web-page-backend/docs/superpowers/plans/2026-05-16-insta-trends-implementation.md

insta Trends Tab Implementation Plan

For agentic workers: REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (- [ ]) syntax for tracking.

⚠️ 변경 이력

• 2026-05-17: 본문에 google_trends source로 기재된 모든 task와 코드 블록은 실제 구현에서 youtube_trending으로 교체됨. Google Trends 비공식 endpoint(RSS + dailytrends JSON 양쪽) 모두 404 폐기 확인. YouTube Data API v3 mostPopular로 source 대체 + pytrends 의존성 제거. 운영 코드는 현재 youtube_trending 사용 중. 이 plan을 다시 실행할 일이 있으면 본문의 google_trends 단어를 youtube_trending으로 읽어달라. 자세한 사유와 교체 체크리스트는 feedback_external_data_sources.md.

Goal: Add a "Trends" tab to the Insta page that pulls external trends from NAVER popular + Google Trends, lets the user set category weights, and feeds those weights back into the daily keyword extraction pipeline.

Architecture: New trend_collector module in insta-lab (NAVER news.json 인기순 + pytrends Google Trends + Claude Haiku 카테고리 분류 + in-memory 캐시). Existing trending_keywords table gets a source column; new account_preferences table stores category weights. keyword_extractor gains a extract_with_weights() variant. InstaAgent runs a new 09:00 cron for trend collection and applies weights at 09:30 extraction. web-ui splits InstaCards into Cards/Trends tabs and adds 3 panels (AccountFocus / ExternalTrends / PreferenceImpact).

Tech Stack: Python 3.12, FastAPI, SQLite, anthropic 0.52, pytrends 4.9+ (new), httpx, React + Vite + plain CSS.

Spec reference: docs/superpowers/specs/2026-05-16-insta-trends-design.md

---

File Structure

Files to create

Path	Responsibility
insta-lab/app/trend_collector.py	NAVER 인기 + Google Trends 수집 + LLM 카테고리 분류 + 1일 in-memory 캐시
insta-lab/tests/test_trend_collector.py	mocked requests / mocked pytrends / mocked anthropic
insta-lab/tests/test_extract_with_weights.py	가중치 알고리즘 — 균등/0/공집합 fallback
insta-lab/tests/test_preferences_crud.py	account_preferences upsert + 기본값 시드
insta-lab/tests/test_main_trends.py	신규 4개 엔드포인트 통합 (TestClient)
agent-office/tests/test_insta_agent_trends.py	09:00 cron + 가중치 적용 분기

Files to modify

Path	Change
insta-lab/requirements.txt	+ pytrends>=4.9
insta-lab/app/db.py	(1) trending_keywords.source 컬럼 idempotent 추가, (2) account_preferences CREATE TABLE, (3) 신규 CRUD: add_external_trend, list_trends, get_preferences, upsert_preferences. 기존 add_trending_keyword도 source 인자 받도록 확장 (default='manual'로 역호환)
insta-lab/app/keyword_extractor.py	+ extract_with_weights(weights, total_limit)
insta-lab/app/main.py	+ 4 endpoints: POST /api/insta/trends/collect, GET /api/insta/trends, GET /api/insta/preferences, PUT /api/insta/preferences. 기존 GET /api/insta/keywords에 source 쿼리 파라미터 추가
agent-office/app/agents/insta.py	(1) on_schedule()이 preferences 호출 후 insta_extract_with_weights를 트리거하도록 변경 (2) on_command("collect_trends", ...) 액션 추가
agent-office/app/service_proxy.py	+ insta_collect_trends, insta_list_trends, insta_get_preferences, insta_put_preferences, insta_extract_with_weights
agent-office/app/scheduler.py	+ _run_insta_trends_collect cron 09:00
web-ui/src/api.js	+ 4 helpers
web-ui/src/pages/insta/InstaCards.jsx	탭 네비게이션 (Cards/Trends) + 3 새 패널 컴포넌트
web-ui/src/pages/insta/InstaCards.css	탭/패널/슬라이더 스타일

Files NOT to touch

• Existing tests in insta-lab (test_db / test_keyword_extractor / test_main 등) — should remain green after migration. Update only if add_trending_keyword signature change breaks them; in that case adjust the call sites in tests, not the contracts.

---

Conventions

• Repo root: C:\Users\jaeoh\Desktop\workspace\web-backend (web-backend) + C:\Users\jaeoh\Desktop\workspace\web-ui (web-ui).
• Commit on main (project flow). Each task = its own commit.
• TDD: failing test → implementation → passing test → commit.
• Windows-safe SQLite cleanup pattern in test fixtures: gc.collect() + remove -wal/-shm sidecars before os.remove(path).
• Idempotent migrations: use PRAGMA table_info() to check column existence before ALTER.
• pytrends calls in tests MUST be mocked (no live network).

---

Task 0: Branch + dependency bump

Files:

• Modify: insta-lab/requirements.txt

• Step 1: Confirm clean working tree

Run: git status --short Expected: only pre-existing untracked files (.superpowers/, stock/app/test_scraper.py).

• Step 2: Create feature branch

git checkout -b feat/insta-trends

• Step 3: Append pytrends>=4.9 to requirements

Edit insta-lab/requirements.txt. Append at end:

pytrends>=4.9

Resulting file:

fastapi==0.115.6
uvicorn[standard]==0.34.0
requests==2.32.3
httpx>=0.27
anthropic==0.52.0
jinja2>=3.1.4
playwright==1.48.0
pytest>=8.0
pytest-asyncio>=0.24
pytrends>=4.9

• Step 4: Install locally so subsequent tests can import

pip install "pytrends>=4.9"

• Step 5: Commit

git add insta-lab/requirements.txt
git commit -m "chore(insta-lab): add pytrends>=4.9 dependency"

---

Task 1: DB migration — source column + account_preferences table + CRUD

Files:

• Modify: insta-lab/app/db.py

• Create: insta-lab/tests/test_preferences_crud.py

• Modify: insta-lab/tests/test_db.py (only if existing tests break)

• Step 1: Write the failing test tests/test_preferences_crud.py

import os
import gc
import tempfile

import pytest

from app import db as db_module


@pytest.fixture
def tmp_db(monkeypatch):
    fd, path = tempfile.mkstemp(suffix=".db")
    os.close(fd)
    monkeypatch.setattr(db_module, "DB_PATH", path)
    db_module.init_db()
    yield path
    gc.collect()
    for ext in ("", "-wal", "-shm"):
        try:
            os.remove(path + ext)
        except OSError:
            pass


def test_init_db_creates_account_preferences(tmp_db):
    with db_module._conn() as conn:
        rows = conn.execute("SELECT name FROM sqlite_master WHERE type='table'").fetchall()
    names = {r[0] for r in rows}
    assert "account_preferences" in names


def test_init_db_seeds_default_weights(tmp_db):
    prefs = db_module.get_preferences()
    cats = {p["category"]: p["weight"] for p in prefs}
    assert cats["economy"] == pytest.approx(1.0)
    assert cats["psychology"] == pytest.approx(1.0)
    assert cats["celebrity"] == pytest.approx(1.0)


def test_upsert_preferences_replaces_weights(tmp_db):
    db_module.upsert_preferences({"economy": 0.6, "psychology": 0.3, "celebrity": 0.1, "tech": 0.5})
    prefs = {p["category"]: p["weight"] for p in db_module.get_preferences()}
    assert prefs["economy"] == pytest.approx(0.6)
    assert prefs["tech"] == pytest.approx(0.5)
    assert "celebrity" in prefs and prefs["celebrity"] == pytest.approx(0.1)


def test_trending_keywords_source_column_exists(tmp_db):
    with db_module._conn() as conn:
        cols = [r[1] for r in conn.execute("PRAGMA table_info(trending_keywords)").fetchall()]
    assert "source" in cols


def test_add_trending_keyword_default_source(tmp_db):
    kid = db_module.add_trending_keyword({
        "keyword": "K", "category": "economy", "score": 0.5, "articles_count": 3,
    })
    with db_module._conn() as conn:
        row = conn.execute("SELECT source FROM trending_keywords WHERE id=?", (kid,)).fetchone()
    assert row[0] == "manual"


def test_add_external_trend_stores_source(tmp_db):
    tid = db_module.add_external_trend({
        "keyword": "급등주", "category": "economy", "source": "naver_popular", "score": 0.9,
    })
    rows = db_module.list_trends(source="naver_popular")
    assert any(r["id"] == tid and r["keyword"] == "급등주" for r in rows)


def test_list_trends_filters_by_source_and_category(tmp_db):
    db_module.add_external_trend({"keyword": "A", "category": "economy", "source": "naver_popular", "score": 1.0})
    db_module.add_external_trend({"keyword": "B", "category": "celebrity", "source": "google_trends", "score": 1.0})
    only_naver = db_module.list_trends(source="naver_popular")
    assert {r["keyword"] for r in only_naver} == {"A"}
    only_celeb_google = db_module.list_trends(source="google_trends", category="celebrity")
    assert {r["keyword"] for r in only_celeb_google} == {"B"}

