fix(stock,docs): portfolio total_buy 수량 곱산 + insta-trends spec 변경 이력 (F4 + F6)

[F4] /api/portfolio 응답의 summary.total_buy가 종목별 단가 × 수량의 합이
되도록 fix. 기존 인라인 코드가 purchase_price를 수량 미곱산으로 단순
누적해 명세(qty 100 · avg 72000 → 7,200,000)와 어긋났음. API_SPEC.md에
purchase_price 필드 의미 + total_buy 계산식 명시. test 3건 (단가 곱산,
avg_price 폴백, 다종목 합산).

[F6] insta-trends spec/plan 상단에 "google_trends → youtube_trending"
변경 이력 추가. Google Trends endpoint 폐기로 source 교체된 이력이
본문 검색 시 혼란 주는 문제 차단. 사유 cross-ref:
feedback_external_data_sources.md

stock/tests/test_portfolio_total_buy.py

@@ -0,0 +1,77 @@
+"""포트폴리오 /api/portfolio 응답의 total_buy 계산 회귀 테스트 (CODE_REVIEW F4).
+
+purchase_price는 종목별 단가(1주당) 의미. total_buy = SUM(purchase_price × quantity).
+purchase_price가 없으면 avg_price로 폴백 후 동일하게 수량 곱산.
+"""
+from unittest.mock import patch
+
+from fastapi.testclient import TestClient
+
+from app.main import app
+
+
+def _fake_db_setup(monkeypatch, items, cash=None):
+    from app import main as stock_main
+    monkeypatch.setattr(stock_main, "get_all_portfolio", lambda: items)
+    monkeypatch.setattr(stock_main, "get_all_broker_cash", lambda: cash or [])
+
+
+def test_portfolio_total_buy_uses_purchase_price_times_quantity(monkeypatch):
+    """purchase_price 설정 시: total_buy = purchase_price × quantity 의 합."""
+    items = [
+        {"id": 1, "broker": "KB", "ticker": "005930", "name": "삼성전자",
+         "quantity": 100, "avg_price": 72000, "purchase_price": 70000},
+    ]
+    fake_prices = {"005930": {"price": 74500, "session": "REGULAR", "as_of": "2026-05-17T10:00:00+09:00"}}
+    _fake_db_setup(monkeypatch, items)
+    from app import main as stock_main
+    monkeypatch.setattr(stock_main, "get_current_prices_detail", lambda t: fake_prices)
+
+    client = TestClient(app)
+    resp = client.get("/api/portfolio")
+    assert resp.status_code == 200
+    data = resp.json()
+    # purchase_price=70000 × quantity=100 = 7,000,000
+    assert data["summary"]["total_buy"] == 7_000_000
+
+
+def test_portfolio_total_buy_falls_back_to_avg_price_with_quantity(monkeypatch):
+    """purchase_price 미설정 시: avg_price 폴백 + 수량 곱산. API_SPEC 예시와 일치."""
+    items = [
+        {"id": 1, "broker": "KB", "ticker": "005930", "name": "삼성전자",
+         "quantity": 100, "avg_price": 72000, "purchase_price": None},
+    ]
+    fake_prices = {"005930": {"price": 74500, "session": "REGULAR", "as_of": "2026-05-17T10:00:00+09:00"}}
+    _fake_db_setup(monkeypatch, items)
+    from app import main as stock_main
+    monkeypatch.setattr(stock_main, "get_current_prices_detail", lambda t: fake_prices)
+
+    client = TestClient(app)
+    resp = client.get("/api/portfolio")
+    assert resp.status_code == 200
+    data = resp.json()
+    # avg_price=72000 × quantity=100 = 7,200,000 (API_SPEC.md 예시와 일치)
+    assert data["summary"]["total_buy"] == 7_200_000
+
+
+def test_portfolio_total_buy_sums_multiple_holdings(monkeypatch):
+    """여러 종목 합산도 단가 × 수량 합."""
+    items = [
+        {"id": 1, "broker": "KB", "ticker": "005930", "name": "삼성전자",
+         "quantity": 100, "avg_price": 70000, "purchase_price": 70000},
+        {"id": 2, "broker": "NH", "ticker": "000660", "name": "SK하이닉스",
+         "quantity": 50, "avg_price": 130000, "purchase_price": 130000},
+    ]
+    fake_prices = {
+        "005930": {"price": 74500, "session": "REGULAR", "as_of": "2026-05-17T10:00:00+09:00"},
+        "000660": {"price": 140000, "session": "REGULAR", "as_of": "2026-05-17T10:00:00+09:00"},
+    }
+    _fake_db_setup(monkeypatch, items)
+    from app import main as stock_main
+    monkeypatch.setattr(stock_main, "get_current_prices_detail", lambda t: fake_prices)
+
+    client = TestClient(app)
+    resp = client.get("/api/portfolio")
+    data = resp.json()
+    # 70000*100 + 130000*50 = 7,000,000 + 6,500,000 = 13,500,000
+    assert data["summary"]["total_buy"] == 13_500_000