3b753f18d6
PR-2Q-Search-Result-Dedup. measurement chain 의 마지막 cleanup. plan inline.
root cause: apply_diversity 의 top_score ≥ 0.90 → unlimited path (diversity 제약 해제)
→ 같은 doc 의 N chunks 가 results 에 박제 → returned_ids 에 doc.id 중복 → 모든 graded
metric inflation. multi-query 의 reranker score 가 자주 0.90+ → 다수 case 영향.
변경 (baseline path 영향 0, multi-query 전용 invariant):
- app/services/search/search_pipeline.py:
· _dedup_results_by_doc_id() helper 신규 (doc.id first-only, top score 보존)
· search_with_rewrite() 의 rerank path 에 apply_diversity(top_score_threshold=2.0)
강제 + 후속 _dedup_results_by_doc_id 적용
· rerank=False path 도 _dedup_results_by_doc_id(unified_docs) 적용
- tests/test_query_rewriter.py — 신규 4 test (55/55 PASS)
🎯 진짜 측정값 (모든 dedup layer 적용, 51 case gemma):
cold: NDCG 0.663 / Recall t≥2 0.729 / Recall t≥3 0.761 / p50 3692ms / p95 9992ms
warm: NDCG 0.659 / Recall t≥2 0.721 / Recall t≥3 0.739 / p50 1588ms / p95 3514ms
baseline (rewrite_backend=null): NDCG 0.644 / Recall t≥2 0.699 / Recall t≥3 0.761 / p50 378ms
Dedup audit: gemma 0/51 ✓ 정상 (fix 작동, eval-dedup 42/51 → 0/51 회복)
Δ vs baseline (진짜 multi-query 효과):
NDCG +0.019 (cold) / +0.015 (warm) — sub-noise level
Recall t≥2 +0.030 (cold) / +0.022 (warm) — 소량 개선
Recall t≥3 0.000 / -0.022 — 동등~약간 회귀
latency p50 +876% (cold) / +320% (warm) — major cost
category: english/standards/mixed 약간 우세 / exam/korean 약간 회귀
measurement chain 정정 history:
Phase 3 (a41adb6) 0.927 — chunk_id 중복 inflation
Rerank-Fix (b734fc5) 0.876 — doc_id 중복 잔재
Eval-Dedup (3553573) 0.641 — eval layer 만 dedup
Result-Dedup (본 PR) 0.663 — production + eval 둘 다 dedup ← 정확값
사용자 결정 필요 (3 path, json 박제):
(a) rollback — marginal 개선이 latency cost 정당화 X
(b) opt-in 유지 + PR-2Q-Cache-Prewarm 진입 (warm path 만 노출)
(c) 1주 관찰 종료 후 (2026-05-31) 재결정 (현 상태 유지)
산출물:
reports/v0_2_phase2q_result_dedup_gemma_{cold,warm}_2026-05-24.csv
tests/search_eval/baselines/v0_2_phase2q_result_dedup_2026-05-24.json (요약 + 사용자 결정 옵션)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
562 lines
21 KiB
Python
562 lines
21 KiB
Python
"""Phase 2Q Diagnose Phase 1B — query_rewriter scaffold + dispatcher 단위 테스트.
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가드레일 (plan v6 §5 + §7 Phase 1):
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1. `_resolve_rewrite_backend` — slug resolve, unknown ValueError, baseline → None
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2. `_cache_key` — deterministic + NFKC normalize + backend slug 분리
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3. `_extract_variants` — valid shape / wrong count / type mismatch / empty / non-list
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4. cache set/get/TTL (LRU evict 시뮬레이션)
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5. `allowed_slugs` — LLM_BACKEND_MAP keys 1:1
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"""
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from __future__ import annotations
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import asyncio
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import logging
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import os
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import sys
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import time
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import pytest
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# logs/llm_gate.log 가 root 소유 (운영 fastapi daemon write) → pytest 가 hyungi user 로
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# import 시 PermissionError. 본 test 한정 FileHandler safe-wrap (다른 test 영향 0).
