docs(14-03): complete semantic cache implementation plan

- Created SUMMARY.md with implementation details
- Updated STATE.md with new decisions and session info
- Updated ROADMAP.md progress (1/6 plans complete)
- Marked COST-02 requirement complete

Duration: 1 min (72s)
Tasks: 1 (TDD: RED → GREEN)
Tests: 11 passed

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

.planning/REQUIREMENTS.md

@@ -54,7 +54,7 @@
 ### 成本控制 (COST)
 
 - [ ] **COST-01**: 长视频字幕进行分块处理，避免上下文窗口溢出
-- [ ] **COST-02**: 实现智能缓存，相同内容不重复调用 LLM
+- [x] **COST-02**: 实现智能缓存，相同内容不重复调用 LLM
 - [ ] **COST-03**: 提供配置开关，用户可选择是否启用 LLM 分段
 
 ### 输出格式 (OUTPUT)
@@ -120,7 +120,7 @@
 | ROBUST-03 | Phase 14 | Pending |
 | ROBUST-04 | Phase 14 | Pending |
 | COST-01 | Phase 14 | Pending |
-| COST-02 | Phase 14 | Pending |
+| COST-02 | Phase 14 | Complete |
 | COST-03 | Phase 14 | Pending |
 | OUTPUT-01 | Phase 15 | Pending |
 | OUTPUT-02 | Phase 15 | Pending |

.planning/ROADMAP.md

@@ -233,7 +233,7 @@ Phases execute in numeric order: 1 → 2 → ... → 12 → 13 → 14 → 15
 | 11. Stealth Fingerprinting | v1.4 | 2/2 | Complete | 2026-03-18 |
 | 12. SRT 简化处理器 | v1.5 | 2/2 | Complete | 2026-03-21 |
 | 13. 核心 LLM 分段功能 | 6/7 | Complete    | 2026-03-21 | - |
-| 14. 鲁棒性与成本控制 | v1.6 | 0/6 | Draft | 2026-03-23 |
+| 14. 鲁棒性与成本控制 | 1/6 | In Progress|  | 2026-03-23 |
 | 15. 输出优化与兼容性 | v1.6 | 0/0 | Not started | - |
 
 ---

.planning/STATE.md

@@ -3,14 +3,14 @@ gsd_state_version: 1.0
 milestone: v1.4
 milestone_name: Zhihu Anti-Crawler
 status: executing
-stopped_at: Phase 14 context gathered
+stopped_at: Completed 14-03-PLAN.md
-last_updated: "2026-03-23T12:51:30.858Z"
+last_updated: "2026-03-23T14:36:46.811Z"
 last_activity: 2026-03-22 — Phase 13 Plan 07 completed (SRTProcessor integration)
 progress:
   total_phases: 15
   completed_phases: 11
-  total_plans: 38
+  total_plans: 44
-  completed_plans: 37
+  completed_plans: 38
   percent: 31
 ---
 
@@ -84,6 +84,9 @@ v1.6 Phase 13 decisions (from 13-CONTEXT.md):
 - [Phase 13]: Strategy Pattern with Protocol interface for extensibility (STRAT-01)
 - [Phase 13]: Unified segmentation strategy for all video types (per user decision, STRAT-02)
 - [Phase 13]: Strategy injection via constructor for easy testing and extension (STRAT-03)
+- [Phase 14-robustness-cost]: 缓存键使用 SHA256 内容哈希，确保相同内容精确匹配
+- [Phase 14-robustness-cost]: 缓存文件包含 version 字段（1.0），支持未来格式变更
+- [Phase 14-robustness-cost]: 缓存失败时返回 None，不中断主流程（错误容错）
 
 ### Technical Context
 
@@ -132,12 +135,13 @@ None.
 | 13 | 05 | 2min | 1 | 2 | 2026-03-22 |
 | 13 | 06 | 12min | 1 | 2 | 2026-03-22 |
 | 13 | 07 | 4min | 1 | 4 | 2026-03-22 |
+| Phase 14-robustness-cost P03 | 72 | 1 tasks | 3 files |
 
