feat(study): 이론↔문제 브리지 (Stage B) — 개념별 정답률·약점 개념 지도
이론공부 B→A→C 의 B. 완성된 문제풀이에 이론 연결(약점 구동).
- 마이그 382 study_concept_links(개념 doc↔기출, FK 없음) + 백필 SQL(임베딩 코사인 top-k=10·threshold 0.62 → 2362링크·284개념·964문항)
- concept_links 서비스(related_questions·weakness_map 롤업) + GET /concepts/{id}/questions·/concepts/weakness-map(라우트 순서=weakness-map 먼저)
- 리더 관련기출 섹션(정답률·문항 stub→문항상세) + 홈 약점개념 위젯
- 적대리뷰 반영: Promise.all 격리(weakness-map 실패→코어 대시보드 블랙아웃 방지)·q.subject null 폴백. 백필=배포 후 트랜잭션 래핑 실행. 문제풀이 무접촉
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -15,6 +15,7 @@ from core.auth import get_current_user
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from core.database import get_session
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from models.user import User
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from services.study import concept_curriculum as cc
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from services.study import concept_links as cl
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router = APIRouter()
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@@ -43,6 +44,20 @@ async def get_today_concepts(
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return await cc.today_concepts(session, user.id, topic_id, limit)
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@router.get("/concepts/weakness-map")
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async def get_weakness_map(
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user: Annotated[User, Depends(get_current_user)],
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session: Annotated[AsyncSession, Depends(get_session)],
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topic_id: int = DEFAULT_TOPIC_ID,
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limit: int = 12,
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):
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"""개념 약점 지도 — 링크된 기출 정답률로 약점 개념(정답률<60%) 우선(이론↔문제)."""
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name = await cc._topic_name(session, topic_id)
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if not name:
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return {"weak": [], "weak_total": 0, "evaluated_total": 0}
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return await cl.weakness_map(session, user.id, name, limit)
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@router.get("/concepts/{doc_id}")
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async def get_concept_detail(
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doc_id: int,
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@@ -57,6 +72,17 @@ async def get_concept_detail(
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return detail
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@router.get("/concepts/{doc_id}/questions")
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async def get_concept_questions(
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doc_id: int,
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user: Annotated[User, Depends(get_current_user)],
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session: Annotated[AsyncSession, Depends(get_session)],
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limit: int = 20,
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):
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"""개념 관련 기출 + 내 정답률 (이론↔문제 브리지)."""
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return await cl.related_questions(session, user.id, doc_id, limit)
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@router.post("/concepts/{doc_id}/read")
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async def post_concept_read(
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doc_id: int,
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@@ -0,0 +1,139 @@
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"""concept_links — 이론↔문제 브리지 롤업 (Stage B).
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study_concept_links(개념 doc ↔ 기출문항, 임베딩 코사인) + study_question_progress(내 풀이상태)를
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조인해 (a) 개념별 관련 기출 + 내 정답률(related_questions), (b) 개념 약점 지도(weakness_map) 산출.
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읽기 전용 집계 · LLM 0. 링크 적재는 scripts/concept_links_backfill.sql(임베딩) 배치.
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정답률 = 링크된 문항 중 progress.last_outcome 기준(attempted=풀이이력 보유, correct=최근정답).