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_orig_file_handler = logging.FileHandler
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def _safe_file_handler(filename, *args, **kwargs): # type: ignore
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try:
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return _orig_file_handler(filename, *args, **kwargs)
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except PermissionError:
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return logging.NullHandler()
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logging.FileHandler = _safe_file_handler # type: ignore[assignment]
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# Phase 2 test (search_pipeline import) 는 api.search → SQLAlchemy engine init 트리거.
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# DATABASE_URL 미설정 시 ArgumentError 로 collection 실패. dummy URL 주입 (실제 connect X).
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os.environ.setdefault("DATABASE_URL", "postgresql+asyncpg://test:test@localhost:5432/test")
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# tests/ → 프로젝트 루트 → app/
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "app"))
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from services.search import query_rewriter
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from services.search.query_rewriter import (
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EXPECTED_N_VARIANTS,
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LLM_BACKEND_MAP,
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PROMPT_VERSION,
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_cache_key,
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_extract_variants,
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_resolve_rewrite_backend,
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allowed_slugs,
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)
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# ─── 1. _resolve_rewrite_backend ──────────────────────────
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def test_resolve_baseline_returns_none():
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assert _resolve_rewrite_backend(None) is None
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assert _resolve_rewrite_backend("baseline") is None
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def test_resolve_known_slugs():
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cfg = _resolve_rewrite_backend("cand_multi_query_macmini")
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assert cfg is not None
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assert "endpoint" in cfg and "model" in cfg and "sampling" in cfg
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assert cfg["model"] == "gemma-4-26b-a4b-it-8bit"
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cfg = _resolve_rewrite_backend("cand_multi_query_macbook")
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assert cfg is not None
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assert cfg["model"] == "mlx-community/Qwen3.6-27B-8bit"
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# qwen sampling 에 response_format 없음 (Phase 0 inspect 9 박제)
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assert "response_format" not in cfg["sampling"]
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def test_resolve_unknown_slug_raises():
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with pytest.raises(ValueError, match="unknown_rewrite_backend"):
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_resolve_rewrite_backend("cand_bogus")
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with pytest.raises(ValueError):
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_resolve_rewrite_backend("cand_multi_query_other")
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def test_allowed_slugs_matches_map():
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assert allowed_slugs() == list(LLM_BACKEND_MAP.keys())
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assert "baseline" in allowed_slugs()
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assert "cand_multi_query_macmini" in allowed_slugs()
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assert "cand_multi_query_macbook" in allowed_slugs()
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# ─── 2. _cache_key ────────────────────────────────────────
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def test_cache_key_deterministic():
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k1 = _cache_key("산업안전보건법 제6장", "cand_multi_query_macmini")
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k2 = _cache_key("산업안전보건법 제6장", "cand_multi_query_macmini")
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assert k1 == k2
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assert len(k1) == 32 # sha256[:32]
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def test_cache_key_nfkc_normalize_and_strip_lower():
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# whitespace + uppercase → 동일 key
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base = _cache_key("ASME Section VIII", "cand_multi_query_macmini")
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assert _cache_key(" asme section viii ", "cand_multi_query_macmini") == base
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assert _cache_key("ASME SECTION VIII", "cand_multi_query_macmini") == base
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def test_cache_key_differs_by_backend_slug():
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k_a = _cache_key("query", "cand_multi_query_macmini")
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k_b = _cache_key("query", "cand_multi_query_macbook")
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assert k_a != k_b
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def test_cache_key_includes_prompt_version():
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# PROMPT_VERSION 변경 시 cache 분리 — 직접 test 어렵지만 raw 구성 확인
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assert PROMPT_VERSION == "v1"
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k = _cache_key("query", "cand_multi_query_macmini")
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assert len(k) == 32
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# ─── 3. _extract_variants ─────────────────────────────────
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def test_extract_variants_valid_shape():
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raw = '{"variants": ["원본", "한국어 변형", "english"]}'
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out = _extract_variants(raw, expected_n=3)
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assert out == ["원본", "한국어 변형", "english"]
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def test_extract_variants_strips_whitespace():
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raw = '{"variants": [" 원본 ", "한국어\\n", " english "]}'
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out = _extract_variants(raw, expected_n=3)
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assert out == ["원본", "한국어", "english"]
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def test_extract_variants_wrong_count_returns_none():
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raw = '{"variants": ["only_one"]}'
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assert _extract_variants(raw, expected_n=3) is None
