24 Commits

Author	SHA1	Message	Date
wangdl	e769d67908	fix(M-AI-08): export LearningAnalysisSnapshotBuilder from AiJobModule ... Required by LearningAnalysisExecutionRouter in AiRuntimeModule. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 22:12:06 +08:00
wangdl	9cf85023d1	feat(M-AI-08-05): learning analysis projector + atomic idempotency ... - LearningAnalysisProjector: AiLearningAnalysis + WeakPointCandidate + Recommendation - All in one transaction via ProjectionExecutor - Entry idempotency via Artifact check + P2002 fallback - Artifact types: learning_analysis, weak_point, recommendation - Registered in RESULT_PROJECTORS factory Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 21:44:29 +08:00
wangdl	06a0e21bbf	feat(M-AI-08-04): learning analysis validator + engine integration ... - Schema validation: strengths/weaknesses/trends/risks/recommendations limits - Evidence validation: sourceType enum, metricKey required - Business validation: insufficientData confidence cap, evidence-required conclusions - Content safety: medical diagnosis, personality judgment, markdown code blocks - Engine: validate after executor in learning_analysis dispatch Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 21:43:15 +08:00
wangdl	1bb131a1bc	feat(M-AI-08-03): learning analysis prompt + schema + executor + engine dispatch ... Resolves A1/A2: learning-analysis prompt and Zod output schema created. - Prompt: 6 analysis dimensions, evidence-required, no medical diagnosis - Schema: strengths/weaknesses/trends/risks/recommendations with evidenceRefs - Executor: AiGateway only, constructs user message from snapshot metrics - Engine dispatch for learning_analysis job type Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 21:41:25 +08:00
wangdl	d537ff3bd0	feat(M-AI-08-02): learning analysis snapshot builder + definition ... - LearningAnalysisSnapshotBuilder: aggregates 6 data dimensions from trusted server sources - Windows: behavior 7 days / scores 30 days (matches legacy) - Data quality: availableSources/missingSources/insufficientDataReasons - Definition: learning_analysis, ai-background, primary tier - contentHash: stable via sorted keys + SHA-256 Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 21:36:57 +08:00
wangdl	452144d9c0	fix: export QuizGenerationSnapshotBuilder from AiJobModule ... Required by QuizExecutionRouter in AiRuntimeModule (forwardRef context). Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 21:12:15 +08:00
wangdl	89ad00b4ee	fix: bidirectional forwardRef for AiRuntimeModule <-> AiJobModule ... Both sides of the circular dependency need forwardRef(). AiJobModule's import of AiRuntimeModule also wrapped. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 21:10:16 +08:00
wangdl	a59446266a	feat(M-AI-07-04): quiz generation Projector + atomic idempotency ... - QuizGenerationProjector: Quiz + QuizQuestion x N + Artifact in one tx - Entry idempotency via Artifact check + P2002 fallback - Quiz fields: sourceType=ai, sourceId=job.id, status=ready - Invalid questions filtered (missing stem/answer) - Registered in RESULT_PROJECTORS factory Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 20:43:55 +08:00
wangdl	d368f1a97f	feat(M-AI-07-03): quiz generation Executor + Validator + prompt/schema ... Resolves A1/A2: bring quiz prompt + output schema in-house from Runtime. - quiz-generation.prompt.ts: system prompt with question design principles - quiz-generation.schema.ts: Zod schema (choice/fill/judge types) - Registered in PromptTemplateService with key 'quiz-generation' v1.0.0 - Executor: AiGateway call with knowledge items + generation params - Validator: per-type validation (choice options/index, judge true/false) - Engine dispatch for quiz_generation job type Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 20:40:12 +08:00
wangdl	9cac4781bd	feat(M-AI-07-02): quiz generation Job Definition + Snapshot Builder ... - quiz_generation Definition: ai-interactive, primary tier, 180s timeout - Snapshot Builder: KB ownership validation, content truncation (2k chars) - Parameter normalization: questionCount [1,50], types, difficulty - Stable contentHash via sorted keys + SHA256 Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 20:34:33 +08:00
