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Author SHA1 Message Date
chiguyong bbbf9cd40a feat(bitable): add bitable companion service with full P0-P2 fixes 
Bitable is a multi-dimensional table companion service that runs alongside
the main AgentKit server. It provides structured data storage with formula
fields, views, and ingestion pipelines.

Major components:
- Domain models (Pydantic v2): Table, Field, Record, View, RecalcTask
- SQLAlchemy 2 async ORM with independent bitable PostgreSQL schema
- Formula engine: AST parser, DAG, Kahn topological sort, safe eval
- RecalcWorker: atomic task claiming (FOR UPDATE SKIP LOCKED), topo-order
  processing, stale-threshold reaper for crash recovery
- REST API (/api/v1/bitable): tables, fields, records, views, files
- BitableTool: agent-facing tool with batch chunking (500/batch)
- CLI: agentkit bitable subcommands (create, list, import-excel, etc.)
- Frontend: Vue 3 + vxe-table grid with field management, views, filters
- Ingestion: Excel (openpyxl), database reflection, API collector

Security fixes (ce-code-review P0 + ce-debug P1):
- SQL injection prevention (field_id validation, parameterized queries)
- IDOR protection (_check_table_ownership on all table-level endpoints)
- SSRF prevention (URL scheme + private IP validation in parse_excel_url)
- OOM prevention (streaming file upload, batch delete, batch insert)
- Atomic recalc task claiming (FOR UPDATE SKIP LOCKED)
- Formula engine cache invalidation on field changes
- Composite cursor pagination for non-id sort orders
- Batch upsert (eliminates N+1 queries)
- Sync I/O offloaded to thread pool in async contexts
- Internal token auth (X-Internal-Token, hmac.compare_digest)
- PK unique index enforcement

Test coverage: 88 unit tests (95 skipped without Docker)
 2026-06-25 01:09:59 +08:00
chiguyong 567cbc9c9b refactor: simplify code across U1-U7 (bug fix + efficiency + reuse + quality) 2026-06-24 22:35:52 +08:00
chiguyong fa152e24ac feat(skills): add progressive skill loading with disclosure_level=0 (U5) 
When disclosure_level=0, system prompt only injects skill name + description
(summary mode). SkillDetailTool is injected into the tool set, allowing the
LLM to load full instructions on-demand via skill_detail(query). This reduces
context window consumption when many skills are registered.
 2026-06-24 21:49:00 +08:00
chiguyong 20a4c55d5b feat(skills): SkillHarness 前置条件 + 风险守卫学习增强 
- cli/skill.py: skill learn 子命令增强
- evolution/risk_guard_learner.py: 风险守卫学习改进
- memory/models.py: 记忆模型扩展
- skills/base.py + loader.py: SkillHarness 前置条件支持
- 对应测试更新
 2026-06-24 18:56:51 +08:00
chiguyong fef7ecea39 feat(skills): SkillHarness 激活前置条件 + 风险守卫学习 
基于 SkillHarness 论文（arXiv:2606.20636）与 Agent Skills 综述
（arXiv:2602.12430）引入激活前置条件（preconditions）与来源标记
（provenance），并新增从失败轨迹学习风险守卫建议的能力。

变更内容：
- U1: SkillConfig 新增 v7 preconditions/provenance 字段（base.py）
- U2: build_skill_system_prompt 注入 preconditions 软检查段落
- U3: SkillLoader 三路径记录 provenance + entry_points 危险能力告警
- U4: 10 个业务 Skill YAML 补充 preconditions（2-4 条中文短句）
- U5: RiskGuardLearner 从失败轨迹学习风险守卫建议（人工审查，不自动应用）
- U6: CLI 命令 agentkit skill learn-risk-guards

关键决策：
- KTD1: preconditions 通过 system_prompt 注入（软检查），不做硬 LLM 调用
- KTD2: RiskGuardLearner 不自动应用，需人工审查（论文显示 75% 自动学习不安全）
- KTD3: provenance 为轻量字符串，不加 hash/签名（无合规需求）

