KyeongminandClaude Opus 4.8
b836e79ee1
- src: phase_z2 composition/mapper/pipeline/placement_planner/retry, ai_fallback(prompts/schema/validate), mdx_text_atoms 신규 - Front: PipelineTracePanel 신규, FramePanel/SlideCanvas/Home/designAgentApi 등 갱신 + 테스트 4종 추가 - templates/phase_z2: catalog(component_expansion_registry, node_slot_mapping 신규), frames, families, slide_base 갱신 - tests/matching: phase2~26 매칭 실험 스크립트·리포트·온톨로지 전체 (미커밋 진행분) - tests: b4_v4 evidence, task5~28.5 시리즈, regression(imp95 baseline) 등 신규 테스트 대량 추가 - docs/reference: MDX 구조 인벤토리, MDX→Frame 구조 계약 문서 - scripts: mdx 계약/parity/coverage/viewport 체크, gitea comment, run sync 유틸 - .gitignore: tmp*.json, chromedriver, .orchestrator, *.pkl, Front_test* 등 임시/스냅샷 제외 미완성 작업의 보존용 스냅샷 커밋 (2026-07-02) Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
200 lines
8.2 KiB
Python
200 lines
8.2 KiB
Python
"""CASE 1 (균등 가중) + CASE 2 (계층 가중) 매트릭스 생성.
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각 유닛별 Top-3을 PNG + 점수로 표시."""
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import sys
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import json
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import yaml
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent))
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from common import load_figma_texts
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from extract_units import extract_units
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from methods import (
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method_tfidf, method_bm25, method_char_ngram,
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method_kiwi_bm25, method_structural,
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method_ai_metadata_matcher,
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method_hybrid_kiwi_char,
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method_tfidf_weighted, method_bm25_weighted,
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method_char_ngram_weighted, method_kiwi_bm25_weighted,
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method_hybrid_kiwi_char_weighted,
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)
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ROOT = Path(r"d:\ad-hoc\kei\design_agent")
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PREVIEW_DIR = ROOT / "data" / "figma_previews"
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UNIT_ORDER = [
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("MDX01-intro", "중목차 앞 본문"),
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("MDX01-intro-details", "팝업"),
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("MDX01-1", "중목차"),
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("MDX01-2", "중목차"),
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("MDX01-2-image", "이미지"),
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("MDX01-2-details", "팝업+표"),
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("MDX02-1", "중목차"),
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("MDX02-1-image", "이미지"),
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("MDX02-2", "중목차(컨테이너)"),
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("MDX02-2.1", "소목차"),
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("MDX02-2.2", "소목차"),
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("MDX02-2.2-table", "표"),
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("MDX03-1", "중목차"),
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("MDX03-2", "중목차(컨테이너)"),
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("MDX03-2.1", "소목차"),
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("MDX03-2.1-table", "표"),
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("MDX03-2.2", "소목차"),
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]
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def fmt_score(score, method_name):
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if method_name in ("TF-IDF", "Char-ngram", "AI-Meta", "Structural", "하이브리드"):
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return f"{score * 100:.0f}%"
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else:
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return f"{score:.1f}"
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def get_preview_cell(fid, short_to_info, png_rel_prefix):
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"""프레임 번호 → PNG 썸네일 + 제목 셀"""
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short = fid
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info = short_to_info.get(short, {})
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title = info.get("title_text", "").strip().replace("\n", " ") or ""
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if len(title) > 20:
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title = title[:20] + "…"
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png_rel = f"{png_rel_prefix}{info.get('png', '')}"
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return f"<br>**{short}**<br>{title}"
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def generate_report(case_name, case_desc, methods_def, units, figma, idx_data,
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short_to_info, frame_to_short, metadata_db, extra_meta,
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out_path, png_rel_prefix):
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# 실행
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results = {}
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for uid, unit_text in units.items():
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results[uid] = {}
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for mname, fn in methods_def:
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if not unit_text.strip():
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results[uid][mname] = []
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continue
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if mname == "AI-Meta":
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ranked = method_ai_metadata_matcher(
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uid, metadata_db["figma_frames"],
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{**metadata_db.get("mdx_sections", {}), **extra_meta}
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)
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else:
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ranked = fn(unit_text, figma)
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results[uid][mname] = ranked[:3]
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# 리포트 작성
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lines = []
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lines.append(f"# {case_name}")
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lines.append("")
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lines.append(case_desc)
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lines.append("")
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for i, (uid, kind) in enumerate(UNIT_ORDER, 1):
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lines.append(f"---")
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lines.append("")
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lines.append(f"## {i}. {uid} ({kind})")
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lines.append("")
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# 각 방법별 Top-3 표
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lines.append("| 방법 | 1순위 | 2순위 | 3순위 |")
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lines.append("|------|-------|-------|-------|")
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for mname, _ in methods_def:
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cells = [mname]
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top3 = results[uid].get(mname, [])
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if not top3:
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cells.append("(결과 없음)")
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cells.append("-")
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cells.append("-")
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else:
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for fid, score in top3:
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short = frame_to_short.get(str(fid), "?")
