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>
85 lines
3.0 KiB
Python
85 lines
3.0 KiB
Python
"""IDF-only 매칭: TF 빼고 공통 희귀 단어의 IDF 합으로만 매칭"""
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import sys
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import json
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import math
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from collections import Counter
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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, tokenize_simple
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from extract_units import extract_units
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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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# 전체 corpus IDF
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all_docs = {}
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for uid, text in units.items():
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all_docs[f"MDX:{uid}"] = tokenize_simple(text)
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for fid, text in figma.items():
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all_docs[f"FIG:{fid}"] = tokenize_simple(text)
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df = Counter()
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for toks in all_docs.values():
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for w in set(toks):
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df[w] += 1
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N = len(all_docs)
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idf = {w: math.log(N / c) for w, c in df.items()}
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with open(Path(__file__).parent.parent.parent / "data" / "figma_previews" / "index.json",
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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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def idf_sum_score(query_tokens, doc_tokens, idf_dict):
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"""공통 단어의 IDF 합 (단순)"""
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common = set(query_tokens) & set(doc_tokens)
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return sum(idf_dict.get(w, 0) for w in common)
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def idf_jaccard(query_tokens, doc_tokens, idf_dict):
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"""IDF 가중 Jaccard = IDF(교집합) / IDF(합집합)"""
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q_set = set(query_tokens)
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d_set = set(doc_tokens)
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common = q_set & d_set
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union = q_set | d_set
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num = sum(idf_dict.get(w, 0) for w in common)
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den = sum(idf_dict.get(w, 0) for w in union)
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return num / den if den > 0 else 0
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# 핵심: MDX03-1 테스트
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test_units = ["MDX03-1", "MDX03-2", "MDX01-2", "MDX02-1", "MDX02-2", "MDX01-1"]
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for uid in test_units:
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if uid not in units:
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continue
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print(f"\n═══════════════════════════════════════")
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print(f"{uid}")
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print(f"═══════════════════════════════════════")
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query_toks = tokenize_simple(units[uid])
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# IDF sum
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scores_sum = []
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scores_jac = []
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for fid, text in figma.items():
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doc_toks = tokenize_simple(text)
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scores_sum.append((fid, idf_sum_score(query_toks, doc_toks, idf)))
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scores_jac.append((fid, idf_jaccard(query_toks, doc_toks, idf)))
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scores_sum.sort(key=lambda x: -x[1])
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scores_jac.sort(key=lambda x: -x[1])
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print(f"\n[IDF-Sum] (공통 희귀 단어 IDF 합)")
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for i, (fid, sc) in enumerate(scores_sum[:5], 1):
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short = frame_to_short.get(str(fid), "?")
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print(f" {i}. {short} score={sc:.2f}")
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print(f"\n[IDF-Jaccard] (IDF 가중 Jaccard)")
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for i, (fid, sc) in enumerate(scores_jac[:5], 1):
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short = frame_to_short.get(str(fid), "?")
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print(f" {i}. {short} score={sc:.3f}")
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if __name__ == "__main__":
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main()
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