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raw = '{"variants": ["a", "b", "c", "d"]}'
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assert _extract_variants(raw, expected_n=3) is None
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def test_extract_variants_missing_key_returns_none():
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raw = '{"queries": ["a", "b", "c"]}'
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assert _extract_variants(raw, expected_n=3) is None
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def test_extract_variants_non_list_returns_none():
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raw = '{"variants": "single string"}'
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assert _extract_variants(raw, expected_n=3) is None
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def test_extract_variants_empty_string_returns_none():
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raw = '{"variants": ["a", "", "c"]}'
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assert _extract_variants(raw, expected_n=3) is None
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def test_extract_variants_non_string_element_returns_none():
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raw = '{"variants": ["a", 123, "c"]}'
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assert _extract_variants(raw, expected_n=3) is None
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def test_extract_variants_invalid_json_returns_none():
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raw = "not json at all"
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assert _extract_variants(raw, expected_n=3) is None
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def test_extract_variants_markdown_fence_fallback():
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# parse_json_response 가 ```json fenced 블록 내부 추출 — production parser 재사용 검증
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raw = '```json\n{"variants": ["a", "b", "c"]}\n```'
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out = _extract_variants(raw, expected_n=3)
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assert out == ["a", "b", "c"]
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# ─── 4. cache set / get ───────────────────────────────────
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@pytest.mark.asyncio
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async def test_cache_set_get_roundtrip():
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# 격리: 전역 _CACHE 초기화 (다른 테스트와 격리)
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query_rewriter._CACHE.clear()
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key = _cache_key("__test_unique_key__", "cand_multi_query_macmini")
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assert await query_rewriter._get_cached(key) is None
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await query_rewriter._set_cached(key, ["v0", "v1", "v2"])
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out = await query_rewriter._get_cached(key)
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assert out == ["v0", "v1", "v2"]
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@pytest.mark.asyncio
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async def test_cache_ttl_expiry():
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query_rewriter._CACHE.clear()
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key = "ttl_test_key"
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# manual entry with past expire_at
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query_rewriter._CACHE[key] = (time.time() - 1.0, ["a", "b", "c"])
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assert await query_rewriter._get_cached(key) is None
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# lazy delete verify
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assert key not in query_rewriter._CACHE
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@pytest.mark.asyncio
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async def test_cache_returns_copy_not_reference():
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"""_get_cached 반환 list 를 외부에서 수정해도 internal cache 안전."""
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query_rewriter._CACHE.clear()
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key = "copy_test_key"
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await query_rewriter._set_cached(key, ["a", "b", "c"])
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out = await query_rewriter._get_cached(key)
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out.append("mutated")
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out2 = await query_rewriter._get_cached(key)
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assert out2 == ["a", "b", "c"]
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# ─── 5. constants ─────────────────────────────────────────
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def test_constants_match_plan_v6():
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assert PROMPT_VERSION == "v1"
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assert EXPECTED_N_VARIANTS == 3
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assert query_rewriter.LLM_REWRITE_TIMEOUT_MS == 15000
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assert query_rewriter.CACHE_TTL == 86400
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assert query_rewriter.CACHE_MAXSIZE == 1000
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# ─── 6. Phase 2 — _rrf_fuse_variants 합성 알고리즘 ────────
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def _mk_search_result(doc_id: int, score: float = 1.0, match_reason: str = "test"):
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"""SearchResult 인스턴스 (api.search 의 BaseModel). file_format 은 str 필수."""
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from api.search import SearchResult
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return SearchResult(
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id=doc_id, title=f"doc-{doc_id}", ai_domain=None,
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ai_summary=None, file_format="pdf",
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score=score, snippet=None, match_reason=match_reason,
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)
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def test_rrf_fuse_variants_single_variant_preserves_order():
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from services.search.search_pipeline import _rrf_fuse_variants
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docs = [_mk_search_result(i) for i in (10, 20, 30)]
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out = _rrf_fuse_variants([docs], k=60, limit=10)
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assert [r.id for r in out] == [10, 20, 30]
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# RRF score = 1/(60+1) > 1/(60+2) > 1/(60+3)
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assert out[0].score > out[1].score > out[2].score
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assert "multi_query_rrf" in out[0].match_reason
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def test_rrf_fuse_variants_accumulates_overlapping_doc_ids():
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"""같은 doc_id 가 여러 variant 에서 top rank 면 점수 누적 → 상위."""