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info = short_to_info.get(short, {})
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png_file = info.get("png", "")
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title = info.get("title_text", "").strip().replace("\n", " ") or ""
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if len(title) > 15:
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title = title[:15] + "…"
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png_rel = f"{png_rel_prefix}{png_file}"
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cell = f"<br>**{short}** ({fmt_score(score, mname)})<br>{title}"
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cells.append(cell)
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while len(cells) < 4:
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cells.append("-")
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lines.append("| " + " | ".join(cells) + " |")
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lines.append("")
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out_path.write_text("\n".join(lines), encoding="utf-8")
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print(f"완료: {out_path}")
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def main():
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figma = load_figma_texts()
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units = extract_units()
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with open(PREVIEW_DIR / "index.json", encoding="utf-8") as f:
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idx_data = json.load(f)
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frame_to_short = {info["frame_id"]: sid for sid, info in idx_data.items()}
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short_to_info = idx_data
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with open(Path(__file__).parent / "metadata_db.yaml", encoding="utf-8") as f:
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metadata_db = yaml.safe_load(f)
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# extra concepts for 17 units
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extra_meta = {
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"MDX01-intro-details": {"concepts": ["정책", "디지털화", "BIM", "스마트건설", "사례"], "layout_hint": "popup-list"},
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"MDX01-2-image": {"concepts": ["DX", "핵심기술", "상호관계", "GIS", "BIM", "디지털트윈"], "layout_hint": "diagram"},
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"MDX01-2-details": {"concepts": ["BIM", "DX", "비교", "범위", "S/W", "프로세스", "성과품", "활용", "확장성", "수행개념", "CIVIL", "IT", "주체", "발주처", "설계사", "시공사"], "layout_hint": "compare-rows"},
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"MDX02-1-image": {"concepts": ["DX", "목표", "안전", "품질", "생산성", "소통", "신뢰"], "layout_hint": "cycle-3way"},
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"MDX02-2.1": {"concepts": ["Process", "변화", "수작업", "S/W", "체계화", "2D", "3D", "협업", "검증", "사전"], "layout_hint": "transition-list"},
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"MDX02-2.2": {"concepts": ["발주자", "시공자", "설계자", "역량", "기대효과", "3D모델", "협업", "Claim", "리스크", "품질"], "layout_hint": "persona-3col"},
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"MDX02-2.2-table": {"concepts": ["발주자", "시공자", "설계자", "필요역량", "업무", "변화", "3D", "검증", "협업", "표"], "layout_hint": "table-3col"},
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"MDX03-2.1": {"concepts": ["Process", "Analogue", "Digital", "혁신", "GIS", "BIM", "Solution", "2D", "3D", "협업"], "layout_hint": "compare-2col"},
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"MDX03-2.1-table": {"concepts": ["Analogue", "Digital", "As-is", "To-be", "2D", "3D", "문서", "행정", "시각화", "소통", "표"], "layout_hint": "compare-2col"},
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"MDX03-2.2": {"concepts": ["Product", "결과", "성과물", "품질", "Digital", "정보물", "Solution", "협업", "통합관리"], "layout_hint": "compare-2col"},
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}
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png_rel = "../../data/figma_previews/"
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# ═══ CASE 1: 균등 가중 ═══
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case1_methods = [
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("TF-IDF", method_tfidf),
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("BM25", method_bm25),
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("Char-ngram", method_char_ngram),
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("Kiwi+BM25", method_kiwi_bm25),
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("Structural", method_structural),
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("AI-Meta", None),
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("하이브리드", method_hybrid_kiwi_char),
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]
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generate_report(
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case_name="CASE 1 — 균등 가중 매칭",
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case_desc="전체 텍스트(블릿 포함)를 동일 가중치로 토큰화. 하이브리드 = Kiwi+BM25 × 0.5 + Char n-gram × 0.5",
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methods_def=case1_methods,
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units=units, figma=figma, idx_data=idx_data,
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short_to_info=short_to_info, frame_to_short=frame_to_short,
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metadata_db=metadata_db, extra_meta=extra_meta,
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out_path=Path(__file__).parent / "MATRIX_CASE1.md",
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png_rel_prefix=png_rel,
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)
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# ═══ CASE 2: 계층 가중 ═══
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case2_methods = [
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("TF-IDF", method_tfidf_weighted),
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("BM25", method_bm25_weighted),
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("Char-ngram", method_char_ngram_weighted),
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("Kiwi+BM25", method_kiwi_bm25_weighted),
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("Structural", method_structural),
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("AI-Meta", None),
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("하이브리드", method_hybrid_kiwi_char_weighted),
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]
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generate_report(
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case_name="CASE 2 — 계층 가중 매칭",
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case_desc="중목차(##) ×3, 소목차(###) ×3, 굵은 글씨 라벨(**xx**) ×2 가중 토큰화. 하이브리드 = 가중 Kiwi+BM25 × 0.5 + 가중 Char n-gram × 0.5",
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methods_def=case2_methods,
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units=units, figma=figma, idx_data=idx_data,
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short_to_info=short_to_info, frame_to_short=frame_to_short,
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metadata_db=metadata_db, extra_meta=extra_meta,
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out_path=Path(__file__).parent / "MATRIX_CASE2.md",
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png_rel_prefix=png_rel,
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)
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if __name__ == "__main__":
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main()
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