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"""
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from __future__ import annotations
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from sqlalchemy import text
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from sqlalchemy.ext.asyncio import AsyncSession
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_ACCURACY_WEAK_PCT = 60 # 정답률 < 60% = 약점(attempted>0 일 때만)
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_AGG_SQL = text(
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"""
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SELECT count(*) AS linked,
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count(pr.study_question_id) FILTER (WHERE pr.last_outcome IS NOT NULL) AS attempted,
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count(*) FILTER (WHERE pr.last_outcome = 'correct') AS correct
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FROM study_concept_links l
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LEFT JOIN study_question_progress pr
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ON pr.study_question_id = l.question_id AND pr.user_id = :uid
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WHERE l.concept_doc_id = :doc_id AND l.link_source = 'embedding'
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"""
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)
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_QROWS_SQL = text(
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"""
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SELECT q.id AS id, q.subject AS subject, q.exam_round AS exam_round,
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q.exam_question_number AS qnum, l.score AS score,
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pr.last_outcome AS last_outcome, pr.review_stage AS review_stage
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FROM study_concept_links l
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JOIN study_questions q ON q.id = l.question_id AND q.deleted_at IS NULL AND q.is_active
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LEFT JOIN study_question_progress pr
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ON pr.study_question_id = q.id AND pr.user_id = :uid
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WHERE l.concept_doc_id = :doc_id AND l.link_source = 'embedding'
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ORDER BY l.score DESC
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LIMIT :limit
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"""
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)
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_WEAKNESS_SQL = text(
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"""
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SELECT d.id AS doc_id, d.title AS title,
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split_part(replace(d.user_tags::text, '"', ''), '/', 3) AS subject,
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count(l.id) AS linked,
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count(pr.study_question_id) FILTER (WHERE pr.last_outcome IS NOT NULL) AS attempted,
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count(*) FILTER (WHERE pr.last_outcome = 'correct') AS correct
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FROM documents d
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JOIN study_concept_links l ON l.concept_doc_id = d.id AND l.link_source = 'embedding'
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LEFT JOIN study_question_progress pr
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ON pr.study_question_id = l.question_id AND pr.user_id = :uid
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WHERE d.user_tags::text LIKE :like AND d.deleted_at IS NULL
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GROUP BY d.id, d.title, subject
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"""
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)
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async def related_questions(
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session: AsyncSession, user_id: int, doc_id: int, limit: int = 20
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) -> dict:
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"""개념 doc 의 관련 기출 + 내 정답률(전체 링크 기준 집계 + 상위 N 표시용)."""
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agg = (
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await session.execute(_AGG_SQL, {"uid": user_id, "doc_id": doc_id})
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).mappings().first()
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rows = (
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await session.execute(
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_QROWS_SQL, {"uid": user_id, "doc_id": doc_id, "limit": limit}
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)
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).mappings().all()
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linked = (agg["linked"] if agg else 0) or 0
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attempted = (agg["attempted"] if agg else 0) or 0
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correct = (agg["correct"] if agg else 0) or 0
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accuracy = round(100 * correct / attempted) if attempted else None
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return {
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"linked": linked,
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"attempted": attempted,
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"correct": correct,
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"accuracy": accuracy,
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"questions": [
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{
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"id": r["id"],
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"subject": r["subject"],
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"exam_round": r["exam_round"],
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"qnum": r["qnum"],
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"score": round(r["score"], 3) if r["score"] is not None else None,
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"last_outcome": r["last_outcome"],
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"review_stage": r["review_stage"],
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}
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for r in rows
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],
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}
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async def weakness_map(
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session: AsyncSession, user_id: int, topic_name: str, limit: int = 12
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) -> dict:
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"""개념 약점 지도 — 링크된 기출 정답률로 개념 채색. 약점(attempted>0·정답률<60%) 우선 정렬."""
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like = f"%@library/{topic_name}/%"
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rows = (
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await session.execute(_WEAKNESS_SQL, {"uid": user_id, "like": like})
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).mappings().all()
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concepts = []
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for r in rows:
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attempted = r["attempted"] or 0
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correct = r["correct"] or 0
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accuracy = round(100 * correct / attempted) if attempted else None
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if accuracy is None:
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state = "unattempted"
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elif accuracy < _ACCURACY_WEAK_PCT:
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state = "weak"
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else:
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state = "ok"
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concepts.append(
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{
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"doc_id": r["doc_id"],
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"title": r["title"],
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"subject": r["subject"],
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"linked": r["linked"] or 0,
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"attempted": attempted,
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"accuracy": accuracy,
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"state": state,
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}
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)
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# 약점 우선(정답률 오름차순) → 미평가는 뒤로. 홈 위젯용 상위 N.