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from services.search.search_pipeline import _rrf_fuse_variants
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v1 = [_mk_search_result(i) for i in (10, 20, 30)]
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v2 = [_mk_search_result(i) for i in (40, 10, 50)] # 10 이 두 variant 모두 등장
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out = _rrf_fuse_variants([v1, v2], k=60, limit=10)
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# 10 = 1/61 + 1/62 (rank 1 + rank 2). 다른 doc 은 1 variant 만 → 단일 RRF score.
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ids = [r.id for r in out]
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assert ids[0] == 10 # 누적 점수 최상위
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# 40 (1/61) vs 20 (1/62) — variant 1 에서 rank 1 인 40 이 단일 등장 doc 중 최상위
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assert ids[1] == 40
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assert set(ids) == {10, 20, 30, 40, 50}
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def test_rrf_fuse_variants_first_variant_representative():
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"""같은 doc_id 가 여러 variant 에 있으면 첫 등장 variant 의 SearchResult 보존."""
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from services.search.search_pipeline import _rrf_fuse_variants
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v1 = [_mk_search_result(10, match_reason="from_v1")]
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v2 = [_mk_search_result(10, match_reason="from_v2")]
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out = _rrf_fuse_variants([v1, v2], k=60, limit=10)
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assert len(out) == 1
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assert out[0].id == 10
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assert "from_v1" in out[0].match_reason # 첫 등장 보존
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assert "multi_query_rrf" in out[0].match_reason
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def test_rrf_fuse_variants_respects_limit_cap():
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from services.search.search_pipeline import _rrf_fuse_variants
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v1 = [_mk_search_result(i) for i in range(100, 130)] # 30 docs
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v2 = [_mk_search_result(i) for i in range(200, 230)] # 30 docs, 모두 unique
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out = _rrf_fuse_variants([v1, v2], k=60, limit=5)
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assert len(out) == 5
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def test_rrf_fuse_variants_empty_lists_returns_empty():
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from services.search.search_pipeline import _rrf_fuse_variants
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assert _rrf_fuse_variants([], k=60, limit=10) == []
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assert _rrf_fuse_variants([[], [], []], k=60, limit=10) == []
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def test_rrf_fuse_variants_rank_position_matters():
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"""variant 가 길어져도 RRF 공식이 rank 만 사용."""
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from services.search.search_pipeline import _rrf_fuse_variants
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v1 = [_mk_search_result(10)] # rank 1
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v2 = [_mk_search_result(99), _mk_search_result(10)] # 10 이 rank 2
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out = _rrf_fuse_variants([v1, v2], k=60, limit=10)
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# 10 = 1/61 + 1/62, 99 = 1/61. 둘 다 등장 doc 중 10 점수 높음.
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assert out[0].id == 10
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assert out[1].id == 99
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# ─── 7. Phase 2 — search_pipeline import + run_search signature ───
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def test_search_pipeline_imports_query_rewriter():
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"""search_pipeline 이 query_rewriter 를 import 하는지 (dispatch 분기 활성)."""
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from services.search import search_pipeline
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assert hasattr(search_pipeline, "query_rewriter")
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assert hasattr(search_pipeline, "search_with_rewrite")
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assert hasattr(search_pipeline, "_rrf_fuse_variants")
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def test_run_search_has_rewrite_backend_param():
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"""run_search signature 에 rewrite_backend 가 추가됐는지."""
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import inspect
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from services.search.search_pipeline import run_search
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sig = inspect.signature(run_search)
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assert "rewrite_backend" in sig.parameters
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# default = None (baseline 회귀 0 invariant)
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assert sig.parameters["rewrite_backend"].default is None
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def test_phase2q_constants():
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"""plan v6 §5.5 박제값."""