 ## Session Continuity
 
-Last session: 2026-03-23T12:51:30.856Z
+Last session: 2026-03-23T14:36:46.809Z
-Stopped at: Phase 14 context gathered
+Stopped at: Completed 14-03-PLAN.md
-Resume file: .planning/phases/14-robustness-cost/14-CONTEXT.md
+Resume file: None
 
 **Next step:** Phase 13 complete, continue to Phase 14 (鲁棒性) or Phase 15 (优化)
 

.planning/phases/14-robustness-cost/14-03-SUMMARY.md

@@ -0,0 +1,200 @@
+---
+phase: 14-robustness-cost
+plan: 03
+subsystem: caching
+tags: [cache, sha256, content-hashing, llm-optimization]
+
+# Dependency graph
+requires:
+  - phase: 13-llm
+    provides: SemanticSegmentationEngine, SegmentationResult, VideoSegment
+provides:
+  - SemanticCache 缓存管理器
+  - compute_content_hash() 内容哈希函数
+  - 缓存目录结构 (.planning/cache/semantic/)
+affects: [14-04, 14-05, semantic-segmentation]
+
+# Tech tracking
+tech-stack:
+  added: [hashlib, json, pathlib]
+  patterns: [content-based-caching, versioned-cache-format, error-tolerant-cache]
+
+key-files:
+  created:
+    - kb_workflow/srt/cache/semantic_cache.py
+    - kb_workflow/srt/cache/__init__.py
+    - tests/test_semantic_robustness.py
+  modified: []
+
+key-decisions:
+  - "缓存键使用 SHA256 内容哈希，确保相同内容精确匹配"
+  - "缓存文件包含 version 字段（1.0），支持未来格式变更"
+  - "缓存失败时返回 None，不中断主流程（错误容错）"
+
+patterns-established:
+  - "Pattern: Content-based caching - 使用内容哈希而非 ID 作为缓存键"
+  - "Pattern: Versioned cache format - 缓存数据包含版本号便于迁移"
+  - "Pattern: Error-tolerant cache - 缓存读写失败时降级，不影响核心功能"
+
+requirements-completed: [COST-02]
+
+# Metrics
+duration: 1min
+completed: 2026-03-23
+---
+
+# Phase 14: 鲁棒性与成本控制 - Plan 03 Summary
+
+**基于 SHA256 内容哈希的智能缓存系统，避免重复 LLM 调用，降低 API 成本和延迟**
+
+## Performance
+
+- **Duration:** 1 min (72s)
+- **Started:** 2026-03-23T14:34:58Z
+- **Completed:** 2026-03-23T14:36:09Z
+- **Tasks:** 1 (TDD cycle: RED → GREEN)
+- **Files modified:** 3
+
+## Accomplishments
+
+- **SemanticCache 缓存管理器**: 实现完整的读写功能，支持基于内容哈希的缓存
+- **SHA256 哈希函数**: `compute_content_hash()` 生成 64 字符十六进制缓存键
+- **版本控制机制**: 缓存文件包含 `version` 字段，支持未来格式变更
+- **错误容错设计**: 缓存读写失败时返回 None，不中断主流程
+- **全面测试覆盖**: 11 个测试用例，覆盖缓存命中/未命中、版本控制、错误处理
+
+## Task Commits
+
+Each task was committed atomically:
+
+1. **Task 1: 创建 SemanticCache 缓存管理器** - TDD Cycle
+   - `b6e923c` (test) - 添加失败的测试用例（RED）
+   - `baf7c0f` (feat) - 实现 SemanticCache 使测试通过（GREEN）
+
+**Plan metadata:** TBD (docs: complete plan)
+
+_Note: TDD tasks followed RED → GREEN flow. No refactoring needed._
+
+## Files Created/Modified
+
+### Created
+
+- `kb_workflow/srt/cache/semantic_cache.py` - 缓存管理器核心实现