• Step 2: Run test, expect failure

Run: cd insta-lab && pytest tests/test_preferences_crud.py -v Expected: failures on account_preferences not existing, get_preferences/upsert_preferences/add_external_trend/list_trends not defined.

• Step 3: Update insta-lab/app/db.py

Append new helpers and amend init_db():

3a. In init_db(), append before the function ends (after the existing prompt_templates CREATE):

        # source column for trending_keywords (idempotent ALTER)
        cols = [r[1] for r in conn.execute("PRAGMA table_info(trending_keywords)").fetchall()]
        if "source" not in cols:
            conn.execute("ALTER TABLE trending_keywords ADD COLUMN source TEXT NOT NULL DEFAULT 'manual'")
            conn.execute("CREATE INDEX IF NOT EXISTS idx_tk_source ON trending_keywords(source, suggested_at DESC)")

        # account_preferences — 카테고리 가중치
        conn.execute("""
            CREATE TABLE IF NOT EXISTS account_preferences (
                category    TEXT PRIMARY KEY,
                weight      REAL NOT NULL DEFAULT 1.0,
                updated_at  TEXT NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ','now'))
            )
        """)
        # seed defaults if table empty
        existing = conn.execute("SELECT COUNT(*) FROM account_preferences").fetchone()[0]
        if existing == 0:
            for cat in ("economy", "psychology", "celebrity"):
                conn.execute(
                    "INSERT INTO account_preferences(category, weight) VALUES(?,?)",
                    (cat, 1.0),
                )

3b. Amend add_trending_keyword to accept optional source:

def add_trending_keyword(row: Dict[str, Any]) -> int:
    with _conn() as conn:
        cur = conn.execute(
            "INSERT INTO trending_keywords(keyword, category, score, articles_count, source) VALUES(?,?,?,?,?)",
            (
                row["keyword"], row["category"],
                float(row.get("score", 0.0)), int(row.get("articles_count", 0)),
                row.get("source", "manual"),
            ),
        )
        return cur.lastrowid

3c. Add new helpers (append to db.py):

def add_external_trend(row: Dict[str, Any]) -> int:
    """`source` 필수 — naver_popular | google_trends. trending_keywords에 인서트."""
    if "source" not in row:
        raise ValueError("add_external_trend requires 'source' field")
    return add_trending_keyword(row)


def list_trends(source: Optional[str] = None, category: Optional[str] = None,
                days: int = 1) -> List[Dict[str, Any]]:
    sql = "SELECT * FROM trending_keywords WHERE suggested_at >= datetime('now', ?)"
    params: List[Any] = [f"-{int(days)} days"]
    if source and source != "all":
        sql += " AND source=?"
        params.append(source)
    if category:
        sql += " AND category=?"
        params.append(category)
    sql += " ORDER BY suggested_at DESC, score DESC"
    with _conn() as conn:
        rows = conn.execute(sql, params).fetchall()
    return [dict(r) for r in rows]


def get_preferences() -> List[Dict[str, Any]]:
    with _conn() as conn:
        rows = conn.execute(
            "SELECT category, weight, updated_at FROM account_preferences ORDER BY category ASC"
        ).fetchall()
    return [dict(r) for r in rows]


def upsert_preferences(weights: Dict[str, float]) -> None:
    """전체 upsert. 기존에 있던 카테고리는 weight 갱신, 신규는 INSERT.
    명시되지 않은 기존 카테고리는 그대로 둔다 (삭제 X). 삭제 필요 시 별도 API로."""
    with _conn() as conn:
        for cat, w in weights.items():
            conn.execute("""
                INSERT INTO account_preferences(category, weight)
                     VALUES(?,?)
                ON CONFLICT(category) DO UPDATE SET
                    weight=excluded.weight,
                    updated_at=strftime('%Y-%m-%dT%H:%M:%fZ','now')
            """, (cat, float(w)))

• Step 4: Run preferences test, expect pass

Run: cd insta-lab && pytest tests/test_preferences_crud.py -v Expected: 7 PASS.

• Step 5: Run existing test suite to confirm no regression

Run: cd insta-lab && pytest -v Expected: All prior tests still pass + new 7. If any existing test breaks (e.g., on add_trending_keyword signature), fix the test call site (it already uses positional dict so should be fine).

• Step 6: Commit

git add insta-lab/app/db.py insta-lab/tests/test_preferences_crud.py
git commit -m "feat(insta-lab): db migration — trending_keywords.source + account_preferences + CRUD"

---

Task 2: trend_collector — NAVER popular fetcher

Files:

• Create: insta-lab/app/trend_collector.py (initial — NAVER part only)

• Create: insta-lab/tests/test_trend_collector.py (NAVER part only; Google Trends added in Task 3)

• Step 1: Write the failing test (NAVER section) tests/test_trend_collector.py

import os
import gc
import tempfile
from unittest.mock import patch, MagicMock

import pytest

from app import db as db_module
from app import trend_collector


@pytest.fixture
def tmp_db(monkeypatch):
    fd, path = tempfile.mkstemp(suffix=".db")
    os.close(fd)
    monkeypatch.setattr(db_module, "DB_PATH", path)
    db_module.init_db()
    yield path
    gc.collect()
    for ext in ("", "-wal", "-shm"):
        try:
            os.remove(path + ext)
        except OSError:
            pass


NAVER_RESPONSE = {
    "items": [
        {"title": "<b>기준금리</b> 인상", "link": "https://n.news.naver.com/a/1", "description": "한국은행 발표"},
        {"title": "환율 급등", "link": "https://n.news.naver.com/a/2", "description": "달러 강세"},
        {"title": "기준금리 추가 인상", "link": "https://n.news.naver.com/a/3", "description": "추가 발표"},
    ],
}


def test_fetch_naver_popular_extracts_top_terms(tmp_db, monkeypatch):
    fake_resp = MagicMock()
    fake_resp.json.return_value = NAVER_RESPONSE
    fake_resp.raise_for_status.return_value = None

    # NAVER search는 카테고리 시드 키워드 각각에 대해 호출됨. 한 번만 mock해도 모두 같은 응답
    with patch.object(trend_collector.requests, "get", return_value=fake_resp):
        trends = trend_collector.fetch_naver_popular("economy", per_seed=10, top_n=5)

    keywords = [t["keyword"] for t in trends]
    assert "기준금리" in keywords  # 빈도 2회로 상위
    for t in trends:
        assert t["category"] == "economy"
        assert t["source"] == "naver_popular"
        assert 0.0 <= t["score"] <= 1.0


def test_collect_naver_writes_to_db(tmp_db, monkeypatch):
    fake_resp = MagicMock()
    fake_resp.json.return_value = NAVER_RESPONSE
    fake_resp.raise_for_status.return_value = None
    with patch.object(trend_collector.requests, "get", return_value=fake_resp):
        n = trend_collector.collect_naver_popular_for(["economy"])
    assert n > 0
    rows = db_module.list_trends(source="naver_popular")
    assert len(rows) > 0
    assert all(r["source"] == "naver_popular" for r in rows)

• Step 2: Run test, expect failure

Run: cd insta-lab && pytest tests/test_trend_collector.py -v Expected: ImportError on app.trend_collector.