wangdl	f1e529b99e	feat: M-AI-06 Feynman ReviewCard Child Job 与可靠生成 ... 完成 M-AI-06 全部 7 个 Issue： - 01: 审计冻结契约 (docs/architecture/m-ai-06-review-card-child-job-contract.md) - 02: AiJobCreationService.createInTransaction(tx, input) - 03: ReviewCard Generation Job Definition + Snapshot Builder - 04: ReviewCard Generation Executor + 输出验证 Validator - 05: ReviewCard Generation Projector + 卡片幂等 + Engine 接入 - 06: FeynmanProjector 接入 FEYNMAN_REVIEW_CARD_MODE Feature Flag - 07: E2E 测试 (test/m-ai-06-review-card-child.e2e-spec.ts) 核心变更： - 新增 10 个文件, 修改 7 个文件 - 新增 createInTransaction() 外部事务支持 - 新增 review_card_generation Job Type (ai-background / cheap tier) - FeynmanProjector 根据 Feature Flag 路由 child_job / legacy_event - Projector 入口幂等 + P2002 回退双重保障 - 测试: 单元 482 passed, E2E 待 CI 执行 Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-22 19:27:14 +08:00
wangdl	8987598eb8	feat(M-AI-05): track Feynman unified engine migration implementation ... 23 files (+4676/-10): - Contract: m-ai-05-feynman-migration-contract.md (737 lines) - Gate audit: m-ai-05-gate-audit.md (318 lines) - Job Definition + Snapshot Builder + Registration - Executor + BusinessValidator + ReferenceValidator - Projector (atomic transaction + 3-layer idempotency) - ExecutionRouter (FeatureFlag + idempotencyKey) - ObservabilityService (structured logging + counters) - Engine: feynman_evaluation execution branch - AiJobCreationService: feynman_evaluation safety branch - Controller/Module: Router injection - CI: path detection for m-ai-05 - E2E: 8 HTTP-layer scenarios (14 total) - Unit tests: 104 new tests (5 spec files) Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 17:44:58 +08:00
wangdl	0ec58669dd	feat(M-AI-04): Active Recall 端到端迁移至统一 Job Engine ... M-AI-04-01: 审计并冻结迁移契约 (文档) M-AI-04-02: 注册 JobDefinition + SnapshotBuilder (28 tests) M-AI-04-03: Executor + BusinessValidator + ReferenceValidator (31 tests) M-AI-04-04: Projector + Artifact + 幂等写入 (19 tests) M-AI-04-05: 入口集成 (Router + CreationService + Engine + Executor) M-AI-04-06: 状态兼容 + 结构化日志 + 指标计数器 (255 tests) M-AI-04-07: 真实业务 E2E + CI 触发 + FeatureFlag 受控切换 (11 tests) P0 修复: - 跨用户 question 所有权校验 (active-recall.service.ts) - E2E infra 不可用时 HARD FAIL (fail() 替代静默 skip) 添加文件: - docs/architecture/m-ai-04-active-recall-migration-contract.md - 12 个 ai-job 模块文件 (Definition/Snapshot/Executor/Validator/Projector/Router/Observability) - test/m-ai-04-active-recall.e2e-spec.ts + setup 修改文件: - active-recall.service.ts, active-recall.module.ts - ai-job-creation.service.ts, ai-job-execution-engine.ts, ai-job.module.ts - .gitea/workflows/deploy.yml (CI 变更检测) - test/jest-e2e.json (setupFiles + globals) Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 14:55:33 +08:00
wangdl	bbac2e358c	fix: use useFactory returning array + Array.isArray guard for RESULT_PROJECTORS ... Two changes to fix 'projectors is not iterable' TypeError: 1. ai-job.module.ts: Replace useClass+multi:true with useFactory that explicitly returns [p] — avoids NestJS multi-provider array-wrapping ambiguity. SyntheticResultProjector back as standalone provider. 2. projection-executor.service.ts: Replace truthiness check with Array.isArray() guard for defense-in-depth. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 12:16:40 +08:00
wangdl	5b0d105788	fix: use useClass instead of useFactory for RESULT_PROJECTORS multi-provider ... The useFactory pattern returned the SyntheticResultProjector object directly but NestJS multi-provider resolution didn't wrap it in an array, causing 'projectors is not iterable' in ProjectionExecutor. useClass is the standard NestJS pattern for registering a class as a multi-provider element. Also removed the redundant standalone SyntheticResultProjector provider since useClass handles instantiation internally. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 12:00:27 +08:00
wangdl	7f326b078a	fix: register SyntheticResultProjector in AiJobModule providers ... RESULT_PROJECTORS factory injects SyntheticResultProjector but it wasn't registered as a provider, causing NestJS DI resolution to fail at module compilation. Added it to providers array — has zero dependencies, so just needs registration. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 11:56:50 +08:00
wangdl	2cf9579935	feat: M-AI-03 Synthetic Job Definition + 环境门控 + 测试 ... - synthetic-job-definition.ts: SyntheticDefinition + isSyntheticEnabled() + assertNotProduction() - synthetic-registration.service.ts: onModuleInit 条件注册（仅 test+SYNTHETIC_ENABLED） - synthetic-job-definition.spec.ts: 13 测试（环境门控/Definition 合法性/Registry） Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 10:11:16 +08:00
