From e7cd710e69494de319c1cd7441700afafb605149 Mon Sep 17 00:00:00 2001
From: Hyungi Ahn <hyungiahn@Hyungiui-MacBookPro.local>
Date: Fri, 3 Apr 2026 14:16:36 +0900
Subject: [PATCH] =?UTF-8?q?fix:=20hybrid=20=EA=B2=80=EC=83=89=20=EB=8B=A8?=
 =?UTF-8?q?=EC=88=9C=ED=99=94=20=E2=80=94=20FTS=20+=20ILIKE=20(vector/trgm?=
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asyncpg 파라미터 바인딩 충돌 문제 근본 해결.
한국어 검색: ILIKE fallback으로 안정 동작.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 app/api/search.py | 66 ++++++++++++++---------------------------------
 1 file changed, 19 insertions(+), 47 deletions(-)

diff --git a/app/api/search.py b/app/api/search.py
index 4a67ac7..2a09fb2 100644
--- a/app/api/search.py
+++ b/app/api/search.py
@@ -143,55 +143,27 @@ async def _search_vector(session: AsyncSession, query: str, limit: int) -> list[
 
 
 async def _search_hybrid(session: AsyncSession, query: str, limit: int) -> list[SearchResult]:
-    """하이브리드 검색 — FTS + 트리그램 + 벡터 가중 합산"""
-    # 벡터 임베딩 생성 (실패 시 FTS+트리그램만)
-    query_embedding = None
-    try:
-        client = AIClient()
-        query_embedding = await client.embed(query)
-        await client.close()
-    except Exception:
-        pass
-
-    vector_clause = ""
-    vector_score = "0"
-    params = {"query": query, "limit": limit, "w_fts": W_FTS, "w_trgm": W_TRGM, "w_vector": W_VECTOR}
-
-    if query_embedding:
-        vector_clause = "LEFT JOIN LATERAL (SELECT 1 - (d.embedding <=> :embedding::vector) AS vscore) v ON true"
-        vector_score = "coalesce(v.vscore, 0)"
-        params["embedding"] = str(query_embedding)
-    else:
-        # 벡터 없으면 FTS+트리그램만 사용
-        params["w_fts"] = 0.6
-        params["w_trgm"] = 0.4
-        params["w_vector"] = 0.0
-
+    """하이브리드 검색 — FTS + ILIKE (안정적 한국어 지원)"""
     result = await session.execute(
-        text(f"""
-            SELECT * FROM (
-                SELECT d.id, d.title, d.ai_domain, d.ai_summary, d.file_format,
-                       (
-                           :w_fts * coalesce(ts_rank(
-                               to_tsvector('simple', coalesce(d.title, '') || ' ' || coalesce(d.extracted_text, '')),
-                               plainto_tsquery('simple', :query)
-                           ), 0)
-                           + :w_trgm * coalesce(similarity(
-                               coalesce(d.title, '') || ' ' || coalesce(d.extracted_text, ''),
-                               :query
-                           ), 0)
-                           + :w_vector * {vector_score}
-                       ) AS score,
-                       left(d.extracted_text, 200) AS snippet
-                FROM documents d
-                {vector_clause}
-                WHERE coalesce(d.extracted_text, '') != ''
-                   OR (coalesce(d.title, '') || ' ' || coalesce(d.extracted_text, '')) ILIKE '%%' || :query || '%%'
-            ) sub
-            WHERE sub.score > 0.001
-            ORDER BY sub.score DESC
+        text("""
+            SELECT id, title, ai_domain, ai_summary, file_format,
+                   GREATEST(
+                       coalesce(ts_rank(
+                           to_tsvector('simple', coalesce(title, '') || ' ' || coalesce(extracted_text, '')),
+                           plainto_tsquery('simple', :query)
+                       ), 0),
+                       CASE WHEN (coalesce(title, '') || ' ' || coalesce(extracted_text, ''))
+                            ILIKE '%%' || :query || '%%' THEN 0.5 ELSE 0 END
+                   ) AS score,
+                   left(extracted_text, 200) AS snippet
+            FROM documents
+            WHERE to_tsvector('simple', coalesce(title, '') || ' ' || coalesce(extracted_text, ''))
+                  @@ plainto_tsquery('simple', :query)
+               OR (coalesce(title, '') || ' ' || coalesce(extracted_text, ''))
+                  ILIKE '%%' || :query || '%%'
+            ORDER BY score DESC
             LIMIT :limit
         """),
-        params,
+        {"query": query, "limit": limit},
     )
     return [SearchResult(**row._mapping) for row in result]