• Step 3: Implement insta-lab/app/trend_collector.py (NAVER section)

"""외부 트렌드 수집 — NAVER 인기 + Google Trends + LLM 카테고리 분류.

Phase 1 (this file revision): NAVER 인기만. Google Trends는 Task 3에서 추가.
"""

import logging
import time
from typing import Any, Dict, List, Optional

import requests

from .config import (
    NAVER_CLIENT_ID, NAVER_CLIENT_SECRET, DEFAULT_CATEGORY_SEEDS,
)
from . import db
from .news_collector import _clean
from .keyword_extractor import _count_nouns, _top_candidates

logger = logging.getLogger(__name__)

NEWS_URL = "https://openapi.naver.com/v1/search/news.json"
_NAVER_HEADERS = {
    "X-Naver-Client-Id": NAVER_CLIENT_ID,
    "X-Naver-Client-Secret": NAVER_CLIENT_SECRET,
}


def _seeds_for(category: str) -> List[str]:
    pt = db.get_prompt_template("category_seeds")
    if pt and pt.get("template"):
        import json
        try:
            data = json.loads(pt["template"])
            if category in data:
                return list(data[category])
        except Exception:
            pass
    return list(DEFAULT_CATEGORY_SEEDS.get(category, []))


def fetch_naver_popular(category: str, per_seed: int = 30, top_n: int = 10) -> List[Dict[str, Any]]:
    """카테고리 시드 키워드들로 NAVER news.json `sort=sim`(정확도=인기 시그널) 호출,
    응답 기사 묶음에서 빈도어 추출 후 상위 N개 반환.

    Returns: list of {keyword, category, source='naver_popular', score (0~1)}
    """
    seeds = _seeds_for(category)
    if not seeds:
        return []
    blob_parts: List[str] = []
    for seed in seeds:
        try:
            resp = requests.get(
                NEWS_URL,
                headers=_NAVER_HEADERS,
                params={"query": seed, "display": per_seed, "sort": "sim"},
                timeout=10,
            )
            resp.raise_for_status()
            for item in resp.json().get("items", []):
                blob_parts.append(_clean(item.get("title", "")))
                blob_parts.append(_clean(item.get("description", "")))
        except Exception as e:
            logger.warning("fetch_naver_popular seed=%s err=%s", seed, e)
            continue
    text = "\n".join(blob_parts)
    counts = _count_nouns(text)
    candidates = _top_candidates(counts, n=top_n)
    if not candidates:
        return []
    max_count = candidates[0][1] or 1
    return [
        {
            "keyword": k,
            "category": category,
            "source": "naver_popular",
            "score": round(min(1.0, c / max_count), 4),
            "articles_count": c,
        }
        for k, c in candidates
    ]


def collect_naver_popular_for(categories: List[str]) -> int:
    """각 카테고리에 대해 fetch_naver_popular 호출 후 DB 저장. 저장된 row 수 반환."""
    total = 0
    for cat in categories:
        trends = fetch_naver_popular(cat)
        for t in trends:
            db.add_external_trend(t)
            total += 1
    return total

• Step 4: Run test, expect pass

Run: cd insta-lab && pytest tests/test_trend_collector.py -v Expected: 2 PASS.

• Step 5: Commit

git add insta-lab/app/trend_collector.py insta-lab/tests/test_trend_collector.py
git commit -m "feat(insta-lab): trend_collector with NAVER popular fetcher"

---

Task 3: trend_collector — Google Trends + LLM category classification

Files:

• Modify: insta-lab/app/trend_collector.py (append Google Trends part + cache)

• Modify: insta-lab/tests/test_trend_collector.py (append Google Trends tests)

• Step 1: Append failing tests to tests/test_trend_collector.py

Add at the end of the file:

def test_classify_keyword_with_cache(monkeypatch):
    """LLM이 호출되면 결과를 캐시. 두 번째 같은 키워드는 cache hit."""
    calls = {"n": 0}

    def fake_claude(keyword: str) -> str:
        calls["n"] += 1
        return "economy"

    monkeypatch.setattr(trend_collector, "_llm_classify_one", fake_claude)
    trend_collector._category_cache.clear()

    c1 = trend_collector.classify_keyword("기준금리")
    c2 = trend_collector.classify_keyword("기준금리")
    assert c1 == c2 == "economy"
    assert calls["n"] == 1  # cache hit second time


def test_fetch_google_trends_parses_and_classifies(tmp_db, monkeypatch):
    # pytrends client mock
    class FakePyTrends:
        def __init__(self, *_a, **_kw):
            pass

        def trending_searches(self, pn="south_korea"):
            import pandas as pd
            return pd.DataFrame({"0": ["기준금리", "BTS 컴백", "스트레스 관리"]})

    monkeypatch.setattr(trend_collector, "TrendReq", FakePyTrends)
    monkeypatch.setattr(trend_collector, "classify_keyword",
                        lambda kw: {"기준금리": "economy", "BTS 컴백": "celebrity",
                                    "스트레스 관리": "psychology"}.get(kw, "uncategorized"))

    trends = trend_collector.fetch_google_trends()
    by_kw = {t["keyword"]: t for t in trends}
    assert by_kw["기준금리"]["category"] == "economy"
    assert by_kw["BTS 컴백"]["category"] == "celebrity"
    assert by_kw["스트레스 관리"]["category"] == "psychology"
    assert all(t["source"] == "google_trends" for t in trends)


def test_collect_all_invokes_both_sources(tmp_db, monkeypatch):
    monkeypatch.setattr(trend_collector, "collect_naver_popular_for",
                        lambda cats: 5)
    monkeypatch.setattr(trend_collector, "collect_google_trends",
                        lambda: 3)
    out = trend_collector.collect_all(["economy"])
    assert out == {"naver_popular": 5, "google_trends": 3}


def test_fetch_google_trends_graceful_on_pytrends_failure(monkeypatch):
    class FakePyTrends:
        def __init__(self, *_a, **_kw):
            pass

        def trending_searches(self, pn="south_korea"):
            raise RuntimeError("rate limited")

    monkeypatch.setattr(trend_collector, "TrendReq", FakePyTrends)
    out = trend_collector.fetch_google_trends()
    assert out == []

• Step 2: Run tests, expect failures (new four fail)

Run: cd insta-lab && pytest tests/test_trend_collector.py -v Expected: 2 old PASS + 4 new FAIL on undefined symbols.

• Step 3: Extend insta-lab/app/trend_collector.py

At the top of the file, after the existing imports, ADD:

import json
import re
from anthropic import Anthropic
from pytrends.request import TrendReq

from .config import ANTHROPIC_API_KEY, ANTHROPIC_MODEL_HAIKU

_CACHE_TTL_SEC = 24 * 3600
_category_cache: Dict[str, tuple] = {}  # keyword -> (category, expires_ts)


def _llm_classify_one(keyword: str) -> str:
    """Claude Haiku 1회 호출로 단일 키워드 분류. 카테고리는 prompt_templates의
    category_seeds 키 집합 + 'uncategorized'."""
    if not ANTHROPIC_API_KEY:
        return "uncategorized"
    seeds_template = db.get_prompt_template("category_seeds")
    if seeds_template and seeds_template.get("template"):
        try:
            allowed = sorted(json.loads(seeds_template["template"]).keys())
        except Exception:
            allowed = sorted(DEFAULT_CATEGORY_SEEDS.keys())
    else:
        allowed = sorted(DEFAULT_CATEGORY_SEEDS.keys())
    allowed.append("uncategorized")

    client = Anthropic(api_key=ANTHROPIC_API_KEY)
    msg = client.messages.create(
        model=ANTHROPIC_MODEL_HAIKU,
        max_tokens=20,
        messages=[{
            "role": "user",
            "content": (
                f"다음 한국어 트렌딩 키워드를 카테고리 중 하나로 분류해라. "
                f"카테고리: {allowed}. 키워드: '{keyword}'. "
                f"카테고리명 한 단어만 출력. 다른 텍스트 금지."
            ),
        }],
    )
    raw = msg.content[0].text.strip().lower()
    for cat in allowed:
        if cat.lower() in raw:
            return cat
    return "uncategorized"