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weak = sorted(
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[c for c in concepts if c["state"] == "weak"],
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key=lambda c: (c["accuracy"], -c["attempted"], c["doc_id"]),
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)
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return {
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"weak": weak[:limit],
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"weak_total": len(weak),
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"evaluated_total": sum(1 for c in concepts if c["state"] != "unattempted"),
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}
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@@ -4,7 +4,7 @@
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import { onMount } from 'svelte';
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import { api } from '$lib/api';
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import { addToast } from '$lib/stores/toast';
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import { BookOpen, PenLine, GraduationCap, FolderKanban, Layers, Repeat, Flag, Inbox, Activity, CalendarCheck } from 'lucide-svelte';
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import { BookOpen, PenLine, GraduationCap, FolderKanban, Layers, Repeat, Flag, Inbox, Activity, CalendarCheck, Target } from 'lucide-svelte';
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let cardReviewCount = $state(0);
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let questionFlagCount = $state(0);
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@@ -12,6 +12,7 @@
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// 오늘의 공부 (이론 홈)
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let curriculum = $state(null);
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let todayConcepts = $state([]);
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let weakConcepts = $state([]); // 약점 개념(관련 기출 정답률 낮음)
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let dashLoading = $state(true);
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let readPct = $derived(
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@@ -28,10 +29,15 @@
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curriculum = cur;
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todayConcepts = today?.concepts ?? [];
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} catch {
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// 대시보드 실패해도 허브 나머지는 동작 (조용히)
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// 코어 대시보드 실패해도 허브 나머지는 동작 (조용히)
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} finally {
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dashLoading = false;
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}
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// 약점 개념 = 비차단(신규 엔드포인트 실패해도 코어 대시보드 블랙아웃 방지)
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try {
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const weak = await api('/study/concepts/weakness-map?limit=5');
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weakConcepts = weak?.weak ?? [];
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} catch {}
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}
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async function markRead(doc) {
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@@ -121,6 +127,22 @@
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{/each}
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</ul>
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{/if}
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{#if weakConcepts.length > 0}
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<div class="mt-4 pt-3 border-t border-default">
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<div class="text-xs text-dim mb-2 flex items-center gap-1.5">
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<Target size={13} class="text-error" /> 약점 개념 <span class="text-faint">(관련 기출 정답률 낮음)</span>
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</div>
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<div class="flex flex-wrap gap-2">
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{#each weakConcepts as w (w.doc_id)}
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<a href="/study/read/{w.doc_id}"
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class="text-xs rounded-full border border-error/40 bg-error/10 text-error px-3 py-1 hover:bg-error/20 transition-colors">
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{w.title.replace(/^\d+_/, '')} <span class="font-semibold">{w.accuracy}%</span>
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</a>
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{/each}
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</div>
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</div>
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{/if}
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{/if}
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</section>
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@@ -13,11 +13,12 @@
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import Button from '$lib/components/ui/Button.svelte';
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import EmptyState from '$lib/components/ui/EmptyState.svelte';
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import Skeleton from '$lib/components/ui/Skeleton.svelte';
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import { BookOpen, ArrowLeft, Eye, EyeOff, Check, ChevronLeft, ChevronRight } from 'lucide-svelte';
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import { BookOpen, ArrowLeft, Eye, EyeOff, Check, ChevronLeft, ChevronRight, FileQuestion } from 'lucide-svelte';
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let docId = $derived($page.params.docId);
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let concept = $state(null);
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let relatedQ = $state(null); // 관련 기출(이론↔문제, 비차단)
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let loading = $state(true);
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let notFound = $state(false);
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let mode = $state('read'); // 'read' | 'recall'(떠올리기)
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@@ -25,12 +26,17 @@
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let marking = $state(false);
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const STAGE_LABEL = { 0: '복습 시작', 1: '복습 1단계', 2: '복습 2단계', 3: '복습 3단계', 4: '학습 완료' };
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const OUTCOME_MARK = { correct: '○', wrong: '✕', unsure: '?' };
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const OUTCOME_CLASS = { correct: 'text-success', wrong: 'text-error', unsure: 'text-warning' };
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const outcomeMark = (o) => OUTCOME_MARK[o] ?? '–';
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const outcomeClass = (o) => OUTCOME_CLASS[o] ?? 'text-faint';
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async function load() {