测试：39 个新增单元测试全部通过，ruff 检查通过。
 2026-06-24 13:56:37 +08:00
chiguyong 3337589395 fix(review): document-processing code review fixes — validation, tests, formatting
Deploy to Production / deploy (push) Waiting to run Details 
- SkillConfig._validate_v2: validate fallback_strategies against
  ReWOOEngine.VALID_STRATEGIES (lazy import, #20)
- test_skill_config: +4 tests for fallback_strategies validation
- test_document_loader: +8 xlsx edge case tests (empty workbook,
  malformed bytes, column mismatch, row/cell truncation, multi-sheet,
  file size limit, None cells, #16)
- test_execution_modes: fix ReWOOEngine patch path (lazy import ->
  patch at source) + FakeReWOOEngine.execute return .output attribute
- config_driven: ruff formatting (quotes, blank lines after imports)
- project_rules: remove stale "known failing test" note (now passes)
 2026-06-23 20:21:19 +08:00
chiguyong cac9c73dd5 fix(routing): U1-U6 路由优化 + 修复方案 + 代码审查修复 
实现 6 个修复单元（U1-U6）并应用 ce-code-review 发现的 5 项安全修复。

## U1: benchmark 超时阈值
- 按 difficulty 分级超时：easy=45s, medium=60s, hard=90s
- 替换原单一 60s 硬编码

## U2: OpenAICompatibleProvider httpx 超时
- 新增 timeout 参数（默认 120s），替换硬编码 60s
- ProviderConfig.timeout 透传到 Provider
- 新增 2 项单元测试

## U3: 激活 QualityGate skill_match 校验
- BaseAgent._build_skill_context() 构造 skill_context
- 在 base.py / tasks.py / runner.py 三处传入 QualityGate.validate()

## U4: 添加 disambiguation_keywords 字段
- IntentConfig 新增 disambiguation_keywords 字段
- 8 个 skill YAML 补充该字段

## U5: 优化 RequestPreprocessor 路由正则
- 拆分 _FACTUAL_RE 为 CN/EN 双正则（中文无空格）
- 新增 _MATH_RE / _TRANSLATION_RE 纯模式
- _TOOL_CONTEXT_RE 排除需要工具的实时查询
- 多行输入守卫 + 结尾标点支持
- 新增 21 项单元测试（共 40 项全通过）

## U6: 重新基准测试
- 真实 LLM benchmark：准确率 60% -> 93.3%
- 4/5 通过，p50=40.8s，一致性=100%
- 旧基线备份至 baseline_2026-06-17_old_arch.json

## ce-code-review 修复（5 项）
- 修复 \s 字符类匹配换行符的安全隐患
- 添加事实/数学正则的结尾标点支持
- 修复 geo_optimizer.yaml 关键词重复
- 修复 _login_with_retry 不可达 return
- 修复 real_llm_server fixture stderr_fh 资源泄漏

测试：tests/unit/chat/ 63 项全通过，ruff 检查通过。
 2026-06-20 19:31:49 +08:00
chiguyong 8713636d50 feat(marketplace): add Phase B/C - CostAwareRouter, OrganizationContext, AlignmentGuard, Soul Evolution, Auction, Server Integration 
Phase B:
- U1: CostAwareRouter with 3-layer routing (rule/LLM/capability matching)
- U6: OrganizationContext with agent profiles and capability-based discovery
- U7: AlignmentGuard with constraint injection and cascade detection

Phase C:
- U8: Soul dynamic evolution with version tracking and reflection-triggered updates
- U9: Auction mechanism as optional advanced routing mode
- U10: Server integration + end-to-end integration tests

250 new tests passing across all units.
 2026-06-10 19:09:02 +08:00
chiguyong 5b42487d8a feat(core): add ReWOO, Plan-and-Execute, Reflexion execution engines 
Phase A of Multi-Agent Marketplace architecture:
- ReWOOEngine: plan-all-then-execute pattern for parallel data fetch
- PlanExecEngine: adapter wrapping GoalPlanner+PlanExecutor+PipelineReplanner
- ReflexionEngine: ReAct + Evaluate + Reflect + Retry for high-precision tasks
- SkillConfig: extend VALID_EXECUTION_MODES with rewoo/plan_exec/reflexion
- ConfigDrivenAgent: add _handle_rewoo/_handle_plan_exec/_handle_reflexion routes
- 5 professional agent YAML configs with layered model defaults
- 107 unit tests passing
 2026-06-10 17:08:48 +08:00
chiguyong fd4a811929 feat(phase1): implement core kernel and experience foundation (U1-U5) 
- U1: GoalPlanner - structured goal decomposition wrapping _decompose_task()
- U2: PlanExecutor - parallel execution with retry/skip/replace strategies
- U3: PlanChecker - quality gate + review + experience writing
- U4: Skill spec upgrade - dependencies, capabilities, version management
- U5: ExperienceStore - PostgreSQL+pgvector task experience storage