wangdl	c91a290536	feat: M-AI-03 Job 查询/取消/Admin/可观测性 ... - AiJobController: GET /api/ai/jobs/:jobId, POST /cancel（JWT 用户隔离） - 公开响应不含 validatedOutput/internalErrorMessage/Snapshot/Credential - 终态取消幂等返回 - AiJobAdminController: Admin 列表/详情/重试/队列状态/Outbox 状态 - 重试：创建新 Job + parentJobId + 复制 Snapshot + OutboxEvent - AiJobService: 用户/Admin 共享业务逻辑 - WorkerHeartbeat: activeJobCount 改为真实活跃数（ai-interactive + ai-background） Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 10:08:57 +08:00
wangdl	4cfcb7afe5	feat: M-AI-03 Result Projector 与 Artifact 原子提交框架 ... - result-projector.interface.ts: ResultProjector 接口冻结（ADR-003 §6.1） project(tx, context) → ArtifactReference[] - synthetic-result-projector.ts: 测试用 Synthetic Projector 幂等：已有 Artifact 时直接返回 - projection-executor.service.ts: ProjectionExecutor 事务内：projector.project(tx) + markSucceeded(tx) 原子提交 幂等检查：Job 已终态 → 跳过 NestJS multi-provider 注入 RESULT_PROJECTORS - ai-job-execution-engine.ts: PROJECT 阶段改为调用 ProjectionExecutor - ai-job.module.ts: 注册 ProjectionExecutor + SyntheticResultProjector Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-21 09:49:25 +08:00
wangdl	d82ae8ba71	feat: M-AI-03 统一 AiJob Worker Execution Engine ... - AiJobExecutionEngineImpl: 完整 5 阶段管线 PREPARE: read Job → terminal check → cancel check → Registry.get → CAS lockJob RESOLVE: load Snapshot → schemaVersion check → AbortController timeout EXECUTE: AiGatewayService.generate() (不直接导入 Provider SDK) PROJECT: write validatedOutput + outputHash (#292 替换为 Projector) COMPLETE: usageLog → markSucceeded - 错误分类: classifyError() — 7 种错误码, retryable/permanent 分流 provider_rate_limited/timeout/unavailable → retryable → 抛给 BullMQ schema/business/reference validation → permanent → markFailed cancelled → markCancelled (3 个检查点: 执行前/Provider前/Projector前) - Usage logging: 每次 Provider 调用写 AiUsageLog (jobId/attemptNo/credentialMode/token) - AiJobModule: 使用 AI_JOB_EXECUTION_ENGINE token 注册，替换 #288 的 no-op - 10 个单元测试: 全链路成功/终态跳过/取消(2)/错误分类(3)/锁冲突/Schema不兼容/UsageLog Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-20 18:30:02 +08:00
wangdl	6668bba9b4	feat: M-AI-03 Outbox Dispatcher — 可靠投递 ai.job.enqueue 到 BullMQ ... - OutboxDispatcher: 每 5s 轮询 OutboxEvent 表，CAS 领取 → 验证 → BullMQ 投递 → 标记 published - 采用 ADR-003 §4.3 先 CAS 后投递算法：markProcessing(CAS) → queue.add() → markPublished - BullMQ jobId = AiJob.id（幂等重复 add） - 崩溃窗口保护：bullmq jobId 幂等 + releaseExpiredLocks(60s) - 错误处理：永久失败（未知eventType/Job不存在/非法queueName/超过最大尝试） vs 暂时失败（exponential backoff 回退 pending） - 仅在 WorkerModule 注册（API 进程不运行 Dispatcher） Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-20 18:20:22 +08:00
wangdl	f0183c03c4	feat: M-AI-03 事务化 AiJob 创建、Snapshot 与 Enqueue Outbox ... - AiJobCreationService: 在一个 Prisma Transaction 内原子创建 Job+Snapshot+Outbox - 幂等性: (userId, jobType, idempotencyKey) UNIQUE 约束防重复 - Job 元数据从 JobDefinition 写入 (queueName/priority/maxAttempts/timeoutMs 等) - overrides 支持覆盖 priority/credentialMode/credentialId - Outbox payload 仅含 {jobId}，不含 userId/credentialId/snapshot - 依赖 SnapshotBuilderService + OutboxRepository，AiJobModule 导入 AiRuntimeModule Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-20 18:13:15 +08:00
wangdl	e4b922e7e4	feat: M-AI-03 Job Definition Registry 与注册校验 ... - JobDefinition 接口冻结（job-definition.types.ts）：对齐 ADR-003 §2.1， 涵盖 queue/execution/input/output/prompt/model/credential/security - JobDefinitionRegistry：启动时注册、运行时只读、Object.freeze 防篡改 - 10 类校验错误：DuplicateJobType/UnknownJobType/InvalidJobType/ InvalidQueueName/MissingSchema/InvalidTimeout/InvalidRetries/ InvalidCredentialMode/InvalidPromptKey/MissingBackoff - 43 个单元测试覆盖所有校验路径 + 顺序稳定性 + 禁止覆盖 - 更新 AiJobModule 注册新 Provider Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-20 17:24:57 +08:00
wangdl	b08d27a449	feat: M-AI-03 AiJob 状态机与原子状态仓储 ... - AiJobStateMachine: 5 状态（queued/running/succeeded/failed/cancelled）、 合法/非法迁移验证、终态判断、双向 Shadow Write 映射 - AiJobLifecycleRepository: 唯一 lifecycleStatus 写入入口、 CAS（条件 UPDATE WHERE lifecycleStatus IN (...)）抢锁/续锁/标记成功/失败/取消、 可选 tx 参数支持 Projector 事务内调用 - requestCancellation: queued 直接取消 → cancelled、 running 设置 cancelRequestedAt 信号 - 6 个类型化错误（JobLockConflict/JobNotActive/JobAlreadyTerminal/ JobNotCancellable/JobExtendLock/IllegalStateTransition） - 41 个单元测试全部通过 Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-20 17:17:12 +08:00