Upgrades content processing from a single LLM call to a structured 5-step document reconstruction pipeline: 1. Normalize — 구어체 정제, 문장부호 복원, 핵심 엔티티 추출 2. Index Tree — 텍스트 전체 스캔 → 계층적 목차(JSON) 생성 3. Leaf Summarize — 섹션별 상세 요약 (context overlap 300자 적용) 4. Consistency Check — 누락 엔티티 검증 및 보완 5. Assemble — 최종 Markdown 문서 조립 (LLM 불필요) - Short texts (< 3000 chars): simple 1-pass fallback - Long texts: full pipeline (N+4 LLM calls where N = section count) - worker.py: uses body_md from enricher as Obsidian note body Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
3.6 KiB
3.6 KiB