_tokens: 0, input_tokens: 0,
output_tokens: 0, output_tokens: 0,
}; };
match chain.run_before_completion(&mut mw_ctx).await? { match self.middleware_chain.run_before_completion(&mut mw_ctx).await? {
middleware::MiddlewareDecision::Continue => { middleware::MiddlewareDecision::Continue => {
messages = mw_ctx.messages; messages = mw_ctx.messages;
enhanced_prompt = mw_ctx.system_prompt; enhanced_prompt = mw_ctx.system_prompt;
@@ -400,7 +373,6 @@ impl AgentLoop {
// Create tool context and execute all tools // Create tool context and execute all tools
let tool_context = self.create_tool_context(session_id.clone()); let tool_context = self.create_tool_context(session_id.clone());
let mut circuit_breaker_triggered = false;
let mut abort_result: Option<AgentLoopResult> = None; let mut abort_result: Option<AgentLoopResult> = None;
let mut clarification_result: Option<AgentLoopResult> = None; let mut clarification_result: Option<AgentLoopResult> = None;
for (id, name, input) in tool_calls { for (id, name, input) in tool_calls {
@@ -408,8 +380,8 @@ impl AgentLoop {
if abort_result.is_some() { if abort_result.is_some() {
break; break;
} }
// Check tool call safety — via middleware chain or inline loop guard // Check tool call safety — via middleware chain
if let Some(ref chain) = self.middleware_chain { {
let mw_ctx_ref = middleware::MiddlewareContext { let mw_ctx_ref = middleware::MiddlewareContext {
agent_id: self.agent_id.clone(), agent_id: self.agent_id.clone(),
session_id: session_id.clone(), session_id: session_id.clone(),
@@ -420,7 +392,7 @@ impl AgentLoop {
input_tokens: total_input_tokens, input_tokens: total_input_tokens,
output_tokens: total_output_tokens, output_tokens: total_output_tokens,
}; };
match chain.run_before_tool_call(&mw_ctx_ref, &name, &input).await? { match self.middleware_chain.run_before_tool_call(&mw_ctx_ref, &name, &input).await? {
middleware::ToolCallDecision::Allow => {} middleware::ToolCallDecision::Allow => {}
middleware::ToolCallDecision::Block(msg) => { middleware::ToolCallDecision::Block(msg) => {
tracing::warn!("[AgentLoop] Tool '{}' blocked by middleware: {}", name, msg); tracing::warn!("[AgentLoop] Tool '{}' blocked by middleware: {}", name, msg);
@@ -456,26 +428,6 @@ impl AgentLoop {
}); });
} }
} }
} else {
// Legacy inline path
let guard_result = self.loop_guard.lock().unwrap_or_else(|e| e.into_inner()).check(&name, &input);
match guard_result {
LoopGuardResult::CircuitBreaker => {
tracing::warn!("[AgentLoop] Circuit breaker triggered by tool '{}'", name);
circuit_breaker_triggered = true;
break;
}
LoopGuardResult::Blocked => {
tracing::warn!("[AgentLoop] Tool '{}' blocked by loop guard", name);
let error_output = serde_json::json!({ "error": "工具调用被循环防护拦截" });
messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), error_output, true));
continue;
}
LoopGuardResult::Warn => {
tracing::warn!("[AgentLoop] Tool '{}' triggered loop guard warning", name);
}
LoopGuardResult::Allowed => {}
}
} }
let tool_result = match tokio::time::timeout( let tool_result = match tokio::time::timeout(
@@ -537,21 +489,10 @@ impl AgentLoop {
break result; break result;
} }
// If circuit breaker was triggered, terminate immediately
if circuit_breaker_triggered {
let msg = "检测到工具调用循环,已自动终止";
self.memory.append_message(&session_id, &Message::assistant(msg)).await?;
break AgentLoopResult {
response: msg.to_string(),
input_tokens: total_input_tokens,
output_tokens: total_output_tokens,
iterations,
};
}
}; };
// Post-completion processing — middleware chain or inline growth // Post-completion processing — middleware chain
if let Some(ref chain) = self.middleware_chain { {
let mw_ctx = middleware::MiddlewareContext { let mw_ctx = middleware::MiddlewareContext {
agent_id: self.agent_id.clone(), agent_id: self.agent_id.clone(),
session_id: session_id.clone(), session_id: session_id.clone(),
@@ -562,16 +503,9 @@ impl AgentLoop {
input_tokens: total_input_tokens, input_tokens: total_input_tokens,
output_tokens: total_output_tokens, output_tokens: total_output_tokens,
}; };
if let Err(e) = chain.run_after_completion(&mw_ctx).await { if let Err(e) = self.middleware_chain.run_after_completion(&mw_ctx).await {
tracing::warn!("[AgentLoop] Middleware after_completion failed: {}", e); tracing::warn!("[AgentLoop] Middleware after_completion failed: {}", e);
} }
} else if let Some(ref growth) = self.growth {
// Legacy inline path
if let Ok(all_messages) = self.memory.get_messages(&session_id).await {
if let Err(e) = growth.process_conversation(&self.agent_id, &all_messages, session_id.clone()).await {
tracing::warn!("[AgentLoop] Growth processing failed: {}", e);
}
}
} }
Ok(result) Ok(result)
@@ -593,49 +527,19 @@ impl AgentLoop {
// Get all messages for context // Get all messages for context
let mut messages = self.memory.get_messages(&session_id).await?; let mut messages = self.memory.get_messages(&session_id).await?;
let use_middleware = self.middleware_chain.is_some(); // Enhance system prompt via PromptBuilder (middleware may further modify)
let prompt_ctx = PromptContext {
// Apply compaction — skip inline path when middleware chain handles it base_prompt: self.system_prompt.clone(),
if !use_middleware && self.compaction_threshold > 0 { soul: self.soul.clone(),
let needs_async = thinking_enabled: self.thinking_enabled,
self.compaction_config.use_llm || self.compaction_config.memory_flush_enabled; plan_mode: self.plan_mode,
if needs_async { tool_definitions: self.tools.definitions(),
let outcome = compaction::maybe_compact_with_config( agent_name: None,
messages,
self.compaction_threshold,
&self.compaction_config,
&self.agent_id,
&session_id,
Some(&self.driver),
self.growth.as_ref(),
)
.await;
messages = outcome.messages;
} else {
messages = compaction::maybe_compact(messages, self.compaction_threshold);
}
}
// Enhance system prompt — skip when middleware chain handles it
let mut enhanced_prompt = if use_middleware {
let prompt_ctx = PromptContext {
base_prompt: self.system_prompt.clone(),
soul: self.soul.clone(),
thinking_enabled: self.thinking_enabled,
plan_mode: self.plan_mode,
tool_definitions: self.tools.definitions(),
agent_name: None,
};
PromptBuilder::new().build(&prompt_ctx)
} else if let Some(ref growth) = self.growth {
let base = self.system_prompt.as_deref().unwrap_or("");
growth.enhance_prompt(&self.agent_id, base, &input).await?
} else {
self.system_prompt.clone().unwrap_or_default()
}; };
let mut enhanced_prompt = PromptBuilder::new().build(&prompt_ctx);
// Run middleware before_completion hooks (compaction, memory inject, etc.) // Run middleware before_completion hooks (compaction, memory inject, etc.)
if let Some(ref chain) = self.middleware_chain { {
let mut mw_ctx = middleware::MiddlewareContext { let mut mw_ctx = middleware::MiddlewareContext {
agent_id: self.agent_id.clone(), agent_id: self.agent_id.clone(),
session_id: session_id.clone(), session_id: session_id.clone(),
@@ -646,18 +550,20 @@ impl AgentLoop {
input_tokens: 0, input_tokens: 0,
output_tokens: 0, output_tokens: 0,
}; };
match chain.run_before_completion(&mut mw_ctx).await? { match self.middleware_chain.run_before_completion(&mut mw_ctx).await? {
middleware::MiddlewareDecision::Continue => { middleware::MiddlewareDecision::Continue => {
messages = mw_ctx.messages; messages = mw_ctx.messages;
enhanced_prompt = mw_ctx.system_prompt; enhanced_prompt = mw_ctx.system_prompt;
} }
middleware::MiddlewareDecision::Stop(reason) => { middleware::MiddlewareDecision::Stop(reason) => {
let _ = tx.send(LoopEvent::Complete(AgentLoopResult { if let Err(e) = tx.send(LoopEvent::Complete(AgentLoopResult {
response: reason, response: reason,
input_tokens: 0, input_tokens: 0,
output_tokens: 0, output_tokens: 0,
iterations: 1, iterations: 1,
})).await; })).await {
tracing::warn!("[AgentLoop] Failed to send Complete event: {}", e);
}
return Ok(rx); return Ok(rx);
} }
} }
@@ -668,9 +574,9 @@ impl AgentLoop {
let memory = self.memory.clone(); let memory = self.memory.clone();
let driver = self.driver.clone(); let driver = self.driver.clone();
let tools = self.tools.clone(); let tools = self.tools.clone();
let loop_guard_clone = self.loop_guard.lock().unwrap_or_else(|e| e.into_inner()).clone();
let middleware_chain = self.middleware_chain.clone(); let middleware_chain = self.middleware_chain.clone();
let skill_executor = self.skill_executor.clone(); let skill_executor = self.skill_executor.clone();
let hand_executor = self.hand_executor.clone();
let path_validator = self.path_validator.clone(); let path_validator = self.path_validator.clone();
let agent_id = self.agent_id.clone(); let agent_id = self.agent_id.clone();
let model = self.model.clone(); let model = self.model.clone();
@@ -682,7 +588,6 @@ impl AgentLoop {
tokio::spawn(async move { tokio::spawn(async move {
let mut messages = messages; let mut messages = messages;
let loop_guard_clone = Mutex::new(loop_guard_clone);
let max_iterations = 10; let max_iterations = 10;
let mut iteration = 0; let mut iteration = 0;
let mut total_input_tokens = 0u32; let mut total_input_tokens = 0u32;
@@ -691,15 +596,19 @@ impl AgentLoop {
'outer: loop { 'outer: loop {
iteration += 1; iteration += 1;
if iteration > max_iterations { if iteration > max_iterations {
let _ = tx.send(LoopEvent::Error("达到最大迭代次数".to_string())).await; if let Err(e) = tx.send(LoopEvent::Error("达到最大迭代次数".to_string())).await {
tracing::warn!("[AgentLoop] Failed to send Error event: {}", e);
}
break; break;
} }
// Notify iteration start // Notify iteration start
let _ = tx.send(LoopEvent::IterationStart { if let Err(e) = tx.send(LoopEvent::IterationStart {
iteration, iteration,
max_iterations, max_iterations,
}).await; }).await {
tracing::warn!("[AgentLoop] Failed to send IterationStart event: {}", e);
}
// Build completion request // Build completion request
let request = CompletionRequest { let request = CompletionRequest {
@@ -742,13 +651,17 @@ impl AgentLoop {
text_delta_count += 1; text_delta_count += 1;
tracing::debug!("[AgentLoop] TextDelta #{}: {} chars", text_delta_count, delta.len()); tracing::debug!("[AgentLoop] TextDelta #{}: {} chars", text_delta_count, delta.len());
iteration_text.push_str(delta); iteration_text.push_str(delta);
let _ = tx.send(LoopEvent::Delta(delta.clone())).await; if let Err(e) = tx.send(LoopEvent::Delta(delta.clone())).await {
tracing::warn!("[AgentLoop] Failed to send Delta event: {}", e);
}
} }
StreamChunk::ThinkingDelta { delta } => { StreamChunk::ThinkingDelta { delta } => {
thinking_delta_count += 1; thinking_delta_count += 1;
tracing::debug!("[AgentLoop] ThinkingDelta #{}: {} chars", thinking_delta_count, delta.len()); tracing::debug!("[AgentLoop] ThinkingDelta #{}: {} chars", thinking_delta_count, delta.len());
reasoning_text.push_str(delta); reasoning_text.push_str(delta);
let _ = tx.send(LoopEvent::ThinkingDelta(delta.clone())).await; if let Err(e) = tx.send(LoopEvent::ThinkingDelta(delta.clone())).await {
tracing::warn!("[AgentLoop] Failed to send ThinkingDelta event: {}", e);
}
} }
StreamChunk::ToolUseStart { id, name } => { StreamChunk::ToolUseStart { id, name } => {
tracing::debug!("[AgentLoop] ToolUseStart: id={}, name={}", id, name); tracing::debug!("[AgentLoop] ToolUseStart: id={}, name={}", id, name);
@@ -770,7 +683,9 @@ impl AgentLoop {
// Update with final parsed input and emit ToolStart event // Update with final parsed input and emit ToolStart event
if let Some(tool) = pending_tool_calls.iter_mut().find(|(tid, _, _)| tid == id) { if let Some(tool) = pending_tool_calls.iter_mut().find(|(tid, _, _)| tid == id) {
tool.2 = input.clone(); tool.2 = input.clone();
let _ = tx.send(LoopEvent::ToolStart { name: tool.1.clone(), input: input.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolStart { name: tool.1.clone(), input: input.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolStart event: {}", e);
}
} }
} }
StreamChunk::Complete { input_tokens: it, output_tokens: ot, .. } => { StreamChunk::Complete { input_tokens: it, output_tokens: ot, .. } => {
@@ -787,20 +702,26 @@ impl AgentLoop {
} }
StreamChunk::Error { message } => { StreamChunk::Error { message } => {
tracing::error!("[AgentLoop] Stream error: {}", message); tracing::error!("[AgentLoop] Stream error: {}", message);