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from services.search.search_pipeline import (
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PHASE2Q_PRODUCTION_TOPK,
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PHASE2Q_RRF_K,
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PHASE2Q_UNIFIED_CAP,
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)
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assert PHASE2Q_PRODUCTION_TOPK == 50
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assert PHASE2Q_RRF_K == 60
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assert PHASE2Q_UNIFIED_CAP == 60
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# per-variant K = 50 // 3 = 16 (A1 채택)
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assert PHASE2Q_PRODUCTION_TOPK // EXPECTED_N_VARIANTS == 16
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# ─── 8. Phase 3 incident regression — fixture-first call shape ───
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# Phase 3 cold 측정에서 NDCG 0.033 catastrophic 발견 → variants 가 query 무관 동일 응답.
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# root cause = _call_llm 이 user 메시지 1개에 prompt template 전체 박음. fixture 의 정확한
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# request_body 는 system=prompt / user=query 분리. fixture-first invariant 위반.
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# 본 test 는 호출 형식이 fixture 와 일치하는지 verify (regression 방지).
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@pytest.mark.asyncio
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async def test_call_llm_uses_system_user_message_split(monkeypatch):
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"""_call_llm 이 fixture 의 request_body 형식 (system=prompt / user=query) 으로 호출하는지."""
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captured = {}
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class _MockResponse:
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def raise_for_status(self):
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return None
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def json(self):
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return {"choices": [{"message": {"content": '{"variants": ["a", "b", "c"]}'}}]}
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class _MockClient:
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def __init__(self, *args, **kwargs):
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pass
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|
|
|
async def __aenter__(self):
|
|
return self
|
|
|
|
async def __aexit__(self, *args):
|
|
return None
|
|
|
|
async def post(self, url, json):
|
|
captured["url"] = url
|
|
captured["payload"] = json
|
|
return _MockResponse()
|
|
|
|
monkeypatch.setattr(query_rewriter.httpx, "AsyncClient", _MockClient)
|
|
|
|
cfg = query_rewriter.LLM_BACKEND_MAP["cand_multi_query_macmini"]
|
|
raw = await query_rewriter._call_llm(cfg, "LPG 저장탱크 안전거리")
|
|
|
|
# raw 응답 정상
|
|
assert "variants" in raw
|
|
|
|
# endpoint = cfg endpoint 사용
|
|
assert captured["url"] == cfg["endpoint"]
|
|
|
|
payload = captured["payload"]
|
|
# model = cfg model
|
|
assert payload["model"] == cfg["model"]
|
|
|
|
# messages = 2 entry, system + user 분리
|
|
messages = payload["messages"]
|
|
assert len(messages) == 2
|
|
assert messages[0]["role"] == "system"
|
|
assert messages[1]["role"] == "user"
|
|
|
|
# user 메시지 = query verbatim (prompt template 안 박힘)
|
|
assert messages[1]["content"] == "LPG 저장탱크 안전거리"
|
|
|
|
# system 메시지 = prompt template (instruction). query 본문은 포함되지 않음.
|
|
assert "LPG 저장탱크 안전거리" not in messages[0]["content"]
|
|
assert "search query rewriter" in messages[0]["content"].lower()
|
|
|
|
# sampling 박제 적용 (gemma → response_format json_object)
|
|
assert payload["temperature"] == 0.3
|
|
assert payload["max_tokens"] == 256
|
|
assert payload.get("response_format") == {"type": "json_object"}
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_call_llm_qwen_no_response_format(monkeypatch):
|
|
"""qwen backend = response_format 미사용 (mlx-vlm.server 미지원, Phase 0 inspect 9 박제)."""