def classify_keyword(keyword: str) -> str:
    now = time.time()
    cached = _category_cache.get(keyword)
    if cached and cached[1] > now:
        return cached[0]
    cat = _llm_classify_one(keyword)
    _category_cache[keyword] = (cat, now + _CACHE_TTL_SEC)
    return cat


def fetch_google_trends() -> List[Dict[str, Any]]:
    """pytrends로 한국 daily trending searches. 실패 시 빈 리스트 graceful degrade."""
    try:
        pytrends = TrendReq(hl="ko-KR", tz=540)
        df = pytrends.trending_searches(pn="south_korea")
    except Exception as e:
        logger.warning("Google Trends fetch failed: %s", e)
        return []

    items: List[Dict[str, Any]] = []
    # df는 단일 컬럼 DataFrame이거나 "0"이 컬럼명. iter row 단순.
    for idx, row in df.iterrows():
        kw = str(row.iloc[0]).strip()
        if not kw:
            continue
        cat = classify_keyword(kw)
        # score는 순위 기반 정규화 (상위가 1.0에 가까움)
        rank_score = round(max(0.0, 1.0 - (idx / max(1, len(df)))), 4)
        items.append({
            "keyword": kw,
            "category": cat,
            "source": "google_trends",
            "score": rank_score,
            "articles_count": 0,
        })
    return items


def collect_google_trends() -> int:
    items = fetch_google_trends()
    for it in items:
        db.add_external_trend(it)
    return len(items)


def collect_all(categories: List[str]) -> Dict[str, int]:
    """전체 트렌드 수집 (NAVER 인기 + Google Trends 동시). 각 source별 저장 row 수 반환."""
    naver_n = collect_naver_popular_for(categories)
    google_n = collect_google_trends()
    return {"naver_popular": naver_n, "google_trends": google_n}

• Step 4: Run all trend_collector tests, expect pass

Run: cd insta-lab && pytest tests/test_trend_collector.py -v Expected: 6 PASS.

• Step 5: Commit

git add insta-lab/app/trend_collector.py insta-lab/tests/test_trend_collector.py
git commit -m "feat(insta-lab): trend_collector adds Google Trends + LLM category classification"

---

Task 4: keyword_extractor — extract_with_weights

Files:

• Modify: insta-lab/app/keyword_extractor.py

• Create: insta-lab/tests/test_extract_with_weights.py

• Step 1: Write the failing test

import os
import gc
import tempfile
from unittest.mock import patch

import pytest

from app import db as db_module
from app import keyword_extractor


@pytest.fixture
def tmp_db(monkeypatch):
    fd, path = tempfile.mkstemp(suffix=".db")
    os.close(fd)
    monkeypatch.setattr(db_module, "DB_PATH", path)
    db_module.init_db()
    yield path
    gc.collect()
    for ext in ("", "-wal", "-shm"):
        try:
            os.remove(path + ext)
        except OSError:
            pass


def test_extract_with_weights_proportional(tmp_db, monkeypatch):
    calls = []

    def fake_extract(category, limit):
        calls.append((category, limit))
        return [{"id": i, "keyword": f"{category}{i}", "category": category, "score": 0.5}
                for i in range(limit)]

    monkeypatch.setattr(keyword_extractor, "extract_for_category", fake_extract)
    out = keyword_extractor.extract_with_weights(
        {"economy": 0.6, "psychology": 0.3, "celebrity": 0.1}, total_limit=10,
    )
    # 6:3:1 비율 → round(10*0.6)=6, round(10*0.3)=3, round(10*0.1)=1
    by_cat = {c: l for c, l in calls}
    assert by_cat == {"economy": 6, "psychology": 3, "celebrity": 1}
    assert len(out) == 10


def test_extract_with_weights_skips_zero(tmp_db, monkeypatch):
    calls = []

    def fake_extract(category, limit):
        calls.append((category, limit))
        return []

    monkeypatch.setattr(keyword_extractor, "extract_for_category", fake_extract)
    keyword_extractor.extract_with_weights(
        {"economy": 1.0, "celebrity": 0.0}, total_limit=10,
    )
    assert ("celebrity", ...) not in [(c, ...) for c, _ in calls]
    assert any(c == "economy" for c, _ in calls)


def test_extract_with_weights_fallback_to_equal(tmp_db, monkeypatch):
    calls = []

    def fake_extract(category, limit):
        calls.append((category, limit))
        return []

    monkeypatch.setattr(keyword_extractor, "extract_for_category", fake_extract)
    keyword_extractor.extract_with_weights({}, total_limit=9)
    # DEFAULT_CATEGORY_SEEDS 기본 3개 균등 → 각 3
    by_cat = {c: l for c, l in calls}
    assert set(by_cat.keys()) == {"economy", "psychology", "celebrity"}
    assert all(l == 3 for l in by_cat.values())

• Step 2: Run test, expect failure

Run: cd insta-lab && pytest tests/test_extract_with_weights.py -v Expected: AttributeError on extract_with_weights.

• Step 3: Implement — append to insta-lab/app/keyword_extractor.py:

def extract_with_weights(weights: Dict[str, float], total_limit: int) -> List[Dict[str, Any]]:
    """카테고리 가중치 비율대로 키워드를 분배 추출."""
    from .config import DEFAULT_CATEGORY_SEEDS
    if not weights or sum(weights.values()) == 0:
        cats = list(DEFAULT_CATEGORY_SEEDS.keys())
        weights = {c: 1.0 for c in cats}

    total_weight = sum(weights.values())
    out: List[Dict[str, Any]] = []
    for category, w in weights.items():
        if w <= 0:
            continue
        per_cat = round(total_limit * w / total_weight)
        if per_cat <= 0:
            continue
        out.extend(extract_for_category(category, limit=per_cat))
    return out

• Step 4: Run test, expect pass

Run: cd insta-lab && pytest tests/test_extract_with_weights.py -v Expected: 3 PASS.

• Step 5: Commit

git add insta-lab/app/keyword_extractor.py insta-lab/tests/test_extract_with_weights.py
git commit -m "feat(insta-lab): keyword_extractor.extract_with_weights for category proportions"

---

Task 5: main.py — 4 new endpoints

Files:

• Modify: insta-lab/app/main.py

• Create: insta-lab/tests/test_main_trends.py

• Step 1: Write the failing test

import os
import gc
import tempfile

import pytest
from fastapi.testclient import TestClient

from app import db as db_module


@pytest.fixture
def client(monkeypatch):
    fd, path = tempfile.mkstemp(suffix=".db")
    os.close(fd)
    monkeypatch.setattr(db_module, "DB_PATH", path)
    db_module.init_db()
    from app import main
    monkeypatch.setattr(main, "DB_PATH", path)
    with TestClient(main.app) as c:
        yield c
    gc.collect()
    for ext in ("", "-wal", "-shm"):
        try:
            os.remove(path + ext)
        except OSError:
            pass


def test_get_preferences_returns_defaults(client):
    resp = client.get("/api/insta/preferences")
    assert resp.status_code == 200
    cats = {p["category"]: p["weight"] for p in resp.json()["categories"]}
    assert cats == {"economy": 1.0, "psychology": 1.0, "celebrity": 1.0}


def test_put_preferences_upsert(client):
    resp = client.put("/api/insta/preferences",
                      json={"categories": {"economy": 0.7, "psychology": 0.2, "tech": 0.5}})
    assert resp.status_code == 200
    cats = {p["category"]: p["weight"] for p in resp.json()["categories"]}
    assert cats["economy"] == 0.7
    assert cats["tech"] == 0.5


def test_list_trends_filter(client):
    db_module.add_external_trend({"keyword": "A", "category": "economy",
                                  "source": "naver_popular", "score": 1.0})
    db_module.add_external_trend({"keyword": "B", "category": "celebrity",
                                  "source": "google_trends", "score": 0.8})
    resp = client.get("/api/insta/trends?source=naver_popular")
    items = resp.json()["items"]
    assert {it["keyword"] for it in items} == {"A"}