let _ = tx.send(LoopEvent::Error(message.clone())).await; if let Err(e) = tx.send(LoopEvent::Error(message.clone())).await {
tracing::warn!("[AgentLoop] Failed to send Error event: {}", e);
}
stream_errored = true; stream_errored = true;
} }
} }
} }
Ok(Some(Err(e))) => { Ok(Some(Err(e))) => {
tracing::error!("[AgentLoop] Chunk error: {}", e); tracing::error!("[AgentLoop] Chunk error: {}", e);
let _ = tx.send(LoopEvent::Error(format!("LLM 响应错误: {}", e.to_string()))).await; if let Err(e) = tx.send(LoopEvent::Error(format!("LLM 响应错误: {}", e.to_string()))).await {
tracing::warn!("[AgentLoop] Failed to send Error event: {}", e);
}
stream_errored = true; stream_errored = true;
} }
Ok(None) => break, // Stream ended normally Ok(None) => break, // Stream ended normally
Err(_) => { Err(_) => {
tracing::error!("[AgentLoop] Stream chunk timeout ({}s)", chunk_timeout.as_secs()); tracing::error!("[AgentLoop] Stream chunk timeout ({}s)", chunk_timeout.as_secs());
let _ = tx.send(LoopEvent::Error("LLM 响应超时,请重试".to_string())).await; if let Err(e) = tx.send(LoopEvent::Error("LLM 响应超时,请重试".to_string())).await {
tracing::warn!("[AgentLoop] Failed to send Error event: {}", e);
}
stream_errored = true; stream_errored = true;
} }
} }
@@ -820,7 +741,9 @@ impl AgentLoop {
if iteration_text.is_empty() && !reasoning_text.is_empty() { if iteration_text.is_empty() && !reasoning_text.is_empty() {
tracing::info!("[AgentLoop] Model generated {} chars of reasoning but no text — using reasoning as response", tracing::info!("[AgentLoop] Model generated {} chars of reasoning but no text — using reasoning as response",
reasoning_text.len()); reasoning_text.len());
let _ = tx.send(LoopEvent::Delta(reasoning_text.clone())).await; if let Err(e) = tx.send(LoopEvent::Delta(reasoning_text.clone())).await {
tracing::warn!("[AgentLoop] Failed to send Delta event: {}", e);
}
iteration_text = reasoning_text.clone(); iteration_text = reasoning_text.clone();
} else if iteration_text.is_empty() { } else if iteration_text.is_empty() {
tracing::warn!("[AgentLoop] No text content after {} chunks (thinking_delta={})", tracing::warn!("[AgentLoop] No text content after {} chunks (thinking_delta={})",
@@ -838,15 +761,17 @@ impl AgentLoop {
tracing::warn!("[AgentLoop] Failed to save final assistant message: {}", e); tracing::warn!("[AgentLoop] Failed to save final assistant message: {}", e);
} }
let _ = tx.send(LoopEvent::Complete(AgentLoopResult { if let Err(e) = tx.send(LoopEvent::Complete(AgentLoopResult {
response: iteration_text.clone(), response: iteration_text.clone(),
input_tokens: total_input_tokens, input_tokens: total_input_tokens,
output_tokens: total_output_tokens, output_tokens: total_output_tokens,
iterations: iteration, iterations: iteration,
})).await; })).await {
tracing::warn!("[AgentLoop] Failed to send Complete event: {}", e);
}
// Post-completion: middleware after_completion (memory extraction, etc.) // Post-completion: middleware after_completion (memory extraction, etc.)
if let Some(ref chain) = middleware_chain { {
let mw_ctx = middleware::MiddlewareContext { let mw_ctx = middleware::MiddlewareContext {
agent_id: agent_id.clone(), agent_id: agent_id.clone(),
session_id: session_id_clone.clone(), session_id: session_id_clone.clone(),
@@ -857,7 +782,7 @@ impl AgentLoop {
input_tokens: total_input_tokens, input_tokens: total_input_tokens,
output_tokens: total_output_tokens, output_tokens: total_output_tokens,
}; };
if let Err(e) = chain.run_after_completion(&mw_ctx).await { if let Err(e) = middleware_chain.run_after_completion(&mw_ctx).await {
tracing::warn!("[AgentLoop] Streaming middleware after_completion failed: {}", e); tracing::warn!("[AgentLoop] Streaming middleware after_completion failed: {}", e);
} }
} }
@@ -889,8 +814,8 @@ impl AgentLoop {
for (id, name, input) in pending_tool_calls { for (id, name, input) in pending_tool_calls {
tracing::debug!("[AgentLoop] Executing tool: name={}, input={:?}", name, input); tracing::debug!("[AgentLoop] Executing tool: name={}, input={:?}", name, input);
// Check tool call safety — via middleware chain or inline loop guard // Check tool call safety — via middleware chain
if let Some(ref chain) = middleware_chain { {
let mw_ctx = middleware::MiddlewareContext { let mw_ctx = middleware::MiddlewareContext {
agent_id: agent_id.clone(), agent_id: agent_id.clone(),
session_id: session_id_clone.clone(), session_id: session_id_clone.clone(),
@@ -901,18 +826,22 @@ impl AgentLoop {
input_tokens: total_input_tokens, input_tokens: total_input_tokens,
output_tokens: total_output_tokens, output_tokens: total_output_tokens,
}; };
match chain.run_before_tool_call(&mw_ctx, &name, &input).await { match middleware_chain.run_before_tool_call(&mw_ctx, &name, &input).await {
Ok(middleware::ToolCallDecision::Allow) => {} Ok(middleware::ToolCallDecision::Allow) => {}
Ok(middleware::ToolCallDecision::Block(msg)) => { Ok(middleware::ToolCallDecision::Block(msg)) => {
tracing::warn!("[AgentLoop] Tool '{}' blocked by middleware: {}", name, msg); tracing::warn!("[AgentLoop] Tool '{}' blocked by middleware: {}", name, msg);
let error_output = serde_json::json!({ "error": msg }); let error_output = serde_json::json!({ "error": msg });
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), error_output, true)); messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), error_output, true));
continue; continue;
} }
Ok(middleware::ToolCallDecision::AbortLoop(reason)) => { Ok(middleware::ToolCallDecision::AbortLoop(reason)) => {
tracing::warn!("[AgentLoop] Loop aborted by middleware: {}", reason); tracing::warn!("[AgentLoop] Loop aborted by middleware: {}", reason);
let _ = tx.send(LoopEvent::Error(reason)).await; if let Err(e) = tx.send(LoopEvent::Error(reason)).await {
tracing::warn!("[AgentLoop] Failed to send Error event: {}", e);
}
break 'outer; break 'outer;
} }
Ok(middleware::ToolCallDecision::ReplaceInput(new_input)) => { Ok(middleware::ToolCallDecision::ReplaceInput(new_input)) => {
@@ -930,24 +859,31 @@ impl AgentLoop {
working_directory: working_dir, working_directory: working_dir,
session_id: Some(session_id_clone.to_string()), session_id: Some(session_id_clone.to_string()),
skill_executor: skill_executor.clone(), skill_executor: skill_executor.clone(),
hand_executor: hand_executor.clone(),
path_validator: Some(pv), path_validator: Some(pv),
event_sender: Some(tx.clone()), event_sender: Some(tx.clone()),
}; };
let (result, is_error) = if let Some(tool) = tools.get(&name) { let (result, is_error) = if let Some(tool) = tools.get(&name) {
match tool.execute(new_input, &tool_context).await { match tool.execute(new_input, &tool_context).await {
Ok(output) => { Ok(output) => {
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
(output, false) (output, false)
} }
Err(e) => { Err(e) => {
let error_output = serde_json::json!({ "error": e.to_string() }); let error_output = serde_json::json!({ "error": e.to_string() });
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
(error_output, true) (error_output, true)
} }
} }
} else { } else {
let error_output = serde_json::json!({ "error": format!("Unknown tool: {}", name) }); let error_output = serde_json::json!({ "error": format!("Unknown tool: {}", name) });
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
(error_output, true) (error_output, true)
}; };
messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), result, is_error)); messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), result, is_error));
@@ -956,31 +892,13 @@ impl AgentLoop {
Err(e) => { Err(e) => {
tracing::error!("[AgentLoop] Middleware error for tool '{}': {}", name, e); tracing::error!("[AgentLoop] Middleware error for tool '{}': {}", name, e);
let error_output = serde_json::json!({ "error": e.to_string() }); let error_output = serde_json::json!({ "error": e.to_string() });
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), error_output, true)); messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), error_output, true));
continue; continue;
} }
} }
} else {
// Legacy inline loop guard path
let guard_result = loop_guard_clone.lock().unwrap_or_else(|e| e.into_inner()).check(&name, &input);
match guard_result {
LoopGuardResult::CircuitBreaker => {
let _ = tx.send(LoopEvent::Error("检测到工具调用循环,已自动终止".to_string())).await;
break 'outer;
}
LoopGuardResult::Blocked => {
tracing::warn!("[AgentLoop] Tool '{}' blocked by loop guard", name);
let error_output = serde_json::json!({ "error": "工具调用被循环防护拦截" });
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await;
messages.push(Message::tool_result(id, zclaw_types::ToolId::new(&name), error_output, true));
continue;
}
LoopGuardResult::Warn => {
tracing::warn!("[AgentLoop] Tool '{}' triggered loop guard warning", name);
}
LoopGuardResult::Allowed => {}
}
} }
// Use pre-resolved path_validator (already has default fallback from create_tool_context logic) // Use pre-resolved path_validator (already has default fallback from create_tool_context logic)
let pv = path_validator.clone().unwrap_or_else(|| { let pv = path_validator.clone().unwrap_or_else(|| {
@@ -996,6 +914,7 @@ impl AgentLoop {
working_directory: working_dir, working_directory: working_dir,
session_id: Some(session_id_clone.to_string()), session_id: Some(session_id_clone.to_string()),
skill_executor: skill_executor.clone(), skill_executor: skill_executor.clone(),
hand_executor: hand_executor.clone(),
path_validator: Some(pv), path_validator: Some(pv),
event_sender: Some(tx.clone()), event_sender: Some(tx.clone()),
}; };
@@ -1005,20 +924,26 @@ impl AgentLoop {
match tool.execute(input.clone(), &tool_context).await { match tool.execute(input.clone(), &tool_context).await {
Ok(output) => { Ok(output) => {
tracing::debug!("[AgentLoop] Tool '{}' executed successfully: {:?}", name, output); tracing::debug!("[AgentLoop] Tool '{}' executed successfully: {:?}", name, output);
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
(output, false) (output, false)
} }
Err(e) => { Err(e) => {
tracing::error!("[AgentLoop] Tool '{}' execution failed: {}", name, e); tracing::error!("[AgentLoop] Tool '{}' execution failed: {}", name, e);
let error_output = serde_json::json!({ "error": e.to_string() }); let error_output = serde_json::json!({ "error": e.to_string() });
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
(error_output, true) (error_output, true)
} }
} }
} else { } else {
tracing::error!("[AgentLoop] Tool '{}' not found in registry", name); tracing::error!("[AgentLoop] Tool '{}' not found in registry", name);
let error_output = serde_json::json!({ "error": format!("Unknown tool: {}", name) }); let error_output = serde_json::json!({ "error": format!("Unknown tool: {}", name) });
let _ = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await; if let Err(e) = tx.send(LoopEvent::ToolEnd { name: name.clone(), output: error_output.clone() }).await {
tracing::warn!("[AgentLoop] Failed to send ToolEnd event: {}", e);
}
(error_output, true) (error_output, true)
}; };
@@ -1038,13 +963,17 @@ impl AgentLoop {
is_error, is_error,
)); ));
// Send the question as final delta so the user sees it // Send the question as final delta so the user sees it
let _ = tx.send(LoopEvent::Delta(question.clone())).await; if let Err(e) = tx.send(LoopEvent::Delta(question.clone())).await {
let _ = tx.send(LoopEvent::Complete(AgentLoopResult { tracing::warn!("[AgentLoop] Failed to send Delta event: {}", e);
}
if let Err(e) = tx.send(LoopEvent::Complete(AgentLoopResult {
response: question.clone(), response: question.clone(),
input_tokens: total_input_tokens, input_tokens: total_input_tokens,
output_tokens: total_output_tokens, output_tokens: total_output_tokens,
iterations: iteration, iterations: iteration,
})).await; })).await {
tracing::warn!("[AgentLoop] Failed to send Complete event: {}", e);
}
if let Err(e) = memory.append_message(&session_id_clone, &Message::assistant(&question)).await { if let Err(e) = memory.append_message(&session_id_clone, &Message::assistant(&question)).await {
tracing::warn!("[AgentLoop] Failed to save clarification message: {}", e); tracing::warn!("[AgentLoop] Failed to save clarification message: {}", e);
} }