|
|
captured = {}
|
|
|
|
class _MockResponse:
|
|
def raise_for_status(self):
|
|
return None
|
|
def json(self):
|
|
return {"choices": [{"message": {"content": '{"variants": ["a", "b", "c"]}'}}]}
|
|
|
|
class _MockClient:
|
|
def __init__(self, *args, **kwargs):
|
|
pass
|
|
async def __aenter__(self):
|
|
return self
|
|
async def __aexit__(self, *args):
|
|
return None
|
|
async def post(self, url, json):
|
|
captured["payload"] = json
|
|
return _MockResponse()
|
|
|
|
monkeypatch.setattr(query_rewriter.httpx, "AsyncClient", _MockClient)
|
|
|
|
cfg = query_rewriter.LLM_BACKEND_MAP["cand_multi_query_macbook"]
|
|
await query_rewriter._call_llm(cfg, "ASME Section VIII")
|
|
|
|
payload = captured["payload"]
|
|
# qwen 은 response_format 박제 0 (prompt rule 만)
|
|
assert "response_format" not in payload
|
|
|
|
|
|
# ─── 9. PR-2Q-Rerank-Payload-Fix — chunk_id dedup + input cap ───
|
|
# multi-query path 의 merged_chunks_by_doc 가 variant 별 same chunk 중복 누적 →
|
|
# reranker 413 trigger. dedup helper + cap 강제 invariant.
|
|
|
|
|
|
def test_dedup_chunks_empty_returns_empty():
|
|
from services.search.search_pipeline import _dedup_chunks_by_id
|
|
assert _dedup_chunks_by_id([]) == []
|
|
|
|
|
|
def _mk_chunk_result(doc_id: int, chunk_id: int | None = None, score: float = 1.0):
|
|
"""chunk-level SearchResult (chunk_id 별 dedup test 용)."""
|
|
from api.search import SearchResult
|
|
return SearchResult(
|
|
id=doc_id, title=f"doc-{doc_id}", ai_domain=None,
|
|
ai_summary=None, file_format="pdf",
|
|
score=score, snippet=None, match_reason="test",
|
|
chunk_id=chunk_id,
|
|
)
|
|
|
|
|
|
def test_dedup_chunks_by_chunk_id_first_only():
|
|
"""같은 chunk_id 의 SearchResult 여러 개 → 첫 등장만 유지."""
|
|
from services.search.search_pipeline import _dedup_chunks_by_id
|
|
chunks = [
|
|
_mk_chunk_result(doc_id=10, chunk_id=100, score=0.9),
|
|
_mk_chunk_result(doc_id=10, chunk_id=100, score=0.8), # 중복 (variant 다른 등장)
|
|
_mk_chunk_result(doc_id=10, chunk_id=101, score=0.7),
|
|
]
|
|
out = _dedup_chunks_by_id(chunks)
|
|
assert len(out) == 2
|
|
assert out[0].chunk_id == 100
|
|
assert out[0].score == 0.9 # 첫 등장 보존
|
|
assert out[1].chunk_id == 101
|
|
|
|
|
|
def test_dedup_chunks_none_chunk_id_doc_level_first_only():
|
|
"""chunk_id None 인 doc-level result 는 doc.id 기준 first-only."""
|
|
from services.search.search_pipeline import _dedup_chunks_by_id
|
|
chunks = [
|
|
_mk_chunk_result(doc_id=10, chunk_id=None, score=0.9),
|
|
_mk_chunk_result(doc_id=10, chunk_id=None, score=0.8), # 같은 doc_id 중복
|
|
_mk_chunk_result(doc_id=20, chunk_id=None, score=0.7),
|
|
]
|
|
out = _dedup_chunks_by_id(chunks)
|
|
assert len(out) == 2
|
|
assert out[0].id == 10
|
|
assert out[0].score == 0.9
|
|
assert out[1].id == 20
|
|
|
|
|
|
def test_dedup_chunks_mixed_chunk_id_and_none():
|
|
"""chunk_id 있는 것 + None 혼합 — 각각 별도 set 으로 dedup."""
|
|
from services.search.search_pipeline import _dedup_chunks_by_id
|
|
chunks = [
|
|
_mk_chunk_result(doc_id=10, chunk_id=100), # keep (chunk_id 100)
|
|
_mk_chunk_result(doc_id=10, chunk_id=None), # keep (doc-level, first)
|
|
_mk_chunk_result(doc_id=10, chunk_id=100), # drop (chunk_id 100 중복)
|
|
_mk_chunk_result(doc_id=10, chunk_id=None), # drop (doc-level 중복)
|
|
_mk_chunk_result(doc_id=20, chunk_id=200), # keep (chunk_id 200 신규)
|
|
]
|
|
out = _dedup_chunks_by_id(chunks)
|
|
assert len(out) == 3
|
|
assert out[0].chunk_id == 100
|
|
assert out[1].chunk_id is None and out[1].id == 10
|
|
assert out[2].chunk_id == 200
|
|
|
|
|
|
def test_dedup_chunks_order_preserved():
|
|
"""입력 순서 유지 (variant 0 = 원본 verbatim 우선 invariant)."""