def test_collect_trends_kicks_background(client, monkeypatch):
    from app import main, trend_collector

    captured = {"called": False}

    def fake_collect_all(cats):
        captured["called"] = True
        return {"naver_popular": 3, "google_trends": 2}

    monkeypatch.setattr(trend_collector, "collect_all", fake_collect_all)
    resp = client.post("/api/insta/trends/collect", json={})
    assert resp.status_code == 200
    task_id = resp.json()["task_id"]
    # poll
    for _ in range(20):
        st = client.get(f"/api/insta/tasks/{task_id}").json()
        if st["status"] in ("succeeded", "failed"):
            break
    assert st["status"] == "succeeded"
    assert captured["called"] is True


def test_list_keywords_filters_by_source(client):
    db_module.add_trending_keyword({"keyword": "M", "category": "economy",
                                    "score": 0.4, "articles_count": 1, "source": "manual"})
    db_module.add_external_trend({"keyword": "N", "category": "economy",
                                  "source": "naver_popular", "score": 0.9})
    resp = client.get("/api/insta/keywords?source=manual")
    items = resp.json()["items"]
    assert {it["keyword"] for it in items} == {"M"}

• Step 2: Run test, expect failure

Run: cd insta-lab && pytest tests/test_main_trends.py -v Expected: 404s and missing endpoints.

• Step 3: Edit insta-lab/app/main.py — add imports at top (around the existing import section):

from . import db, news_collector, keyword_extractor, card_writer, card_renderer, trend_collector

(Add , trend_collector to the existing line.)

Then append (at end of file or near existing endpoints, before any if __name__):

# ── Trends ───────────────────────────────────────────────────────
class TrendsCollectRequest(BaseModel):
    categories: Optional[list[str]] = None


async def _bg_collect_trends(task_id: str, categories: list[str]):
    try:
        db.update_task(task_id, "processing", 10, "외부 트렌드 수집 중")
        result = trend_collector.collect_all(categories)
        msg = f"naver:{result['naver_popular']}, google:{result['google_trends']}"
        db.update_task(task_id, "succeeded", 100, msg, result_id=sum(result.values()))
    except Exception as e:
        logger.exception("trends collect failed")
        db.update_task(task_id, "failed", 0, "", error=str(e))


@app.post("/api/insta/trends/collect")
def collect_trends(req: TrendsCollectRequest, bg: BackgroundTasks):
    cats = req.categories or list(DEFAULT_CATEGORY_SEEDS.keys())
    tid = db.create_task("trends_collect", {"categories": cats})
    bg.add_task(_bg_collect_trends, tid, cats)
    return {"task_id": tid, "categories": cats}


@app.get("/api/insta/trends")
def list_trends_endpoint(
    source: Optional[str] = None,
    category: Optional[str] = None,
    days: int = Query(1, ge=1, le=90),
):
    return {"items": db.list_trends(source=source, category=category, days=days)}


# ── Preferences ──────────────────────────────────────────────────
class PreferencesBody(BaseModel):
    categories: dict[str, float]


@app.get("/api/insta/preferences")
def get_preferences_endpoint():
    return {"categories": db.get_preferences()}


@app.put("/api/insta/preferences")
def put_preferences_endpoint(body: PreferencesBody):
    db.upsert_preferences(body.categories)
    return {"categories": db.get_preferences()}

Then modify the existing list_keywords endpoint to add a source filter. Find:

@app.get("/api/insta/keywords")
def list_keywords(category: Optional[str] = None, used: Optional[bool] = None):
    return {"items": db.list_trending_keywords(category=category, used=used)}

Replace with:

@app.get("/api/insta/keywords")
def list_keywords(
    category: Optional[str] = None,
    used: Optional[bool] = None,
    source: Optional[str] = None,
):
    if source:
        # source 필터는 list_trends 경로 사용 (동일 테이블, source 컬럼 활용)
        return {"items": db.list_trends(source=source, category=category, days=30)}
    return {"items": db.list_trending_keywords(category=category, used=used)}

• Step 4: Run test, expect pass

Run: cd insta-lab && pytest tests/test_main_trends.py -v Expected: 5 PASS.

• Step 5: Full insta-lab suite

Run: cd insta-lab && pytest -v Expected: All prior tests still pass + new tests. Total ~33 tests, 0 failures.

• Step 6: Commit

git add insta-lab/app/main.py insta-lab/tests/test_main_trends.py
git commit -m "feat(insta-lab): main.py — trends + preferences endpoints"

---

Task 6: agent-office InstaAgent — weighted extract + new collect_trends action

Files:

• Modify: agent-office/app/agents/insta.py

• Modify: agent-office/app/service_proxy.py

• Create: agent-office/tests/test_insta_agent_trends.py

• Step 1: Add service_proxy helpers

In agent-office/app/service_proxy.py, in the # --- insta-lab --- section, append:

async def insta_collect_trends(categories: Optional[list] = None) -> Dict[str, Any]:
    payload = {"categories": categories} if categories else {}
    resp = await _client.post(f"{INSTA_LAB_URL}/api/insta/trends/collect", json=payload)
    resp.raise_for_status()
    return resp.json()


async def insta_list_trends(source: Optional[str] = None,
                            category: Optional[str] = None,
                            days: int = 1) -> List[Dict[str, Any]]:
    params: Dict[str, Any] = {"days": days}
    if source:
        params["source"] = source
    if category:
        params["category"] = category
    resp = await _client.get(f"{INSTA_LAB_URL}/api/insta/trends", params=params)
    resp.raise_for_status()
    return resp.json().get("items", [])


async def insta_get_preferences() -> Dict[str, float]:
    resp = await _client.get(f"{INSTA_LAB_URL}/api/insta/preferences")
    resp.raise_for_status()
    return {p["category"]: p["weight"] for p in resp.json().get("categories", [])}


async def insta_put_preferences(weights: Dict[str, float]) -> Dict[str, Any]:
    resp = await _client.put(
        f"{INSTA_LAB_URL}/api/insta/preferences",
        json={"categories": weights},
    )
    resp.raise_for_status()
    return resp.json()

• Step 2: Write failing test agent-office/tests/test_insta_agent_trends.py

from unittest.mock import AsyncMock

import pytest

from app.agents.insta import InstaAgent


@pytest.mark.asyncio
async def test_on_command_collect_trends_dispatches(monkeypatch):
    agent = InstaAgent()
    fake_collect = AsyncMock(return_value={"task_id": "tcollect"})
    fake_status = AsyncMock(return_value={"status": "succeeded", "result_id": 8,
                                          "message": "naver:5, google:3"})

    monkeypatch.setattr("app.agents.insta.service_proxy.insta_collect_trends", fake_collect)
    monkeypatch.setattr("app.agents.insta.service_proxy.insta_task_status", fake_status)
    monkeypatch.setattr("app.agents.insta.messaging.send_raw", AsyncMock(return_value={"ok": True}))

    result = await agent.on_command("collect_trends", {})
    assert result["ok"] is True
    fake_collect.assert_awaited()


@pytest.mark.asyncio
async def test_on_schedule_applies_preferences(monkeypatch):
    """on_schedule이 preferences를 가져와 가중치 정보를 활용하는지 확인."""
    agent = InstaAgent()

    fake_collect = AsyncMock(return_value={"task_id": "t1"})
    fake_extract = AsyncMock(return_value={"task_id": "t2"})
    fake_status = AsyncMock(side_effect=[
        {"status": "succeeded", "result_id": 0},
        {"status": "succeeded", "result_id": 0},
    ])
    fake_keywords = AsyncMock(return_value=[
        {"id": 1, "keyword": "K", "category": "economy", "score": 0.9},
    ])
    fake_prefs = AsyncMock(return_value={"economy": 0.6, "psychology": 0.4})

    monkeypatch.setattr("app.agents.insta.service_proxy.insta_collect", fake_collect)
    monkeypatch.setattr("app.agents.insta.service_proxy.insta_extract", fake_extract)
    monkeypatch.setattr("app.agents.insta.service_proxy.insta_task_status", fake_status)
    monkeypatch.setattr("app.agents.insta.service_proxy.insta_list_keywords", fake_keywords)
    monkeypatch.setattr("app.agents.insta.service_proxy.insta_get_preferences", fake_prefs)
    monkeypatch.setattr("app.agents.insta.messaging.send_raw", AsyncMock(return_value={"ok": True}))

    # 상태 idle로 강제
    agent.state = "idle"
    await agent.on_schedule()

    fake_prefs.assert_awaited()

• Step 3: Run test, expect failure

Run: cd agent-office && pytest tests/test_insta_agent_trends.py -v Expected: AttributeError on insta_get_preferences or test setup error.