View File

@@ -279,3 +279,4 @@ pub mod token_calibration;
pub mod tool_error; pub mod tool_error;
pub mod tool_output_guard; pub mod tool_output_guard;
pub mod trajectory_recorder; pub mod trajectory_recorder;
pub mod evolution;

View File

@@ -4,8 +4,14 @@
//! to classify intent, and injects routing context into the system prompt. //! to classify intent, and injects routing context into the system prompt.
//! //!
//! Priority: 80 (runs before data_masking at 90, so it sees raw user input). //! Priority: 80 (runs before data_masking at 90, so it sees raw user input).
//!
//! Supports two modes:
//! 1. **Static mode** (default): Uses built-in `KeywordClassifier` with 4 healthcare domains.
//! 2. **Dynamic mode**: Industry keywords loaded from SaaS via `update_industry_keywords()`.
use async_trait::async_trait; use async_trait::async_trait;
use std::sync::Arc;
use tokio::sync::RwLock;
use zclaw_types::Result; use zclaw_types::Result;
use crate::middleware::{AgentMiddleware, MiddlewareContext, MiddlewareDecision}; use crate::middleware::{AgentMiddleware, MiddlewareContext, MiddlewareDecision};
@@ -21,6 +27,19 @@ pub struct ButlerRouterMiddleware {
/// Optional full semantic router (when zclaw-skills is available). /// Optional full semantic router (when zclaw-skills is available).
/// If None, falls back to keyword-based classification. /// If None, falls back to keyword-based classification.
_router: Option<Box<dyn ButlerRouterBackend>>, _router: Option<Box<dyn ButlerRouterBackend>>,
/// Dynamic industry keywords (loaded from SaaS industry config).
/// If empty, falls back to static KeywordClassifier.
industry_keywords: Arc<RwLock<Vec<IndustryKeywordConfig>>>,
}
/// A single industry's keyword configuration for routing.
#[derive(Debug, Clone)]
pub struct IndustryKeywordConfig {
pub id: String,
pub name: String,
pub keywords: Vec<String>,
pub system_prompt: String,
} }
/// Backend trait for routing implementations. /// Backend trait for routing implementations.
@@ -38,6 +57,8 @@ pub struct RoutingHint {
pub category: String, pub category: String,
pub confidence: f32, pub confidence: f32,
pub skill_id: Option<String>, pub skill_id: Option<String>,
/// Optional domain-specific system prompt to inject.
pub domain_prompt: Option<String>,
} }
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
@@ -81,13 +102,13 @@ impl KeywordClassifier {
]); ]);
let domains = [ let domains = [
("healthcare", healthcare_score), ("healthcare", healthcare_score, Some("用户可能在询问医院行政管理相关的问题。请注意使用医疗行业术语,回答要专业准确。")),
("data_report", data_score), ("data_report", data_score, Some("用户可能在请求数据统计或报表相关的工作。请优先提供结构化的数据和建议。")),
("policy_compliance", policy_score), ("policy_compliance", policy_score, Some("用户可能在咨询政策法规或合规要求。请引用具体政策文件并给出明确的合规建议。")),
("meeting_coordination", meeting_score), ("meeting_coordination", meeting_score, Some("用户可能在处理会议协调或行政事务。请提供简洁的待办清单或行动方案。")),
]; ];
let (best_domain, best_score) = domains let (best_domain, best_score, best_prompt) = domains
.into_iter() .into_iter()
.max_by(|a, b| a.1.partial_cmp(&b.1).unwrap_or(std::cmp::Ordering::Equal))?; .max_by(|a, b| a.1.partial_cmp(&b.1).unwrap_or(std::cmp::Ordering::Equal))?;
@@ -99,6 +120,7 @@ impl KeywordClassifier {
category: best_domain.to_string(), category: best_domain.to_string(),
confidence: best_score, confidence: best_score,
skill_id: None, skill_id: None,
domain_prompt: best_prompt.map(|s| s.to_string()),
}) })
} }
@@ -108,9 +130,40 @@ impl KeywordClassifier {
if hits == 0 { if hits == 0 {
return 0.0; return 0.0;
} }
// Normalize: more hits = higher score, capped at 1.0 // Normalize: 3 keyword hits → score 1.0 (saturated). Threshold 0.2 ≈ 0.6 hits.
(hits as f32 / 3.0).min(1.0) (hits as f32 / 3.0).min(1.0)
} }
/// Classify against dynamic industry keyword configs.
///
/// Tie-breaking: when two industries score equally, the *first* entry wins
/// (keeps existing best on `<=`). Industries should be ordered by priority
/// in the config array if specific tie-breaking is desired.
fn classify_with_industries(query: &str, industries: &[IndustryKeywordConfig]) -> Option<RoutingHint> {
let lower = query.to_lowercase();
let mut best: Option<(String, f32, String)> = None;
for industry in industries {
let keywords: Vec<&str> = industry.keywords.iter().map(|s| s.as_str()).collect();
let score = Self::score_domain(&lower, &keywords);
if score < 0.2 {
continue;
}
match &best {
Some((_, best_score, _)) if score <= *best_score => {}
_ => {
best = Some((industry.id.clone(), score, industry.system_prompt.clone()));
}
}
}
best.map(|(id, score, prompt)| RoutingHint {
category: id,
confidence: score,
skill_id: None,
domain_prompt: if prompt.is_empty() { None } else { Some(prompt) },
})
}
} }
#[async_trait] #[async_trait]
@@ -127,7 +180,10 @@ impl ButlerRouterBackend for KeywordClassifier {
impl ButlerRouterMiddleware { impl ButlerRouterMiddleware {
/// Create a new butler router with keyword-based classification only. /// Create a new butler router with keyword-based classification only.
pub fn new() -> Self { pub fn new() -> Self {
Self { _router: None } Self {
_router: None,
industry_keywords: Arc::new(RwLock::new(Vec::new())),
}
} }
/// Create a butler router with a custom semantic routing backend. /// Create a butler router with a custom semantic routing backend.
@@ -135,38 +191,75 @@ impl ButlerRouterMiddleware {
/// The kernel layer uses this to inject `SemanticSkillRouter` from `zclaw-skills`, /// The kernel layer uses this to inject `SemanticSkillRouter` from `zclaw-skills`,
/// enabling TF-IDF + embedding-based intent classification across all 75 skills. /// enabling TF-IDF + embedding-based intent classification across all 75 skills.
pub fn with_router(router: Box<dyn ButlerRouterBackend>) -> Self { pub fn with_router(router: Box<dyn ButlerRouterBackend>) -> Self {
Self { _router: Some(router) } Self {
_router: Some(router),
industry_keywords: Arc::new(RwLock::new(Vec::new())),
}
}
/// Create a butler router with a custom semantic routing backend AND
/// a shared industry keywords Arc.
///
/// The shared Arc allows the Tauri command layer to update industry keywords
/// through the Kernel's `industry_keywords()` field, which the middleware
/// reads automatically — no chain rebuild needed.
pub fn with_router_and_shared_keywords(
router: Box<dyn ButlerRouterBackend>,
shared_keywords: Arc<RwLock<Vec<IndustryKeywordConfig>>>,
) -> Self {
Self {
_router: Some(router),
industry_keywords: shared_keywords,
}
}
/// Update dynamic industry keyword configs (called from Tauri command or SaaS sync).
pub async fn update_industry_keywords(&self, configs: Vec<IndustryKeywordConfig>) {
let mut guard = self.industry_keywords.write().await;
tracing::info!("ButlerRouter: updating industry keywords ({} industries)", configs.len());
*guard = configs;
} }
/// Domain context to inject into system prompt based on routing hint. /// Domain context to inject into system prompt based on routing hint.
///
/// Uses structured `<butler-context>` XML fencing (Hermes-inspired) for
/// reliable prompt cache preservation across turns.
fn build_context_injection(hint: &RoutingHint) -> String { fn build_context_injection(hint: &RoutingHint) -> String {
let domain_context = match hint.category.as_str() { // Semantic skill routing
"healthcare" => "用户可能在询问医院行政管理相关的问题。请注意使用医疗行业术语,回答要专业准确。", if hint.category == "semantic_skill" {
"data_report" => "用户可能在请求数据统计或报表相关的工作。请优先提供结构化的数据和建议。", if let Some(ref skill_id) = hint.skill_id {