+  - `compute_content_hash()`: SHA256 哈希计算
+  - `SemanticCache.get()`: 从缓存读取 SegmentationResult
+  - `SemanticCache.set()`: 保存 SegmentationResult 到缓存
+  - 支持版本控制和错误容错
+
+- `kb_workflow/srt/cache/__init__.py` - 缓存模块导出
+  - 导出 `SemanticCache` 和 `compute_content_hash`
+
+- `tests/test_semantic_robustness.py` - 缓存功能测试套件
+  - `TestComputeContentHash`: 测试哈希计算（3 个测试）
+  - `TestSemanticCache`: 测试缓存功能（8 个测试）
+  - 覆盖：缓存命中/未命中、版本控制、错误处理、多缓存项
+
+### Modified
+
+None
+
+## Decisions Made
+
+所有决策遵守 14-CONTEXT.md 中的用户决策：
+
+1. **缓存键使用 SHA256 内容哈希**
+   - 理由: 精确匹配，相同内容一定命中缓存
+   - 实现: `hashlib.sha256(content.encode('utf-8')).hexdigest()`
+
+2. **缓存存储在本地文件系统**
+   - 理由: 简单持久化，无需外部依赖
+   - 路径: `.planning/cache/semantic/`
+
+3. **缓存 TTL 永久有效**
+   - 理由: 字幕内容不变，分段结果应该一致
+   - 清理: 手动删除缓存文件
+
+4. **缓存包含完整的 SegmentationResult**
+   - 理由: 包含 video_type 和 segments，完整保存 LLM 输出
+   - 格式: JSON + version 字段
+
+5. **错误容错设计**
+   - 理由: 缓存失败不应中断主流程
+   - 实现: 读写失败时返回 None，记录 warning 日志
+
+## Deviations from Plan
+
+None - plan executed exactly as written.
+
+## Issues Encountered
+
+None - implementation proceeded smoothly with TDD approach.
+
+## User Setup Required
+
+None - no external service configuration required.
+
+缓存目录会在首次使用时自动创建：`.planning/cache/semantic/`
+
+## Next Phase Readiness
+
+### Ready for Integration
+
+- ✅ SemanticCache 类已实现并测试
+- ✅ 缓存模块可以导出到其他组件
+- ✅ 错误容错机制已就位
+
+### Integration Points
+
+计划 14-04 和 14-05 可以将 SemanticCache 集成到 UnifiedSegmentationStrategy：
+
+```python
+from kb_workflow.srt.cache import SemanticCache
+
+class UnifiedSegmentationStrategy:
+    def __init__(self, ...):
+        self.cache = SemanticCache()  # 添加缓存层
+
+    def segment(self, segments, metadata):
+        content = " ".join(seg.text for seg in segments)
+
+        # 尝试从缓存读取
+        cached_result = self.cache.get(content)
+        if cached_result:
+            return cached_result.segments
+
+        # 调用 LLM
+        result = self._call_llm(content, metadata)
+
+        # 保存到缓存
+        self.cache.set(content, result)
+
+        return result.segments
+```
+
+### Blockers/Concerns
+
+None.
+
+## Verification
+
+所有测试通过：
+
+```bash
+pytest tests/test_semantic_robustness.py::TestComputeContentHash \
+       tests/test_semantic_robustness.py::TestSemanticCache -v
+```
+
+结果：11 passed in 0.08s
+
+### Success Criteria Met
+
+- ✅ 相同内容第二次调用时从缓存读取
+- ✅ 缓存文件存储在 `.planning/cache/semantic/` 目录
+- ✅ 缓存文件命名格式: `{sha256_hash}.json`
+- ✅ 缓存内容包含完整的 SegmentationResult (JSON 格式)
+- ✅ 缓存命中时记录 debug 级别日志
+- ✅ 所有测试通过 (11/11)
+
+---
+*Phase: 14-robustness-cost*
+*Completed: 2026-03-23*