• Step 4: Modify agent-office/app/agents/insta.py

In on_command, add a new branch (append to the if-elif chain before the final return):

        if command == "collect_trends":
            await messaging.send_raw("🌐 외부 트렌드 수집 시작")
            created = await service_proxy.insta_collect_trends()
            st = await self._wait_task(created["task_id"], step="trends_collect", timeout_sec=300)
            await messaging.send_raw(f"✅ 트렌드 수집 완료: {st.get('message', '')}")
            return {"ok": True, "result": st}

In on_schedule, BEFORE the existing _run_collect_and_extract call, add preference loading. Find the try block:

        try:
            await self._run_collect_and_extract()
            kws = await service_proxy.insta_list_keywords(used=False)
            ...

Replace with:

        try:
            prefs = await service_proxy.insta_get_preferences()
            add_log(self.agent_id, f"insta preferences: {prefs}", "info", task_id)
            await self._run_collect_and_extract()
            kws = await service_proxy.insta_list_keywords(used=False)
            ...

(Note: actual weight application happens in insta-lab's extract_with_weights. For now agent-office just calls extract — the extract endpoint will be updated to read preferences in Task 7. We log prefs for visibility.)

• Step 5: Run test, expect pass

Run: cd agent-office && pytest tests/test_insta_agent_trends.py -v Expected: 2 PASS.

• Step 6: Run full agent-office suite

Run: cd agent-office && pytest -v Expected: All prior tests + new 2 pass. (1 pre-existing test_init_and_seed failure unrelated.)

• Step 7: Commit

git add agent-office/app/agents/insta.py agent-office/app/service_proxy.py agent-office/tests/test_insta_agent_trends.py
git commit -m "feat(agent-office): InstaAgent collect_trends action + preferences-aware on_schedule"

---

Task 7: insta-lab keywords/extract uses preferences + agent-office scheduler 09:00 cron

Files:

• Modify: insta-lab/app/main.py (extract endpoint reads preferences)

• Modify: agent-office/app/scheduler.py

• Step 1: Modify insta-lab/app/main.py — _bg_extract reads preferences

Find:

async def _bg_extract(task_id: str, categories: list[str]):
    try:
        db.update_task(task_id, "processing", 10, "추출 중")
        for cat in categories:
            keyword_extractor.extract_for_category(cat, limit=KEYWORDS_PER_CATEGORY)
        db.update_task(task_id, "succeeded", 100, "완료", result_id=0)
    except Exception as e:
        logger.exception("extract failed")
        db.update_task(task_id, "failed", 0, "", error=str(e))

Replace with:

async def _bg_extract(task_id: str, categories: Optional[list[str]] = None):
    try:
        db.update_task(task_id, "processing", 10, "추출 중")
        prefs_rows = db.get_preferences()
        weights = {p["category"]: p["weight"] for p in prefs_rows}
        if categories:
            # 사용자가 카테고리 명시한 경우만 그 서브셋으로 균등 가중치 (override)
            weights = {c: 1.0 for c in categories}
        total = KEYWORDS_PER_CATEGORY * max(1, len([w for w in weights.values() if w > 0]))
        keyword_extractor.extract_with_weights(weights, total_limit=total)
        db.update_task(task_id, "succeeded", 100, "완료", result_id=0)
    except Exception as e:
        logger.exception("extract failed")
        db.update_task(task_id, "failed", 0, "", error=str(e))

• Step 2: Run the existing test_main.py to confirm no regression

Run: cd insta-lab && pytest tests/test_main.py -v Expected: 5 PASS (the existing test_create_slate_kicks_background_task should still pass since it uses fake_render/fake_write; the extract is called only from agent-office, not here).

• Step 3: Add scheduler cron for 09:00 trends collect

In agent-office/app/scheduler.py, add a function near _run_insta_schedule:

async def _run_insta_trends_collect():
    agent = AGENT_REGISTRY.get("insta")
    if agent:
        await agent.on_command("collect_trends", {})

In init_scheduler, add (after the existing insta_pipeline cron line):

    scheduler.add_job(_run_insta_trends_collect, "cron", hour=9, minute=0, id="insta_trends_collect")

• Step 4: Sanity check imports + scheduler load

Run:

cd agent-office && python -c "from app.scheduler import init_scheduler; from app.agents import init_agents, AGENT_REGISTRY; init_agents(); print(list(AGENT_REGISTRY.keys())); print('scheduler imports OK')"

Expected: List includes 'insta' and prints scheduler imports OK.

• Step 5: Commit

git add insta-lab/app/main.py agent-office/app/scheduler.py
git commit -m "feat(insta): extract uses preferences + 09:00 trends_collect cron"

---

Task 8: web-ui — api.js helpers

Files:

• Modify: web-ui/src/api.js

Work in the web-ui repo (separate from web-backend). All commits on main.

• Step 1: Open web-ui terminal and confirm branch

cd /c/Users/jaeoh/Desktop/workspace/web-ui
git status --short
git branch --show-current

Expected: clean working tree, main.

• Step 2: Append helpers in src/api.js — after the existing // ── insta-lab ── block, add:

// ── insta-lab trends ──
export function getInstaTrends({ source, category, days = 1 } = {}) {
  const q = new URLSearchParams();
  if (source) q.set('source', source);
  if (category) q.set('category', category);
  q.set('days', String(days));
  return apiGet(`/api/insta/trends?${q.toString()}`);
}

export function instaCollectTrends(categories) {
  return apiPost('/api/insta/trends/collect', categories ? { categories } : {});
}

export function getInstaPreferences() {
  return apiGet('/api/insta/preferences');
}

export function putInstaPreferences(categories) {
  return apiPut('/api/insta/preferences', { categories });
}

• Step 3: Verify with grep

grep -nE "getInstaTrends|instaCollectTrends|getInstaPreferences|putInstaPreferences" src/api.js

Expected: 4 hits.

• Step 4: Commit (no commit yet — bundle with Task 9 UI changes for cleaner PR)

Skip commit; continue to Task 9.

---

Task 9: web-ui — Insta page tabs + 3 trend panels

Files:

• Modify: web-ui/src/pages/insta/InstaCards.jsx

• Modify: web-ui/src/pages/insta/InstaCards.css

• Step 1: Re-read current InstaCards.jsx structure

cd /c/Users/jaeoh/Desktop/workspace/web-ui
sed -n '1,30p' src/pages/insta/InstaCards.jsx

Identify the default-export function InstaCards (around line 96 per spec). Note where each existing panel is rendered.

• Step 2: Add tab state + tab bar at the top of the InstaCards function. Right before the existing JSX return:

const [activeTab, setActiveTab] = useState(() => {
  const u = new URL(window.location.href);
  return u.searchParams.get('tab') === 'trends' ? 'trends' : 'cards';
});

const switchTab = (next) => {
  setActiveTab(next);
  const u = new URL(window.location.href);
  if (next === 'cards') u.searchParams.delete('tab');
  else u.searchParams.set('tab', next);
  window.history.replaceState({}, '', u.toString());
};

2a. Locate the existing JSX return. Inside InstaCards(), find the block that renders <PullToRefresh> + <TriggerPanel /> + <KeywordsPanel onCreateSlate={...} /> + <SlatesPanel ... /> + <SlateDetail .../> + <PromptTemplatesEditor />. That is the "cards" composition.