"policy_compliance" => "用户可能在咨询政策法规或合规要求。请引用具体政策文件并给出明确的合规建议。", return format!(
"meeting_coordination" => "用户可能在处理会议协调或行政事务。请提供简洁的待办清单或行动方案。", "\n\n<butler-context>\n<routing>匹配技能: {} (置信度: {:.0}%)</routing>\n<system-note>系统检测到用户的意图与已注册技能高度相关,请在回答中充分利用该技能的能力。</system-note>\n</butler-context>",
"semantic_skill" => { xml_escape(skill_id),
// Semantic routing matched a specific skill hint.confidence * 100.0
if let Some(ref skill_id) = hint.skill_id { );
return format!(
"\n\n[语义路由] 匹配技能: {} (置信度: {:.0}%)\n系统检测到用户的意图与已注册技能高度相关,请在回答中充分利用该技能的能力。",
skill_id,
hint.confidence * 100.0
);
}
return String::new();
} }
_ => return String::new(), return String::new();
}; }
// Use domain_prompt if available (dynamic industry or static with prompt)
let domain_context = hint.domain_prompt.as_deref().unwrap_or_else(|| {
match hint.category.as_str() {
"healthcare" => "用户可能在询问医院行政管理相关的问题。",
"data_report" => "用户可能在请求数据统计或报表相关的工作。",
"policy_compliance" => "用户可能在咨询政策法规或合规要求。",
"meeting_coordination" => "用户可能在处理会议协调或行政事务。",
_ => "",
}
});
if domain_context.is_empty() {
return String::new();
}
let skill_info = hint.skill_id.as_ref().map_or(String::new(), |id| { let skill_info = hint.skill_id.as_ref().map_or(String::new(), |id| {
format!("\n关联技能: {}", id) format!("\n<skill>{}</skill>", xml_escape(id))
}); });
format!( format!(
"\n\n[路由上下文] (置信度: {:.0}%)\n{}{}", "\n\n<butler-context>\n<routing confidence=\"{:.0}%\">{}</routing>{}<system-note>以上是管家系统对您当前意图的分析。在对话中自然运用这些信息,主动提供有帮助的建议。</system-note>\n</butler-context>",
hint.confidence * 100.0, hint.confidence * 100.0,
domain_context, xml_escape(domain_context),
skill_info skill_info
) )
} }
@@ -178,6 +271,15 @@ impl Default for ButlerRouterMiddleware {
} }
} }
/// Escape XML special characters in user/admin-provided content to prevent
/// breaking the `<butler-context>` XML structure.
fn xml_escape(s: &str) -> String {
s.replace('&', "&amp;")
.replace('<', "&lt;")
.replace('>', "&gt;")
.replace('"', "&quot;")
}
#[async_trait] #[async_trait]
impl AgentMiddleware for ButlerRouterMiddleware { impl AgentMiddleware for ButlerRouterMiddleware {
fn name(&self) -> &str { fn name(&self) -> &str {
@@ -195,10 +297,25 @@ impl AgentMiddleware for ButlerRouterMiddleware {
return Ok(MiddlewareDecision::Continue); return Ok(MiddlewareDecision::Continue);
} }
let hint = if let Some(ref router) = self._router { // Try dynamic industry keywords first
router.classify(user_input).await let industries = self.industry_keywords.read().await;
let hint = if !industries.is_empty() {
KeywordClassifier::classify_with_industries(user_input, &industries)
} else { } else {
KeywordClassifier.classify(user_input).await None
};
drop(industries);
// Fall back to static or custom router
let hint = match hint {
Some(h) => Some(h),
None => {
if let Some(ref router) = self._router {
router.classify(user_input).await
} else {
KeywordClassifier.classify(user_input).await
}
}
}; };
if let Some(hint) = hint { if let Some(hint) = hint {
@@ -260,7 +377,6 @@ mod tests {
#[test] #[test]
fn test_no_match_returns_none() { fn test_no_match_returns_none() {
let result = KeywordClassifier::classify_query("今天天气怎么样?"); let result = KeywordClassifier::classify_query("今天天气怎么样?");
// "天气" doesn't match any domain strongly enough
assert!(result.is_none() || result.unwrap().confidence < 0.3); assert!(result.is_none() || result.unwrap().confidence < 0.3);
} }
@@ -270,13 +386,71 @@ mod tests {
category: "healthcare".to_string(), category: "healthcare".to_string(),
confidence: 0.8, confidence: 0.8,
skill_id: None, skill_id: None,
domain_prompt: None,
}; };
let injection = ButlerRouterMiddleware::build_context_injection(&hint); let injection = ButlerRouterMiddleware::build_context_injection(&hint);
assert!(injection.contains("路由上下文")); assert!(injection.contains("butler-context"));
assert!(injection.contains("医院行政")); assert!(injection.contains("医院"));
assert!(injection.contains("80%")); assert!(injection.contains("80%"));
} }
#[test]
fn test_dynamic_industry_classification() {
let industries = vec![
IndustryKeywordConfig {
id: "ecommerce".to_string(),
name: "电商零售".to_string(),
keywords: vec![
"库存".to_string(), "促销".to_string(), "SKU".to_string(),
"GMV".to_string(), "转化率".to_string(),
],
system_prompt: "电商行业上下文".to_string(),
},
IndustryKeywordConfig {
id: "garment".to_string(),
name: "制衣制造".to_string(),
keywords: vec![
"面料".to_string(), "打版".to_string(), "裁床".to_string(),
"缝纫".to_string(), "供应链".to_string(),
],
system_prompt: "制衣行业上下文".to_string(),
},
];
// Ecommerce match
let hint = KeywordClassifier::classify_with_industries(
"帮我查一下这个SKU的库存和促销活动",
&industries,
).unwrap();
assert_eq!(hint.category, "ecommerce");
assert!(hint.domain_prompt.is_some());
// Garment match
let hint = KeywordClassifier::classify_with_industries(
"这批面料的打版什么时候完成?裁床排期如何?",
&industries,
).unwrap();
assert_eq!(hint.category, "garment");
}
#[test]
fn test_dynamic_industry_no_match() {
let industries = vec![
IndustryKeywordConfig {
id: "ecommerce".to_string(),
name: "电商零售".to_string(),
keywords: vec!["库存".to_string(), "促销".to_string()],
system_prompt: "电商行业上下文".to_string(),
},
];
let result = KeywordClassifier::classify_with_industries(
"今天天气怎么样?",
&industries,
);
assert!(result.is_none());
}
#[tokio::test] #[tokio::test]
async fn test_middleware_injects_context() { async fn test_middleware_injects_context() {
let mw = ButlerRouterMiddleware::new(); let mw = ButlerRouterMiddleware::new();
@@ -293,10 +467,39 @@ mod tests {
let decision = mw.before_completion(&mut ctx).await.unwrap(); let decision = mw.before_completion(&mut ctx).await.unwrap();
assert!(matches!(decision, MiddlewareDecision::Continue)); assert!(matches!(decision, MiddlewareDecision::Continue));
assert!(ctx.system_prompt.contains("路由上下文")); assert!(ctx.system_prompt.contains("butler-context"));
assert!(ctx.system_prompt.contains("医院")); assert!(ctx.system_prompt.contains("医院"));
} }
#[tokio::test]
async fn test_middleware_with_dynamic_industries() {
let mw = ButlerRouterMiddleware::new();
mw.update_industry_keywords(vec![
IndustryKeywordConfig {
id: "ecommerce".to_string(),
name: "电商零售".to_string(),
keywords: vec!["库存".to_string(), "GMV".to_string(), "转化率".to_string()],
system_prompt: "您是电商运营管家。".to_string(),
},
]).await;
let mut ctx = MiddlewareContext {
agent_id: test_agent_id(),
session_id: test_session_id(),
user_input: "帮我查一下库存和GMV数据".to_string(),
system_prompt: "You are a helpful assistant.".to_string(),
messages: vec![],
response_content: vec![],
input_tokens: 0,
output_tokens: 0,
};
let decision = mw.before_completion(&mut ctx).await.unwrap();
assert!(matches!(decision, MiddlewareDecision::Continue));
assert!(ctx.system_prompt.contains("butler-context"));
assert!(ctx.system_prompt.contains("电商运营管家"));
}
#[tokio::test] #[tokio::test]
async fn test_middleware_skips_empty_input() { async fn test_middleware_skips_empty_input() {
let mw = ButlerRouterMiddleware::new(); let mw = ButlerRouterMiddleware::new();
@@ -318,9 +521,7 @@ mod tests {
#[test] #[test]
fn test_mixed_domain_picks_best() { fn test_mixed_domain_picks_best() {
// "医保报表" touches both healthcare and data_report
let hint = KeywordClassifier::classify_query("帮我做一份医保费用的月度报表").unwrap(); let hint = KeywordClassifier::classify_query("帮我做一份医保费用的月度报表").unwrap();
// Should pick the domain with highest score
assert!(!hint.category.is_empty()); assert!(!hint.category.is_empty());
assert!(hint.confidence > 0.3); assert!(hint.confidence > 0.3);
} }