208 new tests passing, fully backward compatible.
 2026-06-09 23:57:03 +08:00
chiguyong 03a5167366 feat(pipeline): U6 step-level retry with exponential backoff and saga compensation 
Add StepRetryPolicy with jitter-based exponential backoff, SagaOrchestrator
with LIFO compensation pattern, integrate retry_policy and compensate
fields into PipelineStage/PipelineStep schema, add GEO pipeline
compensation definitions for all 7 steps.
 2026-06-07 17:26:07 +08:00
chiguyong 1390bd8d6e feat(skills): U5 GEO Pipeline orchestration with DAG execution 
- GEOPipeline: YAML-driven DAG pipeline with parallel/sequential execution
- PipelineStep with input_mapping ($.input.xxx, $.steps.name.output.xxx)
- Topological sort for execution groups, SharedWorkspace integration
- geo_full_pipeline.yaml: detect→analyze→optimize→track workflow
- 10 tests passing
 2026-06-06 22:34:24 +08:00
chiguyong 6e362a8ae7 feat(agentkit): Phase 4 enterprise production upgrade — 12 Implementation Units 
Phase A (P0): EpisodicMemory pgvector search+EmbeddingCache, ReAct timeout+CancellationToken, evolution system fix (A/B test+LLMPromptOptimizer+StrategyTuner), AnthropicProvider native Messages API
Phase B (P1): RetryPolicy+CircuitBreaker, chat_stream fallback chain, WebSocket endpoint, SSE stream fix, Evolution+Memory API routes (7 endpoints), embedding cache+Enhanced Search per-KB degradation fix
Phase C (P2): GeminiProvider native generateContent API, Agent state lock+config hot-reload

Tests: 1301 passed, 18 skipped, 0 failed
 2026-06-06 21:51:04 +08:00
chiguyong 0456429beb fix(review): address all 14 P2 advisory findings 2026-06-06 18:20:46 +08:00
chiguyong 8620751864 fix(review): address P0+P1 findings from Tier 2 code review 
P0: MemoryRetriever.retrieve score mutation fix
P1: Redis atomic Lua script, deprecated API fix, SQLite WAL mode,
Redis URL masking, UniqueConstraint, TraceRecorder completed flag,
EpisodicMemory recall improvement, LLMReflector sanitization,
A/B test safety, generator cleanup, ContextCompressor guards,
OpenAIEmbedder reuse, Pipeline failure handling, Metrics O(1),
Health check Redis PING, CLI skill loading, CORS config,
API key direct pass-through

Tests: 924 passed, 18 skipped, 0 failed
 2026-06-06 17:57:47 +08:00
chiguyong f858d279f3 feat(agentkit): Phase 3 upgrade - persistence, memory, evolution, observability 
10 Implementation Units across 3 phases:

Phase A - Infrastructure:
- U1: RedisTaskStore with Redis/memory backend + factory function
- U2: TraceRecorder for execution trace recording
- U3: PersistentEvolutionStore with SQLite backend

Phase B - Core Capabilities:
- U4: MemoryRetriever integration into ReAct engine
- U5: Embedder abstraction + EpisodicMemory vector search
- U6: LLMReflector for LLM-in-the-loop reflection
- U7: SkillPipeline for multi-skill orchestration

Phase C - Enhancement:
- U8: SKILL.md format + progressive disclosure levels
- U9: ContextCompressor + prompt cache rendering
- U10: Structured logging + metrics endpoint + enhanced health check

Tests: 924 passed, 18 skipped, 0 failed
 2026-06-06 17:17:45 +08:00
chiguyong acec8ff743 feat(evolution): Phase A - lifecycle hooks + EvolutionConfig 
U11: EvolutionMixin integrated into ConfigDrivenAgent lifecycle
  - on_task_complete triggers evolve_after_task
  - on_task_failed records failure patterns
  - Evolution errors never break main task flow

U12: EvolutionConfig added to SkillConfig
  - enabled, reflect_on_failure, auto_apply, min_quality_threshold
  - Backward compatible: defaults to enabled=False

21 new tests passing, no regression.
 2026-06-06 12:05:56 +08:00
chiguyong f87b790c0f feat(agentkit): v2 Phase 1 - ReAct/LLM Gateway/Skill/Server + review fixes 
535 unit + 52 integration tests passing. README added.
 2026-06-05 23:32:16 +08:00