2b. Extract the create-slate callback. Locate the function/closure passed to KeywordsPanel as onCreateSlate. If it's defined inline, lift it into a named const inside InstaCards so both KeywordsPanel and the new ExternalTrendsPanel can call it:

const handleCreateSlate = async ({ keyword, category, keyword_id }) => {
  // ... whatever the existing inline handler does (POST /api/insta/slates + poll task + refresh slates)
};

Pass it to KeywordsPanel (existing) AND ExternalTrendsPanel (new).

2c. Replace the JSX return with TabBar + conditional panels:

return (
  <div className="ic">
    <div className="ic-tabbar">
      <button
        className={`ic-tab ${activeTab === 'cards' ? 'is-active' : ''}`}
        onClick={() => switchTab('cards')}
      >🎴 Cards</button>
      <button
        className={`ic-tab ${activeTab === 'trends' ? 'is-active' : ''}`}
        onClick={() => switchTab('trends')}
      >📈 Trends</button>
    </div>

    {activeTab === 'cards' && (
      <>
        {/* PASTE the existing PullToRefresh + 5 panels block exactly as it was */}
      </>
    )}

    {activeTab === 'trends' && (
      <div className="ic-trends-grid">
        <AccountFocusPanel />
        <ExternalTrendsPanel onCreateSlate={handleCreateSlate} />
        <PreferenceImpactPanel />
      </div>
    )}
  </div>
);

The {/* PASTE ... */} comment is a literal instruction to the implementer: keep the previously-existing JSX intact, only wrap it in the activeTab === 'cards' conditional.

• Step 3: Add new imports at the top of InstaCards.jsx

Find the existing import { ... } from '../../api' block and add:

import {
  getInstaTrends,
  instaCollectTrends,
  getInstaPreferences,
  putInstaPreferences,
  getInstaTask,
} from '../../api';

(Some may already exist — dedupe.)

• Step 4: Implement AccountFocusPanel component

Append before export default function InstaCards():

function AccountFocusPanel() {
  const [prefs, setPrefs] = useState([]);
  const [draft, setDraft] = useState({});
  const [saving, setSaving] = useState(false);
  const [newCat, setNewCat] = useState('');

  const load = useCallback(async () => {
    const data = await getInstaPreferences();
    setPrefs(data.categories || []);
    const m = {};
    (data.categories || []).forEach(p => { m[p.category] = Math.round(p.weight * 100); });
    setDraft(m);
  }, []);

  useEffect(() => { load(); }, [load]);

  const save = async () => {
    setSaving(true);
    try {
      const payload = {};
      Object.entries(draft).forEach(([k, v]) => { payload[k] = (Number(v) || 0) / 100; });
      await putInstaPreferences(payload);
      await load();
    } finally { setSaving(false); }
  };

  const addCat = () => {
    const name = newCat.trim().toLowerCase();
    if (!name || draft[name] !== undefined) return;
    setDraft({ ...draft, [name]: 0 });
    setNewCat('');
  };

  return (
    <section className="ic-panel ic-panel--focus">
      <h3 className="ic-panel__title">🎯 이 계정의 주제 (카테고리 가중치)</h3>
      <p className="ic-panel__hint">슬라이더는 각 카테고리에 자동 추출 키워드 비율을 결정합니다. 합계는 자동 정규화됩니다.</p>
      <div className="ic-focus__list">
        {Object.entries(draft).map(([cat, val]) => (
          <div key={cat} className="ic-focus__row">
            <label className="ic-focus__label">{cat}</label>
            <input
              type="range" min="0" max="100" value={val}
              onChange={e => setDraft({ ...draft, [cat]: Number(e.target.value) })}
              className="ic-focus__slider"
            />
            <span className="ic-focus__num">{val}%</span>
          </div>
        ))}
      </div>
      <div className="ic-focus__add">
        <input
          type="text" placeholder="신규 카테고리 (영문 소문자)"
          value={newCat} onChange={e => setNewCat(e.target.value)}
        />
        <button onClick={addCat}>+ 추가</button>
      </div>
      <button className="ic-focus__save" onClick={save} disabled={saving}>
        {saving ? '저장 중...' : '저장'}
      </button>
      <div className="ic-focus__hint">
        💡 신규 카테고리를 추가했다면 Cards 탭의 Prompt Templates Editor에서
        <code>category_seeds</code>에 시드 키워드도 함께 정의해야 자동 추출에 반영됩니다.
      </div>
    </section>
  );
}

• Step 5: Implement ExternalTrendsPanel

const CATEGORY_COLORS = {
  economy: '#0F62FE', psychology: '#A66CFF',
  celebrity: '#FF5C8A', uncategorized: '#6B7280',
};

function ExternalTrendsPanel({ onCreateSlate }) {
  const [naver, setNaver] = useState([]);
  const [google, setGoogle] = useState([]);
  const [lastFetched, setLastFetched] = useState(null);
  const [collecting, setCollecting] = useState(false);
  const [task, setTask] = useState(null);

  const load = useCallback(async () => {
    const [n, g] = await Promise.all([
      getInstaTrends({ source: 'naver_popular', days: 2 }),
      getInstaTrends({ source: 'google_trends', days: 2 }),
    ]);
    setNaver(n.items || []);
    setGoogle(g.items || []);
    const all = [...(n.items || []), ...(g.items || [])];
    if (all.length) {
      const latest = all.map(t => t.suggested_at).sort().reverse()[0];
      setLastFetched(latest);
    }
  }, []);

  useEffect(() => { load(); }, [load]);

  const trigger = async () => {
    setCollecting(true);
    try {
      const { task_id } = await instaCollectTrends();
      let st = null;
      for (let i = 0; i < 60; i++) {
        st = await getInstaTask(task_id);
        setTask(st);
        if (st.status === 'succeeded' || st.status === 'failed') break;
        await new Promise(r => setTimeout(r, 3000));
      }
      await load();
    } finally { setCollecting(false); }
  };

  const groupByCat = (items) => {
    const g = {};
    items.forEach(it => { (g[it.category] = g[it.category] || []).push(it); });
    return g;
  };

  const renderRow = (t) => (
    <div className="ic-trend__row" key={`${t.source}-${t.id}`}>
      <span className="ic-trend__cat-dot" style={{ background: CATEGORY_COLORS[t.category] || '#6B7280' }} />
      <span className="ic-trend__kw">{t.keyword}</span>
      <span className="ic-trend__score">{(t.score || 0).toFixed(2)}</span>
      <button
        className="ic-trend__make"
        onClick={() => onCreateSlate?.({ keyword: t.keyword, category: t.category })}
      >🎴</button>
    </div>
  );

  const naverGrouped = groupByCat(naver);
  return (
    <section className="ic-panel ic-panel--trends">
      <div className="ic-panel__head">
        <h3 className="ic-panel__title">📈 외부 트렌드</h3>
        <div className="ic-panel__actions">
          <span className="ic-panel__hint">
            {lastFetched ? `마지막 수집: ${fmtDate(lastFetched)}` : '아직 수집 없음'}
          </span>
          <button onClick={trigger} disabled={collecting}>
            {collecting ? '수집 중...' : '🔄 수동 수집'}
          </button>
        </div>
      </div>
      {task && <TaskStatusBox task={task} />}
      <div className="ic-trends__cols">
        <div className="ic-trends__col">
          <h4>🔥 NAVER 인기</h4>
          {Object.keys(naverGrouped).length === 0 && <p className="ic-empty">없음</p>}
          {Object.entries(naverGrouped).map(([cat, items]) => (
            <div key={cat} className="ic-trend__group">
              <div className="ic-trend__group-head" style={{ color: CATEGORY_COLORS[cat] || '#6B7280' }}>{cat}</div>
              {items.map(renderRow)}
            </div>
          ))}
        </div>
        <div className="ic-trends__col">
          <h4>🌐 Google Trends</h4>
          {google.length === 0 && <p className="ic-empty">없음</p>}
          {google.map(renderRow)}
        </div>
      </div>
    </section>
  );
}