View File

@@ -20,19 +20,19 @@ use super::{AgentMiddleware, MiddlewareContext, MiddlewareDecision};
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
static RE_COMPANY: LazyLock<Regex> = LazyLock::new(|| { static RE_COMPANY: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(r"[^\s]{1,20}(?:公司|厂|集团|工作室|商行|有限|股份)").unwrap() Regex::new(r"[^\s]{1,20}(?:公司|厂|集团|工作室|商行|有限|股份)").expect("static regex is valid")
}); });
static RE_MONEY: LazyLock<Regex> = LazyLock::new(|| { static RE_MONEY: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(r"[¥¥$]\s*[\d,.]+[万亿]?元?|[\d,.]+[万亿]元").unwrap() Regex::new(r"[¥¥$]\s*[\d,.]+[万亿]?元?|[\d,.]+[万亿]元").expect("static regex is valid")
}); });
static RE_PHONE: LazyLock<Regex> = LazyLock::new(|| { static RE_PHONE: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(r"1[3-9]\d-?\d{4}-?\d{4}").unwrap() Regex::new(r"1[3-9]\d-?\d{4}-?\d{4}").expect("static regex is valid")
}); });
static RE_EMAIL: LazyLock<Regex> = LazyLock::new(|| { static RE_EMAIL: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}").unwrap() Regex::new(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}").expect("static regex is valid")
}); });
static RE_ID_CARD: LazyLock<Regex> = LazyLock::new(|| { static RE_ID_CARD: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(r"\b\d{17}[\dXx]\b").unwrap() Regex::new(r"\b\d{17}[\dXx]\b").expect("static regex is valid")
}); });
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
@@ -130,7 +130,7 @@ impl DataMasker {
fn recover_read<T>(lock: &RwLock<T>) -> std::sync::LockResult<std::sync::RwLockReadGuard<'_, T>> { fn recover_read<T>(lock: &RwLock<T>) -> std::sync::LockResult<std::sync::RwLockReadGuard<'_, T>> {
match lock.read() { match lock.read() {
Ok(guard) => Ok(guard), Ok(guard) => Ok(guard),
Err(e) => { Err(_e) => {
tracing::warn!("[DataMasker] RwLock poisoned during read, recovering"); tracing::warn!("[DataMasker] RwLock poisoned during read, recovering");
// Poison error still gives us access to the inner guard // Poison error still gives us access to the inner guard
lock.read() lock.read()
@@ -141,7 +141,7 @@ impl DataMasker {
fn recover_write<T>(lock: &RwLock<T>) -> std::sync::LockResult<std::sync::RwLockWriteGuard<'_, T>> { fn recover_write<T>(lock: &RwLock<T>) -> std::sync::LockResult<std::sync::RwLockWriteGuard<'_, T>> {
match lock.write() { match lock.write() {
Ok(guard) => Ok(guard), Ok(guard) => Ok(guard),
Err(e) => { Err(_e) => {
tracing::warn!("[DataMasker] RwLock poisoned during write, recovering"); tracing::warn!("[DataMasker] RwLock poisoned during write, recovering");
lock.write() lock.write()
} }

View File

@@ -0,0 +1,187 @@
//! 进化引擎中间件
//! 在管家对话中检测并呈现"技能进化确认"提示
//! 优先级 78在 ButlerRouter@80 之前运行)
use async_trait::async_trait;
use std::sync::Arc;
use tokio::sync::RwLock;
use crate::middleware::{
AgentMiddleware, MiddlewareContext, MiddlewareDecision,
};
use zclaw_types::Result;
/// 待确认的进化事件
#[derive(Debug, Clone)]
pub struct PendingEvolution {
pub pattern_name: String,
pub trigger_suggestion: String,
pub description: String,
}
/// 进化引擎中间件
/// 检查是否有待确认的进化事件,根据模式:
/// - suggest 模式(默认): 注入确认提示到 system prompt
/// - auto 模式: 不注入,仅排队等待 kernel 自动处理
pub struct EvolutionMiddleware {
pending: Arc<RwLock<Vec<PendingEvolution>>>,
auto_mode: bool,
}
impl EvolutionMiddleware {
pub fn new() -> Self {
Self {
pending: Arc::new(RwLock::new(Vec::new())),
auto_mode: false,
}
}
/// Create with auto mode enabled
pub fn new_auto() -> Self {
Self {
pending: Arc::new(RwLock::new(Vec::new())),
auto_mode: true,
}
}
/// Check if auto mode is enabled
pub fn is_auto_mode(&self) -> bool {
self.auto_mode
}
/// 添加一个待确认的进化事件
pub async fn add_pending(&self, evolution: PendingEvolution) {
self.pending.write().await.push(evolution);
}
/// 获取并清除所有待确认事件
pub async fn drain_pending(&self) -> Vec<PendingEvolution> {
let mut pending = self.pending.write().await;
std::mem::take(&mut *pending)
}
/// 当前待确认事件数量
pub async fn pending_count(&self) -> usize {
self.pending.read().await.len()
}
}
impl Default for EvolutionMiddleware {
fn default() -> Self {
Self::new()
}
}
#[async_trait]
impl AgentMiddleware for EvolutionMiddleware {
fn name(&self) -> &str {
"evolution"
}
fn priority(&self) -> i32 {
78 // 在 ButlerRouter(80) 之前
}
async fn before_completion(
&self,
ctx: &mut MiddlewareContext,
) -> Result<MiddlewareDecision> {
// 先用 read lock 快速判空,避免每次对话都获取写锁
if self.pending.read().await.is_empty() {
return Ok(MiddlewareDecision::Continue);
}
// Auto mode: don't inject into prompt, leave for kernel to process
if self.auto_mode {
return Ok(MiddlewareDecision::Continue);
}
// Suggest mode: 只移除第一个事件,保留后续事件留待下次注入
let to_inject = {
let mut pending = self.pending.write().await;
if pending.is_empty() {
return Ok(MiddlewareDecision::Continue);
}
pending.remove(0)
};
let injection = format!(
"\n\n<evolution-suggestion>\n\
我注意到你经常做「{pattern}」相关的事情。\n\
我可以帮你整理成一个技能,以后直接说「{trigger}」就能用了。\n\
技能描述:{desc}\n\
如果你同意,请回复 '确认保存技能'。如果你想调整,可以告诉我怎么改。\n\
</evolution-suggestion>",
pattern = to_inject.pattern_name,
trigger = to_inject.trigger_suggestion,
desc = to_inject.description,
);
ctx.system_prompt.push_str(&injection);
tracing::info!(
"[EvolutionMiddleware] Injected evolution suggestion for: {}",
to_inject.pattern_name
);
Ok(MiddlewareDecision::Continue)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[tokio::test]
async fn test_no_pending_continues() {
let mw = EvolutionMiddleware::new();
assert_eq!(mw.pending_count().await, 0);
}
#[tokio::test]
async fn test_add_and_drain() {
let mw = EvolutionMiddleware::new();
mw.add_pending(PendingEvolution {
pattern_name: "报表生成".to_string(),
trigger_suggestion: "生成报表".to_string(),
description: "自动生成每日报表".to_string(),
})
.await;
assert_eq!(mw.pending_count().await, 1);
let drained = mw.drain_pending().await;
assert_eq!(drained.len(), 1);
assert_eq!(drained[0].pattern_name, "报表生成");
assert_eq!(mw.pending_count().await, 0);
}
#[tokio::test]
async fn test_name_and_priority() {
let mw = EvolutionMiddleware::new();
assert_eq!(mw.name(), "evolution");
assert_eq!(mw.priority(), 78);
}
#[tokio::test]
async fn test_only_first_event_injected() {
let mw = EvolutionMiddleware::new();
mw.add_pending(PendingEvolution {
pattern_name: "事件A".to_string(),
trigger_suggestion: "触发A".to_string(),
description: "描述A".to_string(),
})
.await;
mw.add_pending(PendingEvolution {
pattern_name: "事件B".to_string(),
trigger_suggestion: "触发B".to_string(),
description: "描述B".to_string(),
})
.await;
// 模拟注入:用 read 判空 + write 取第一个
let first = {
let mut pending = mw.pending.write().await;
pending.remove(0)
};
assert_eq!(first.pattern_name, "事件A");
assert_eq!(mw.pending_count().await, 1); // 事件B 仍保留
}
}

View File

@@ -11,14 +11,17 @@ use async_trait::async_trait;
use zclaw_types::Result; use zclaw_types::Result;
use crate::growth::GrowthIntegration; use crate::growth::GrowthIntegration;
use crate::middleware::{AgentMiddleware, MiddlewareContext, MiddlewareDecision}; use crate::middleware::{AgentMiddleware, MiddlewareContext, MiddlewareDecision};
use crate::middleware::evolution::EvolutionMiddleware;
/// Middleware that handles memory retrieval (pre-completion) and extraction (post-completion). /// Middleware that handles memory retrieval (pre-completion) and extraction (post-completion).
/// ///
/// Wraps `GrowthIntegration` and delegates: /// Wraps `GrowthIntegration` and delegates:
/// - `before_completion` → `enhance_prompt()` for memory injection /// - `before_completion` → `enhance_prompt()` for memory injection
/// - `after_completion` → `process_conversation()` for memory extraction /// - `after_completion` → `extract_combined()` for memory extraction + evolution check
pub struct MemoryMiddleware { pub struct MemoryMiddleware {
growth: GrowthIntegration, growth: std::sync::Arc<GrowthIntegration>,
/// Shared EvolutionMiddleware for pushing evolution suggestions
evolution_mw: Option<std::sync::Arc<EvolutionMiddleware>>,
/// Minimum seconds between extractions for the same agent (debounce). /// Minimum seconds between extractions for the same agent (debounce).
debounce_secs: u64, debounce_secs: u64,
/// Timestamp of last extraction per agent (for debouncing). /// Timestamp of last extraction per agent (for debouncing).
@@ -26,14 +29,21 @@ pub struct MemoryMiddleware {
} }
impl MemoryMiddleware { impl MemoryMiddleware {
pub fn new(growth: GrowthIntegration) -> Self { pub fn new(growth: std::sync::Arc<GrowthIntegration>) -> Self {
Self { Self {
growth, growth,
evolution_mw: None,
debounce_secs: 30, debounce_secs: 30,
last_extraction: std::sync::Mutex::new(std::collections::HashMap::new()), last_extraction: std::sync::Mutex::new(std::collections::HashMap::new()),
} }
} }
/// Attach a shared EvolutionMiddleware for pushing evolution suggestions.
pub fn with_evolution(mut self, mw: std::sync::Arc<EvolutionMiddleware>) -> Self {
self.evolution_mw = Some(mw);
self
}
/// Set the debounce interval in seconds. /// Set the debounce interval in seconds.
pub fn with_debounce_secs(mut self, secs: u64) -> Self { pub fn with_debounce_secs(mut self, secs: u64) -> Self {
self.debounce_secs = secs; self.debounce_secs = secs;
@@ -52,6 +62,49 @@ impl MemoryMiddleware {
map.insert(agent_id.to_string(), now); map.insert(agent_id.to_string(), now);
true true
} }
/// Check for evolvable patterns and push suggestions to EvolutionMiddleware.
async fn check_and_push_evolution(&self, agent_id: &zclaw_types::AgentId) {
let evolution_mw = match &self.evolution_mw {
Some(mw) => mw,
None => return,
};
match self.growth.check_evolution(agent_id).await {
Ok(patterns) if !patterns.is_empty() => {
for pattern in &patterns {
let trigger = pattern
.common_steps
.first()
.cloned()
.unwrap_or_else(|| pattern.pain_pattern.clone());
evolution_mw.add_pending(
crate::middleware::evolution::PendingEvolution {
pattern_name: pattern.pain_pattern.clone(),
trigger_suggestion: trigger,
description: format!(
"基于 {} 次重复经验,自动固化技能",
pattern.total_reuse
),
},
).await;
}
tracing::info!(
"[MemoryMiddleware] Pushed {} evolution candidates for agent {}",
patterns.len(),
agent_id
);
}
Ok(_) => {
tracing::debug!("[MemoryMiddleware] No evolvable patterns found");
}
Err(e) => {
tracing::debug!(
"[MemoryMiddleware] Evolution check failed (non-fatal): {}", e
);
}
}
}
} }
#[async_trait] #[async_trait]
@@ -65,11 +118,6 @@ impl AgentMiddleware for MemoryMiddleware {
ctx.user_input.chars().take(50).collect::<String>() ctx.user_input.chars().take(50).collect::<String>()
); );
// Retrieve relevant memories and inject into system prompt.
// The SqliteStorage retriever now uses FTS5-only matching — if FTS5 finds
// no relevant results, no memories are returned (no scope-based fallback).
// This prevents irrelevant high-importance memories from leaking into
// unrelated conversations.
let base = &ctx.system_prompt; let base = &ctx.system_prompt;
match self.growth.enhance_prompt(&ctx.agent_id, base, &ctx.user_input).await { match self.growth.enhance_prompt(&ctx.agent_id, base, &ctx.user_input).await {
Ok(enhanced) => { Ok(enhanced) => {
@@ -88,7 +136,6 @@ impl AgentMiddleware for MemoryMiddleware {
Ok(MiddlewareDecision::Continue) Ok(MiddlewareDecision::Continue)
} }
Err(e) => { Err(e) => {
// Non-fatal: retrieval failure should not block the conversation
tracing::warn!( tracing::warn!(
"[MemoryMiddleware] Memory retrieval failed (non-fatal): {}", "[MemoryMiddleware] Memory retrieval failed (non-fatal): {}",
e e
@@ -99,7 +146,6 @@ impl AgentMiddleware for MemoryMiddleware {
} }
async fn after_completion(&self, ctx: &MiddlewareContext) -> Result<()> { async fn after_completion(&self, ctx: &MiddlewareContext) -> Result<()> {
// Debounce: skip extraction if called too recently for this agent
let agent_key = ctx.agent_id.to_string(); let agent_key = ctx.agent_id.to_string();
if !self.should_extract(&agent_key) { if !self.should_extract(&agent_key) {
tracing::debug!( tracing::debug!(
@@ -113,8 +159,6 @@ impl AgentMiddleware for MemoryMiddleware {
return Ok(()); return Ok(());
} }
// Combined extraction: single LLM call produces both memories and structured facts.
// Avoids double LLM extraction ( process_conversation + extract_structured_facts).
match self.growth.extract_combined( match self.growth.extract_combined(
&ctx.agent_id, &ctx.agent_id,
&ctx.messages, &ctx.messages,
@@ -127,12 +171,14 @@ impl AgentMiddleware for MemoryMiddleware {
facts.len(), facts.len(),
agent_key agent_key
); );
// Check for evolvable patterns after successful extraction
self.check_and_push_evolution(&ctx.agent_id).await;
} }
Ok(None) => { Ok(None) => {
tracing::debug!("[MemoryMiddleware] No memories or facts extracted"); tracing::debug!("[MemoryMiddleware] No memories or facts extracted");
} }
Err(e) => { Err(e) => {
// Non-fatal: extraction failure should not affect the response
tracing::warn!("[MemoryMiddleware] Combined extraction failed: {}", e); tracing::warn!("[MemoryMiddleware] Combined extraction failed: {}", e);
} }
} }