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const reqId = docId; // in-flight 가드: 백링크 연타 시 stale 응답 무시
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loading = true;
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notFound = false;
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concept = null;
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relatedQ = null;
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revealed = {};
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mode = 'read';
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try {
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@@ -41,9 +47,15 @@
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if (reqId !== docId) return;
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if (e?.status === 404) notFound = true;
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else addToast('error', '개념을 불러오지 못했습니다');
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return; // 본문 실패 → 관련기출 스킵
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} finally {
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if (reqId === docId) loading = false;
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}
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// 관련 기출(비차단 — 실패해도 본문 표시엔 영향 없음)
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try {
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const rq = await api(`/study/concepts/${reqId}/questions?limit=6`);
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if (reqId === docId) relatedQ = rq;
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} catch {}
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}
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// $effect 가 마운트 1회 + docId 변경(백링크/이전·다음) 재로드를 모두 커버 (onMount 불필요)
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@@ -202,6 +214,29 @@
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</section>
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{/if}
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<!-- 관련 기출 (이론↔문제 브리지) -->
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{#if relatedQ && relatedQ.linked > 0}
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<section class="mb-5 rounded-lg border border-default bg-surface p-4">
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<h2 class="text-sm font-semibold text-text mb-2 flex items-center gap-1.5">
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<FileQuestion size={15} class="text-accent" /> 관련 기출
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<span class="ml-1 text-xs font-normal text-dim">
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{relatedQ.linked}문항{#if relatedQ.accuracy !== null} · 정답률 <span class="{relatedQ.accuracy < 60 ? 'text-error' : 'text-text'} font-medium">{relatedQ.accuracy}%</span>{:else} · 아직 안 풂{/if}
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</span>
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</h2>
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<ul class="space-y-0.5">
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{#each relatedQ.questions as q (q.id)}
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<li>
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<a href="/study/topics/4/questions/{q.id}"
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class="flex items-center gap-2 text-xs py-1 text-dim hover:text-accent transition-colors">
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<span class="{outcomeClass(q.last_outcome)} shrink-0 w-4 text-center font-bold">{outcomeMark(q.last_outcome)}</span>
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<span class="truncate">{q.subject ?? '기출'}{#if q.exam_round} · {q.exam_round}{/if}</span>
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</a>
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</li>
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{/each}
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</ul>
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</section>
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{/if}
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<!-- 액션바 -->
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<div class="flex items-center gap-2 border-t border-default pt-4 mt-2">
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{#if concept.prev_id}
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@@ -0,0 +1,15 @@
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-- 382_study_concept_links.sql — 개념문서 ↔ 기출문항 링크 (이론↔문제 브리지, Stage B).
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-- concept_doc_id=documents.id, question_id=study_questions.id — FK 없음(hot 테이블 락 회피, 선례).
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-- link_source: 'embedding'(bge-m3 코사인 top-k, 주력) | 'ref'(해설 .md 참조, 후속 enrichment).
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-- score=코사인 유사도(0~1). UNIQUE(doc,question,source) — source별 공존 허용(재튜닝=source 전삭제 후 재삽입).
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CREATE TABLE IF NOT EXISTS study_concept_links (
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id bigserial PRIMARY KEY,
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concept_doc_id bigint NOT NULL,
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question_id bigint NOT NULL,
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link_source text NOT NULL,
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score double precision,
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created_at timestamptz NOT NULL DEFAULT now(),
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CONSTRAINT uq_concept_link UNIQUE (concept_doc_id, question_id, link_source)
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);
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CREATE INDEX IF NOT EXISTS idx_concept_links_doc ON study_concept_links(concept_doc_id);
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CREATE INDEX IF NOT EXISTS idx_concept_links_q ON study_concept_links(question_id);
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@@ -0,0 +1,23 @@
|
||||
-- concept_links_backfill.sql — 개념↔문항 임베딩 링크 재생성 (Stage B, 멱등·재실행 안전).
|
||||
-- 정찰 확정: bge-m3 1024d 코사인, per-concept top-k=10, threshold 0.62 → ~2362링크·284/289개념·964문항.
|
||||
-- 재튜닝 시 DELETE(embedding 소스만) 후 재삽입 = ref 링크(후속) 불변. 개념 doc = 가스기사 태그.
|
||||
DELETE FROM study_concept_links WHERE link_source = 'embedding';
|
||||
INSERT INTO study_concept_links (concept_doc_id, question_id, link_source, score)
|
||||
WITH cd AS (
|
||||
SELECT id, embedding FROM documents
|
||||
WHERE user_tags::text LIKE '%@library/가스기사/%'
|
||||
AND deleted_at IS NULL AND embedding IS NOT NULL
|
||||
),
|
||||
ranked AS (
|
||||
SELECT cd.id AS concept_doc_id, q.id AS question_id,
|
||||
1 - (q.embedding <=> cd.embedding) AS score,
|
||||
row_number() OVER (PARTITION BY cd.id ORDER BY q.embedding <=> cd.embedding) AS rn
|
||||
FROM cd
|
||||
JOIN study_questions q
|
||||
ON q.study_topic_id = 4 AND q.embedding IS NOT NULL
|
||||
AND q.deleted_at IS NULL AND q.is_active
|
||||
)
|
||||
SELECT concept_doc_id, question_id, 'embedding', score
|
||||
FROM ranked
|
||||
WHERE rn <= 10 AND score >= 0.62
|
||||
ON CONFLICT (concept_doc_id, question_id, link_source) DO NOTHING;
|
||||
Reference in New Issue
Block a user