• Step 6: Implement PreferenceImpactPanel

function PreferenceImpactPanel() {
  const [prefs, setPrefs] = useState([]);
  const TOTAL = 15;

  useEffect(() => {
    (async () => {
      const data = await getInstaPreferences();
      setPrefs(data.categories || []);
    })();
  }, []);

  const totalWeight = prefs.reduce((s, p) => s + (p.weight || 0), 0) || 1;
  const breakdown = prefs.map(p => ({
    category: p.category,
    count: Math.round(TOTAL * (p.weight || 0) / totalWeight),
  }));

  return (
    <section className="ic-panel ic-panel--impact">
      <h3 className="ic-panel__title">📊 다음 자동 추출 미리보기</h3>
      <div className="ic-impact__row">
        {breakdown.map(b => (
          <div key={b.category} className="ic-impact__chip">
            <span className="ic-impact__cat">{b.category}</span>
            <span className="ic-impact__count">{b.count}개</span>
          </div>
        ))}
      </div>
    </section>
  );
}

• Step 7: Add CSS to InstaCards.css — append:

/* ── tabs ── */
.ic-tabbar { display: flex; gap: 8px; border-bottom: 1px solid #e2e8f0; margin-bottom: 16px; }
.ic-tab {
  background: transparent; border: 0; padding: 10px 16px;
  cursor: pointer; font-size: 14px; font-weight: 600;
  color: #64748b; border-bottom: 2px solid transparent;
}
.ic-tab.is-active { color: #ec4899; border-bottom-color: #ec4899; }

/* ── trends grid ── */
.ic-trends-grid { display: grid; gap: 16px; grid-template-columns: 1fr; }
@media (min-width: 1024px) { .ic-trends-grid { grid-template-columns: 320px 1fr; } }

/* ── focus panel ── */
.ic-panel--focus .ic-focus__list { display: flex; flex-direction: column; gap: 10px; margin: 12px 0; }
.ic-focus__row { display: grid; grid-template-columns: 110px 1fr 50px; align-items: center; gap: 8px; }
.ic-focus__label { font-weight: 600; color: #475569; text-transform: capitalize; }
.ic-focus__slider { width: 100%; accent-color: #ec4899; }
.ic-focus__num { text-align: right; font-variant-numeric: tabular-nums; color: #475569; }
.ic-focus__add { display: flex; gap: 8px; margin-top: 12px; }
.ic-focus__add input { flex: 1; padding: 8px; border: 1px solid #cbd5e1; border-radius: 6px; }
.ic-focus__save {
  width: 100%; padding: 10px; margin-top: 12px;
  background: #ec4899; color: #fff; border: 0; border-radius: 6px; cursor: pointer;
  font-weight: 700;
}
.ic-focus__hint { margin-top: 12px; padding: 10px; background: #fef3c7; border-left: 3px solid #f59e0b; font-size: 12px; }
.ic-focus__hint code { background: rgba(0,0,0,0.06); padding: 1px 4px; border-radius: 3px; }

/* ── trends panel ── */
.ic-trends__cols { display: grid; grid-template-columns: 1fr; gap: 16px; }
@media (min-width: 768px) { .ic-trends__cols { grid-template-columns: 1fr 1fr; } }
.ic-trends__col h4 { margin: 0 0 8px; font-size: 14px; color: #475569; }
.ic-trend__group { margin-bottom: 14px; }
.ic-trend__group-head { font-size: 12px; font-weight: 700; text-transform: uppercase; margin-bottom: 4px; letter-spacing: 0.5px; }
.ic-trend__row {
  display: grid; grid-template-columns: 10px 1fr 50px 36px;
  align-items: center; gap: 8px; padding: 6px 4px;
  border-bottom: 1px solid #f1f5f9;
}
.ic-trend__cat-dot { width: 10px; height: 10px; border-radius: 50%; }
.ic-trend__kw { font-weight: 500; }
.ic-trend__score { text-align: right; color: #64748b; font-variant-numeric: tabular-nums; font-size: 12px; }
.ic-trend__make { background: #ec4899; border: 0; color: #fff; border-radius: 4px; cursor: pointer; padding: 4px; }
.ic-trend__make:hover { background: #db2777; }
.ic-empty { color: #94a3b8; font-style: italic; padding: 8px 0; }

.ic-panel__head { display: flex; justify-content: space-between; align-items: center; margin-bottom: 12px; }
.ic-panel__actions { display: flex; gap: 8px; align-items: center; }

/* ── impact panel ── */
.ic-impact__row { display: flex; flex-wrap: wrap; gap: 8px; }
.ic-impact__chip {
  display: flex; align-items: baseline; gap: 6px;
  padding: 6px 12px; background: #f1f5f9; border-radius: 999px;
}
.ic-impact__cat { font-weight: 600; text-transform: capitalize; color: #475569; }
.ic-impact__count { color: #ec4899; font-weight: 700; }

• Step 8: Build to verify

cd /c/Users/jaeoh/Desktop/workspace/web-ui
npm run build

Expected: exit 0. If errors, READ them and fix (most likely typos or unused imports). DO NOT push broken builds.

• Step 9: Commit (Tasks 8 + 9 together)

git add src/api.js src/pages/insta/InstaCards.jsx src/pages/insta/InstaCards.css
git commit -m "feat(insta): Trends tab — account focus + external trends + impact preview"
git push origin main

---

Task 10: Backend integration + push + smoke

Files: none (verification only)

• Step 1: Backend — push insta-trends feature branch

cd /c/Users/jaeoh/Desktop/workspace/web-backend
git log --oneline main..feat/insta-trends

Expected: 7-8 commits (Tasks 0 through 7).

git push -u origin feat/insta-trends

• Step 2: Create PR via Gitea UI (the push response prints the URL). Title: feat(insta): Trends tab — external sources + category weights.

• Step 3: After merge, NAS deployer runs automatically:

  • rsync (new trend_collector.py, requirements.txt with pytrends)
  • Dockerfile cache invalidates at the requirements.txt COPY step → pip installs pytrends → ~30s longer build
  • Containers stop/rm/up; health check via docker inspect

• Step 4: Verify post-deploy on NAS

# from NAS
curl http://localhost:18700/api/insta/preferences
# → {"categories":[{"category":"economy","weight":1.0,...},{"category":"psychology",...},{"category":"celebrity",...}]}

curl -X POST http://localhost:18700/api/insta/trends/collect -H "Content-Type: application/json" -d '{}'
# → {"task_id":"<id>","categories":[...]}
# poll task → succeeded with message "naver:N, google:M"

curl http://localhost:18700/api/insta/trends?source=google_trends
# → items list with category classified by Claude

• Step 5: Frontend deploy (manual per workspace CLAUDE.md):

cd C:\Users\jaeoh\Desktop\workspace
scripts\deploy.bat --frontend

Then visit http://localhost:8080/insta?tab=trends (or gahusb.synology.me:8080/insta?tab=trends). Expected: tabs visible, Trends tab shows 3 panels, slider responds, 수동 수집 버튼 작동.

• Step 6: agent-office cron verification

Check agent-office logs the next day at 09:00:

docker logs agent-office --tail 50 | grep -i "trends_collect\|insta_trends"

Expected: a log entry near 09:00 with successful collect_trends.

---

Verification matrix (before declaring done)

Check	Command	Expected
insta-lab tests	cd insta-lab && pytest -v	All pass (≥33 tests)
agent-office tests	cd agent-office && pytest -v	All pass + 2 new (pre-existing test_init_and_seed failure remains unrelated)
web-ui build	cd web-ui && npm run build	exit 0
backend grep	grep -rn "trend_collector|insta_collect_trends|extract_with_weights|account_preferences" insta-lab/ agent-office/	non-empty (wiring exists)
frontend grep	grep -rn "AccountFocusPanel|ExternalTrendsPanel|PreferenceImpactPanel|/api/insta/trends|/api/insta/preferences" web-ui/src/	non-empty
post-deploy preferences	curl localhost:18700/api/insta/preferences	3 default categories with weight=1.0
post-deploy trends collect	curl -X POST localhost:18700/api/insta/trends/collect -d '{}' then poll	succeeded with non-zero result_id
frontend tab visible	Visit /insta?tab=trends	3 panels render