View File

@@ -4,12 +4,16 @@
//! Inspired by DeerFlow's ToolErrorMiddleware: instead of propagating raw errors //! Inspired by DeerFlow's ToolErrorMiddleware: instead of propagating raw errors
//! that crash the agent loop, this middleware wraps tool errors into a structured //! that crash the agent loop, this middleware wraps tool errors into a structured
//! format that the LLM can use to self-correct. //! format that the LLM can use to self-correct.
//!
//! Also tracks consecutive tool failures across different tools — if N consecutive
//! tool calls all fail, the loop is aborted to prevent infinite retry cycles.
use async_trait::async_trait; use async_trait::async_trait;
use serde_json::Value; use serde_json::Value;
use zclaw_types::Result; use zclaw_types::Result;
use crate::driver::ContentBlock; use crate::driver::ContentBlock;
use crate::middleware::{AgentMiddleware, MiddlewareContext, ToolCallDecision}; use crate::middleware::{AgentMiddleware, MiddlewareContext, ToolCallDecision};
use std::sync::Mutex;
/// Middleware that intercepts tool call errors and formats recovery messages. /// Middleware that intercepts tool call errors and formats recovery messages.
/// ///
@@ -17,12 +21,18 @@ use crate::middleware::{AgentMiddleware, MiddlewareContext, ToolCallDecision};
pub struct ToolErrorMiddleware { pub struct ToolErrorMiddleware {
/// Maximum error message length before truncation. /// Maximum error message length before truncation.
max_error_length: usize, max_error_length: usize,
/// Maximum consecutive failures before aborting the loop.
max_consecutive_failures: u32,
/// Tracks consecutive tool failures.
consecutive_failures: Mutex<u32>,
} }
impl ToolErrorMiddleware { impl ToolErrorMiddleware {
pub fn new() -> Self { pub fn new() -> Self {
Self { Self {
max_error_length: 500, max_error_length: 500,
max_consecutive_failures: 3,
consecutive_failures: Mutex::new(0),
} }
} }
@@ -61,7 +71,6 @@ impl AgentMiddleware for ToolErrorMiddleware {
tool_input: &Value, tool_input: &Value,
) -> Result<ToolCallDecision> { ) -> Result<ToolCallDecision> {
// Pre-validate tool input structure for common issues. // Pre-validate tool input structure for common issues.
// This catches malformed JSON inputs before they reach the tool executor.
if tool_input.is_null() { if tool_input.is_null() {
tracing::warn!( tracing::warn!(
"[ToolErrorMiddleware] Tool '{}' received null input — replacing with empty object", "[ToolErrorMiddleware] Tool '{}' received null input — replacing with empty object",
@@ -69,6 +78,19 @@ impl AgentMiddleware for ToolErrorMiddleware {
); );
return Ok(ToolCallDecision::ReplaceInput(serde_json::json!({}))); return Ok(ToolCallDecision::ReplaceInput(serde_json::json!({})));
} }
// Check consecutive failure count — abort if too many failures
let failures = self.consecutive_failures.lock().unwrap_or_else(|e| e.into_inner());
if *failures >= self.max_consecutive_failures {
tracing::warn!(
"[ToolErrorMiddleware] Aborting loop: {} consecutive tool failures",
*failures
);
return Ok(ToolCallDecision::AbortLoop(
format!("连续 {} 次工具调用失败,已自动终止以避免无限重试", *failures)
));
}
Ok(ToolCallDecision::Allow) Ok(ToolCallDecision::Allow)
} }
@@ -78,14 +100,16 @@ impl AgentMiddleware for ToolErrorMiddleware {
tool_name: &str, tool_name: &str,
result: &Value, result: &Value,
) -> Result<()> { ) -> Result<()> {
let mut failures = self.consecutive_failures.lock().unwrap_or_else(|e| e.into_inner());
// Check if the tool result indicates an error. // Check if the tool result indicates an error.
if let Some(error) = result.get("error") { if let Some(error) = result.get("error") {
*failures += 1;
let error_msg = match error { let error_msg = match error {
Value::String(s) => s.clone(), Value::String(s) => s.clone(),
other => other.to_string(), other => other.to_string(),
}; };
let truncated = if error_msg.len() > self.max_error_length { let truncated = if error_msg.len() > self.max_error_length {
// Use char-boundary-safe truncation to avoid panic on UTF-8 strings (e.g. Chinese)
let end = error_msg.floor_char_boundary(self.max_error_length); let end = error_msg.floor_char_boundary(self.max_error_length);
format!("{}...(truncated)", &error_msg[..end]) format!("{}...(truncated)", &error_msg[..end])
} else { } else {
@@ -93,19 +117,19 @@ impl AgentMiddleware for ToolErrorMiddleware {
}; };
tracing::warn!( tracing::warn!(
"[ToolErrorMiddleware] Tool '{}' failed: {}", "[ToolErrorMiddleware] Tool '{}' failed ({}/{} consecutive): {}",
tool_name, truncated tool_name, *failures, self.max_consecutive_failures, truncated
); );
// Build a guided recovery message so the LLM can self-correct.
let guided_message = self.format_tool_error(tool_name, &truncated); let guided_message = self.format_tool_error(tool_name, &truncated);
// Inject into response_content so the agent loop feeds this back
// to the LLM alongside the raw tool result.
ctx.response_content.push(ContentBlock::Text { ctx.response_content.push(ContentBlock::Text {
text: guided_message, text: guided_message,
}); });
} else {
// Success — reset consecutive failure counter
*failures = 0;
} }
Ok(()) Ok(())
} }
} }

View File

@@ -11,7 +11,7 @@ use tokio::sync::RwLock;
use zclaw_memory::trajectory_store::{ use zclaw_memory::trajectory_store::{
TrajectoryEvent, TrajectoryStepType, TrajectoryStore, TrajectoryEvent, TrajectoryStepType, TrajectoryStore,
}; };
use zclaw_types::{Result, SessionId}; use zclaw_types::Result;
use crate::driver::ContentBlock; use crate::driver::ContentBlock;
use crate::middleware::{AgentMiddleware, MiddlewareContext, MiddlewareDecision}; use crate::middleware::{AgentMiddleware, MiddlewareContext, MiddlewareDecision};