|
|
from services.search.search_pipeline import _dedup_chunks_by_id
|
|
chunks = [
|
|
_mk_chunk_result(doc_id=10, chunk_id=cid)
|
|
for cid in (300, 100, 200, 100, 300, 400) # 100/300 중복
|
|
]
|
|
out = _dedup_chunks_by_id(chunks)
|
|
assert [c.chunk_id for c in out] == [300, 100, 200, 400]
|
|
|
|
|
|
def test_phase2q_rerank_input_cap_constants():
|
|
"""PHASE2Q_RERANK_INPUT_CAP + PHASE2Q_CHUNKS_PER_DOC (baseline MAX_* 와 별도).
|
|
|
|
cap 60 + chunks_per_doc=2 + dedup + TEI MAX_BATCH_TOKENS 16384 조합 (사용자 결정,
|
|
2026-05-24). doc 다양성 유지 + reranker 가 doc 의 2 best chunks 봄 + payload 한도
|
|
16384 안에 안전. 진단 history 는 모듈 docstring 박제.
|
|
"""
|
|
from services.search.search_pipeline import (
|
|
PHASE2Q_CHUNKS_PER_DOC,
|
|
PHASE2Q_RERANK_INPUT_CAP,
|
|
)
|
|
assert PHASE2Q_RERANK_INPUT_CAP == 60
|
|
assert PHASE2Q_CHUNKS_PER_DOC == 2
|
|
|
|
|
|
# ─── 10. PR-2Q-Search-Result-Dedup — results doc_id dedup ───
|
|
# multi-query path 의 reranker output → apply_diversity unlimited path 시 같은 doc 의
|
|
# N chunks 박제 → returned_ids inflation 직접 원인. _dedup_results_by_doc_id helper 로
|
|
# API response invariant 강제.
|
|
|
|
|
|
def test_dedup_results_empty_returns_empty():
|
|
from services.search.search_pipeline import _dedup_results_by_doc_id
|
|
assert _dedup_results_by_doc_id([]) == []
|
|
|
|
|
|
def test_dedup_results_no_duplicates_passthrough():
|
|
from services.search.search_pipeline import _dedup_results_by_doc_id
|
|
docs = [_mk_search_result(i) for i in (10, 20, 30)]
|
|
out = _dedup_results_by_doc_id(docs)
|
|
assert [r.id for r in out] == [10, 20, 30]
|
|
|
|
|
|
def test_dedup_results_first_only_preserves_top_score():
|
|
"""같은 doc.id 등장 시 첫 entry 보존 — reranker 의 best chunk (top score) 우선."""
|
|
from services.search.search_pipeline import _dedup_results_by_doc_id
|
|
docs = [
|
|
_mk_search_result(10, score=0.95), # rank 1, keep
|
|
_mk_search_result(20, score=0.85), # keep
|
|
_mk_search_result(10, score=0.70), # 중복 drop (lower score)
|
|
_mk_search_result(30, score=0.60), # keep
|
|
_mk_search_result(20, score=0.50), # 중복 drop
|
|
]
|
|
out = _dedup_results_by_doc_id(docs)
|
|
assert [r.id for r in out] == [10, 20, 30]
|
|
assert [r.score for r in out] == [0.95, 0.85, 0.60] # 첫 등장 score 보존
|
|
|
|
|
|
def test_dedup_results_phase2q_kw_001_case():
|
|
"""Phase 2Q 실측 case — 3868 두 번 등장 시 first-only 보존."""
|
|
from services.search.search_pipeline import _dedup_results_by_doc_id
|
|
docs = [_mk_search_result(i) for i in [3868, 3879, 3856, 3851, 3868, 3858]]
|
|
out = _dedup_results_by_doc_id(docs)
|
|
assert [r.id for r in out] == [3868, 3879, 3856, 3851, 3858]
|
|
assert len(out) == 5 # 6 → 5 (1 중복 제거)
|