View File

@@ -2,12 +2,15 @@
//! //!
//! Three-layer fallback strategy: //! Three-layer fallback strategy:
//! 1. Regex pattern matching (covers ~80% of common expressions) //! 1. Regex pattern matching (covers ~80% of common expressions)
//! 2. LLM-assisted parsing (for ambiguous/complex expressions) — TODO: wire when Haiku driver available //! 2. LLM-assisted parsing (for ambiguous/complex expressions) — FUTURE: post-release LLM-assisted natural language parsing
//! 3. Interactive clarification (return `Unclear`) //! 3. Interactive clarification (return `Unclear`)
//! //!
//! Lives in `zclaw-runtime` because it's a pure text→cron utility with no kernel dependency. //! Lives in `zclaw-runtime` because it's a pure text→cron utility with no kernel dependency.
use chrono::{Datelike, Timelike}; use std::sync::LazyLock;
use chrono::Timelike;
use regex::Regex;
use serde::{Deserialize, Serialize}; use serde::{Deserialize, Serialize};
use zclaw_types::AgentId; use zclaw_types::AgentId;
@@ -56,20 +59,88 @@ pub enum ScheduleParseResult {
} }
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
// Regex pattern library // Pre-compiled regex patterns (LazyLock — compiled once, reused forever)
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
/// A single pattern for matching Chinese time expressions. /// Time-of-day period fragment used across multiple patterns.
struct SchedulePattern { const PERIOD: &str = "(凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)?";
/// Regex pattern string
regex: &'static str, // extract_task_description
/// Cron template — use {h} for hour, {m} for minute, {dow} for day-of-week, {dom} for day-of-month static RE_TIME_STRIP: LazyLock<Regex> = LazyLock::new(|| {
cron_template: &'static str, Regex::new(
/// Human description template r"^(?:凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)?\d{1,2}[点时:](?:\d{1,2}分?|半)?"
description: &'static str, ).expect("static regex pattern is valid")
/// Base confidence for this pattern });
confidence: f32,
} // try_every_day
static RE_EVERY_DAY_EXACT: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(&format!(
r"(?:每天|每日)(?:的)?{}(\d{{1,2}})[点时:](?:(\d{{1,2}})|(半))?",
PERIOD
)).expect("static regex pattern is valid")
});
static RE_EVERY_DAY_PERIOD: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(
r"(?:每天|每日)(?:的)?(凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)"
).expect("static regex pattern is valid")
});
// try_every_week
static RE_EVERY_WEEK: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(&format!(
r"(?:每周|每个?星期|每个?礼拜)(一|二|三|四|五|六|日|天|周一|周二|周三|周四|周五|周六|周日|周天|星期一|星期二|星期三|星期四|星期五|星期六|星期日|星期天|礼拜一|礼拜二|礼拜三|礼拜四|礼拜五|礼拜六|礼拜日|礼拜天)(?:的)?{}(\d{{1,2}})[点时:](?:(\d{{1,2}})|(半))?",
PERIOD
)).expect("static regex pattern is valid")
});
// try_workday — also matches "工作日每天..." and "工作日每日..."
static RE_WORKDAY_EXACT: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(&format!(
r"(?:工作日|每个?工作日)(?:每天|每日)?(?:的)?{}(\d{{1,2}})[点时:](?:(\d{{1,2}})|(半))?",
PERIOD
)).expect("static regex pattern is valid")
});
static RE_WORKDAY_PERIOD: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(
r"(?:工作日|每个?工作日)(?:的)?(凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)"
).expect("static regex pattern is valid")
});
// try_interval
static RE_INTERVAL: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(r"每(\d{1,2})(小时|分钟|分|钟|个小时)").expect("static regex pattern is valid")
});
// try_monthly
static RE_MONTHLY: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(&format!(
r"(?:每月|每个月)(?:的)?(\d{{1,2}})[号日](?:的)?{}(\d{{1,2}})?[点时:]?(?:(\d{{1,2}})|(半))?",
PERIOD
)).expect("static regex pattern is valid")
});
// try_one_shot
static RE_ONE_SHOT: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(&format!(
r"(明天|后天|大后天)(?:的)?{}(\d{{1,2}})[点时:](?:(\d{{1,2}})|(半))?",
PERIOD
)).expect("static regex pattern is valid")
});
/// Matches same-day one-shot triggers: "下午3点半提醒我..." or "上午10点提醒我..."
/// Pattern: period + time + "提醒我" (no date prefix — implied today)
static RE_ONE_SHOT_TODAY: LazyLock<Regex> = LazyLock::new(|| {
Regex::new(&format!(
r"^{}(\d{{1,2}})[点时:](?:(\d{{1,2}})|(半))?.*提醒我",
PERIOD
)).expect("static regex pattern is valid")
});
// ---------------------------------------------------------------------------
// Helper lookups (pure functions, no allocation)
// ---------------------------------------------------------------------------
/// Chinese time period keywords → hour mapping /// Chinese time period keywords → hour mapping
fn period_to_hour(period: &str) -> Option<u32> { fn period_to_hour(period: &str) -> Option<u32> {
@@ -99,6 +170,23 @@ fn weekday_to_cron(day: &str) -> Option<&'static str> {
} }
} }
/// Adjust hour based on time-of-day period. Chinese 12-hour convention:
/// 下午3点 = 15, 晚上8点 = 20, etc. Morning hours stay as-is.
fn adjust_hour_for_period(hour: u32, period: Option<&str>) -> u32 {
if let Some(p) = period {
match p {
"下午" | "午后" => { if hour < 12 { hour + 12 } else { hour } }
"晚上" | "晚间" | "夜里" | "夜晚" => { if hour < 12 { hour + 12 } else { hour } }
"傍晚" | "黄昏" => { if hour < 12 { hour + 12 } else { hour } }
"中午" => { if hour == 12 { 12 } else if hour < 12 { hour + 12 } else { hour } }
"半夜" | "午夜" => { if hour == 12 { 0 } else { hour } }
_ => hour,
}
} else {
hour
}
}
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
// Parser implementation // Parser implementation
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
@@ -113,35 +201,24 @@ pub fn parse_nl_schedule(input: &str, default_agent_id: &AgentId) -> SchedulePar
return ScheduleParseResult::Unclear; return ScheduleParseResult::Unclear;
} }
// Extract task description (everything after keywords like "提醒我", "帮我")
let task_description = extract_task_description(input); let task_description = extract_task_description(input);
// --- Pattern 1: 每天 + 时间 --- // Try workday BEFORE every_day, so "工作日每天..." matches workday first
if let Some(result) = try_every_day(input, &task_description, default_agent_id) {
return result;
}
// --- Pattern 2: 每周N + 时间 ---
if let Some(result) = try_every_week(input, &task_description, default_agent_id) {
return result;
}
// --- Pattern 3: 工作日 + 时间 ---
if let Some(result) = try_workday(input, &task_description, default_agent_id) { if let Some(result) = try_workday(input, &task_description, default_agent_id) {
return result; return result;
} }
if let Some(result) = try_every_day(input, &task_description, default_agent_id) {
// --- Pattern 4: 每N小时/分钟 --- return result;
}
if let Some(result) = try_every_week(input, &task_description, default_agent_id) {
return result;
}
if let Some(result) = try_interval(input, &task_description, default_agent_id) { if let Some(result) = try_interval(input, &task_description, default_agent_id) {
return result; return result;
} }
// --- Pattern 5: 每月N号 ---
if let Some(result) = try_monthly(input, &task_description, default_agent_id) { if let Some(result) = try_monthly(input, &task_description, default_agent_id) {
return result; return result;
} }
// --- Pattern 6: 明天/后天 + 时间 (one-shot) ---
if let Some(result) = try_one_shot(input, &task_description, default_agent_id) { if let Some(result) = try_one_shot(input, &task_description, default_agent_id) {
return result; return result;
} }
@@ -160,13 +237,7 @@ fn extract_task_description(input: &str) -> String {
let mut desc = input.to_string(); let mut desc = input.to_string();
// Strip prefixes + time expressions in alternating passes until stable
let time_re = regex::Regex::new(
r"^(?:凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)?\d{1,2}[点时:]\d{0,2}分?"
).unwrap_or_else(|_| regex::Regex::new("").unwrap());
for _ in 0..3 { for _ in 0..3 {
// Pass 1: strip prefixes
loop { loop {
let mut stripped = false; let mut stripped = false;
for prefix in &strip_prefixes { for prefix in &strip_prefixes {
@@ -177,8 +248,7 @@ fn extract_task_description(input: &str) -> String {
} }
if !stripped { break; } if !stripped { break; }
} }
// Pass 2: strip time expressions let new_desc = RE_TIME_STRIP.replace(&desc, "").to_string();
let new_desc = time_re.replace(&desc, "").to_string();
if new_desc == desc { break; } if new_desc == desc { break; }
desc = new_desc; desc = new_desc;
} }
@@ -186,35 +256,23 @@ fn extract_task_description(input: &str) -> String {
desc.trim().to_string() desc.trim().to_string()
} }
// -- Pattern matchers -- // -- Pattern matchers (all use pre-compiled statics) --
/// Adjust hour based on time-of-day period. Chinese 12-hour convention: /// Extract minute value from a regex capture group that may be a digit string or "半".
/// 下午3点 = 15, 晚上8点 = 20, etc. Morning hours stay as-is. /// Group 3 is the digit capture, group 4 is absent (used when "半" matches instead).
fn adjust_hour_for_period(hour: u32, period: Option<&str>) -> u32 { fn extract_minute(caps: &regex::Captures, digit_group: usize, han_group: usize) -> u32 {
if let Some(p) = period { // Check if the "半" (half) group matched
match p { if caps.get(han_group).is_some() {
"下午" | "午后" => { if hour < 12 { hour + 12 } else { hour } } return 30;
"晚上" | "晚间" | "夜里" | "夜晚" => { if hour < 12 { hour + 12 } else { hour } }
"傍晚" | "黄昏" => { if hour < 12 { hour + 12 } else { hour } }
"中午" => { if hour == 12 { 12 } else if hour < 12 { hour + 12 } else { hour } }
"半夜" | "午夜" => { if hour == 12 { 0 } else { hour } }
_ => hour,
}
} else {
hour
} }
caps.get(digit_group).map(|m| m.as_str().parse().unwrap_or(0)).unwrap_or(0)
} }
const PERIOD_PATTERN: &str = "(凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)?";
fn try_every_day(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> { fn try_every_day(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> {
let re = regex::Regex::new( if let Some(caps) = RE_EVERY_DAY_EXACT.captures(input) {
&format!(r"(?:每天|每日)(?:的)?{}(\d{{1,2}})[点时:](\d{{1,2}})?", PERIOD_PATTERN)
).ok()?;
if let Some(caps) = re.captures(input) {
let period = caps.get(1).map(|m| m.as_str()); let period = caps.get(1).map(|m| m.as_str());
let raw_hour: u32 = caps.get(2)?.as_str().parse().ok()?; let raw_hour: u32 = caps.get(2)?.as_str().parse().ok()?;
let minute: u32 = caps.get(3).map(|m| m.as_str().parse().unwrap_or(0)).unwrap_or(0); let minute: u32 = extract_minute(&caps, 3, 4);
let hour = adjust_hour_for_period(raw_hour, period); let hour = adjust_hour_for_period(raw_hour, period);
if hour > 23 || minute > 59 { if hour > 23 || minute > 59 {
return None; return None;
@@ -228,9 +286,7 @@ fn try_every_day(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<Sch
})); }));
} }
// "每天早上/下午..." without explicit hour if let Some(caps) = RE_EVERY_DAY_PERIOD.captures(input) {
let re2 = regex::Regex::new(r"(?:每天|每日)(?:的)?(凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)").ok()?;
if let Some(caps) = re2.captures(input) {
let period = caps.get(1)?.as_str(); let period = caps.get(1)?.as_str();
if let Some(hour) = period_to_hour(period) { if let Some(hour) = period_to_hour(period) {
return Some(ScheduleParseResult::Exact(ParsedSchedule { return Some(ScheduleParseResult::Exact(ParsedSchedule {
@@ -247,16 +303,12 @@ fn try_every_day(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<Sch
} }
fn try_every_week(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> { fn try_every_week(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> {
let re = regex::Regex::new( let caps = RE_EVERY_WEEK.captures(input)?;
&format!(r"(?:每周|每个?星期|每个?礼拜)(一|二|三|四|五|六|日|天|周一|周二|周三|周四|周五|周六|周日|周天|星期一|星期二|星期三|星期四|星期五|星期六|星期日|星期天|礼拜一|礼拜二|礼拜三|礼拜四|礼拜五|礼拜六|礼拜日|礼拜天)(?:的)?{}(\d{{1,2}})[点时:](\d{{1,2}})?", PERIOD_PATTERN)
).ok()?;
let caps = re.captures(input)?;
let day_str = caps.get(1)?.as_str(); let day_str = caps.get(1)?.as_str();
let dow = weekday_to_cron(day_str)?; let dow = weekday_to_cron(day_str)?;
let period = caps.get(2).map(|m| m.as_str()); let period = caps.get(2).map(|m| m.as_str());
let raw_hour: u32 = caps.get(3)?.as_str().parse().ok()?; let raw_hour: u32 = caps.get(3)?.as_str().parse().ok()?;
let minute: u32 = caps.get(4).map(|m| m.as_str().parse().unwrap_or(0)).unwrap_or(0); let minute: u32 = extract_minute(&caps, 4, 5);
let hour = adjust_hour_for_period(raw_hour, period); let hour = adjust_hour_for_period(raw_hour, period);
if hour > 23 || minute > 59 { if hour > 23 || minute > 59 {
return None; return None;
@@ -272,14 +324,10 @@ fn try_every_week(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<Sc
} }
fn try_workday(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> { fn try_workday(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> {
let re = regex::Regex::new( if let Some(caps) = RE_WORKDAY_EXACT.captures(input) {
&format!(r"(?:工作日|每个?工作日|工作日(?:的)?){}(\d{{1,2}})[点时:](\d{{1,2}})?", PERIOD_PATTERN)
).ok()?;
if let Some(caps) = re.captures(input) {
let period = caps.get(1).map(|m| m.as_str()); let period = caps.get(1).map(|m| m.as_str());
let raw_hour: u32 = caps.get(2)?.as_str().parse().ok()?; let raw_hour: u32 = caps.get(2)?.as_str().parse().ok()?;
let minute: u32 = caps.get(3).map(|m| m.as_str().parse().unwrap_or(0)).unwrap_or(0); let minute: u32 = extract_minute(&caps, 3, 4);
let hour = adjust_hour_for_period(raw_hour, period); let hour = adjust_hour_for_period(raw_hour, period);
if hour > 23 || minute > 59 { if hour > 23 || minute > 59 {
return None; return None;
@@ -293,11 +341,7 @@ fn try_workday(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<Sched
})); }));
} }
// "工作日下午3点" style if let Some(caps) = RE_WORKDAY_PERIOD.captures(input) {
let re2 = regex::Regex::new(
r"(?:工作日|每个?工作日)(?:的)?(凌晨|早上|早晨|上午|中午|下午|午后|傍晚|黄昏|晚上|晚间|夜里|夜晚|半夜|午夜)"
).ok()?;
if let Some(caps) = re2.captures(input) {
let period = caps.get(1)?.as_str(); let period = caps.get(1)?.as_str();
if let Some(hour) = period_to_hour(period) { if let Some(hour) = period_to_hour(period) {
return Some(ScheduleParseResult::Exact(ParsedSchedule { return Some(ScheduleParseResult::Exact(ParsedSchedule {
@@ -314,9 +358,7 @@ fn try_workday(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<Sched
} }
fn try_interval(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> { fn try_interval(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> {
// "每2小时", "每30分钟", "每N小时/分钟" if let Some(caps) = RE_INTERVAL.captures(input) {
let re = regex::Regex::new(r"每(\d{1,2})(小时|分钟|分|钟|个小时)").ok()?;
if let Some(caps) = re.captures(input) {
let n: u32 = caps.get(1)?.as_str().parse().ok()?; let n: u32 = caps.get(1)?.as_str().parse().ok()?;
if n == 0 { if n == 0 {
return None; return None;
@@ -340,15 +382,11 @@ fn try_interval(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<Sche
} }
fn try_monthly(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> { fn try_monthly(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> {
let re = regex::Regex::new( if let Some(caps) = RE_MONTHLY.captures(input) {
&format!(r"(?:每月|每个月)(?:的)?(\d{{1,2}})[号日](?:的)?{}(\d{{1,2}})?[点时:]?(\d{{1,2}})?", PERIOD_PATTERN)
).ok()?;
if let Some(caps) = re.captures(input) {
let day: u32 = caps.get(1)?.as_str().parse().ok()?; let day: u32 = caps.get(1)?.as_str().parse().ok()?;
let period = caps.get(2).map(|m| m.as_str()); let period = caps.get(2).map(|m| m.as_str());
let raw_hour: u32 = caps.get(3).map(|m| m.as_str().parse().unwrap_or(9)).unwrap_or(9); let raw_hour: u32 = caps.get(3).map(|m| m.as_str().parse().unwrap_or(9)).unwrap_or(9);
let minute: u32 = caps.get(4).map(|m| m.as_str().parse().unwrap_or(0)).unwrap_or(0); let minute: u32 = extract_minute(&caps, 4, 5);
let hour = adjust_hour_for_period(raw_hour, period); let hour = adjust_hour_for_period(raw_hour, period);
if day > 31 || hour > 23 || minute > 59 { if day > 31 || hour > 23 || minute > 59 {
return None; return None;
@@ -366,42 +404,70 @@ fn try_monthly(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<Sched
} }
fn try_one_shot(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> { fn try_one_shot(input: &str, task_desc: &str, agent_id: &AgentId) -> Option<ScheduleParseResult> {
let re = regex::Regex::new( // First try explicit date prefix: 明天/后天/大后天 + time
&format!(r"(明天|后天|大后天)(?:的)?{}(\d{{1,2}})[点时:](\d{{1,2}})?", PERIOD_PATTERN) if let Some(caps) = RE_ONE_SHOT.captures(input) {
).ok()?; let day_offset = match caps.get(1)?.as_str() {
"明天" => 1,
"后天" => 2,
"大后天" => 3,
_ => return None,
};
let period = caps.get(2).map(|m| m.as_str());
let raw_hour: u32 = caps.get(3)?.as_str().parse().ok()?;
let minute: u32 = extract_minute(&caps, 4, 5);
let hour = adjust_hour_for_period(raw_hour, period);
if hour > 23 || minute > 59 {
return None;
}
let caps = re.captures(input)?; let target = chrono::Utc::now()
let day_offset = match caps.get(1)?.as_str() { .checked_add_signed(chrono::Duration::days(day_offset))
"明天" => 1, .unwrap_or_else(chrono::Utc::now)
"后天" => 2, .with_hour(hour)
"大后天" => 3, .unwrap_or_else(|| chrono::Utc::now())
_ => return None, .with_minute(minute)
}; .unwrap_or_else(|| chrono::Utc::now())
let period = caps.get(2).map(|m| m.as_str()); .with_second(0)
let raw_hour: u32 = caps.get(3)?.as_str().parse().ok()?; .unwrap_or_else(|| chrono::Utc::now());
let minute: u32 = caps.get(4).map(|m| m.as_str().parse().unwrap_or(0)).unwrap_or(0);
let hour = adjust_hour_for_period(raw_hour, period); return Some(ScheduleParseResult::Exact(ParsedSchedule {
if hour > 23 || minute > 59 { cron_expression: target.to_rfc3339(),
return None; natural_description: format!("{} {:02}:{:02}", caps.get(1)?.as_str(), hour, minute),
confidence: 0.88,
task_description: task_desc.to_string(),
task_target: TaskTarget::Agent(agent_id.to_string()),
}));
} }
let target = chrono::Utc::now() // Then try same-day implicit: "下午3点半提醒我..." (no date prefix)
.checked_add_signed(chrono::Duration::days(day_offset)) if let Some(caps) = RE_ONE_SHOT_TODAY.captures(input) {
.unwrap_or_else(chrono::Utc::now) let period = caps.get(1).map(|m| m.as_str());
.with_hour(hour) let raw_hour: u32 = caps.get(2)?.as_str().parse().ok()?;
.unwrap_or_else(|| chrono::Utc::now()) let minute: u32 = extract_minute(&caps, 3, 4);
.with_minute(minute) let hour = adjust_hour_for_period(raw_hour, period);
.unwrap_or_else(|| chrono::Utc::now()) if hour > 23 || minute > 59 {
.with_second(0) return None;
.unwrap_or_else(|| chrono::Utc::now()); }
Some(ScheduleParseResult::Exact(ParsedSchedule { let target = chrono::Utc::now()
cron_expression: target.to_rfc3339(), .with_hour(hour)
natural_description: format!("{} {:02}:{:02}", caps.get(1)?.as_str(), hour, minute), .unwrap_or_else(|| chrono::Utc::now())
confidence: 0.88, .with_minute(minute)
task_description: task_desc.to_string(), .unwrap_or_else(|| chrono::Utc::now())
task_target: TaskTarget::Agent(agent_id.to_string()), .with_second(0)
})) .unwrap_or_else(|| chrono::Utc::now());
let period_desc = period.unwrap_or("");
return Some(ScheduleParseResult::Exact(ParsedSchedule {
cron_expression: target.to_rfc3339(),
natural_description: format!("今天{} {:02}:{:02}", period_desc, hour, minute),
confidence: 0.82,
task_description: task_desc.to_string(),
task_target: TaskTarget::Agent(agent_id.to_string()),
}));
}
None
} }
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
@@ -590,4 +656,79 @@ mod tests {
fn test_task_description_extraction() { fn test_task_description_extraction() {
assert_eq!(extract_task_description("每天早上9点提醒我查房"), "查房"); assert_eq!(extract_task_description("每天早上9点提醒我查房"), "查房");
} }
// --- New tests for BUG-3 (半) and BUG-4 (工作日每天) ---
#[test]
fn test_every_day_half_hour() {
// "8点半" should parse as 08:30
let result = parse_nl_schedule("每天早上8点半提醒我打卡", &default_agent());
match result {
ScheduleParseResult::Exact(s) => {
assert_eq!(s.cron_expression, "30 8 * * *");
}
_ => panic!("Expected Exact, got {:?}", result),
}
}
#[test]
fn test_every_day_afternoon_half() {
// "下午3点半" should parse as 15:30
let result = parse_nl_schedule("每天下午3点半提醒我", &default_agent());
match result {
ScheduleParseResult::Exact(s) => {
assert_eq!(s.cron_expression, "30 15 * * *");
}
_ => panic!("Expected Exact, got {:?}", result),
}
}
#[test]
fn test_workday_with_every_day_prefix() {
// "工作日每天早上8点半" should parse as weekday 08:30 with 1-5
let result = parse_nl_schedule("工作日每天早上8点半提醒我打卡", &default_agent());
match result {
ScheduleParseResult::Exact(s) => {
assert_eq!(s.cron_expression, "30 8 * * 1-5");
}
_ => panic!("Expected Exact, got {:?}", result),
}
}
#[test]
fn test_workday_half_hour() {
// "工作日下午5点半" should parse as weekday 17:30
let result = parse_nl_schedule("工作日下午5点半提醒我写周报", &default_agent());
match result {
ScheduleParseResult::Exact(s) => {
assert_eq!(s.cron_expression, "30 17 * * 1-5");
}
_ => panic!("Expected Exact, got {:?}", result),
}
}
#[test]
fn test_every_week_half_hour() {
// "每周一下午3点半" should parse as 15:30 on Monday
let result = parse_nl_schedule("每周一下午3点半提醒我开会", &default_agent());
match result {
ScheduleParseResult::Exact(s) => {
assert_eq!(s.cron_expression, "30 15 * * 1");
}
_ => panic!("Expected Exact, got {:?}", result),
}
}
#[test]
fn test_one_shot_half_hour() {
// "明天早上9点半" should parse as tomorrow 09:30
let result = parse_nl_schedule("明天早上9点半提醒我开会", &default_agent());
match result {
ScheduleParseResult::Exact(s) => {
// Should contain the time in ISO format
assert!(s.cron_expression.contains("T09:30:"));
}
_ => panic!("Expected Exact, got {:?}", result),
}
}
} }

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