# saju-lab 신설 + tarot-lab 분리 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. **Goal:** agent-office에 종속된 tarot을 독립 tarot-lab 컨테이너로 분리하고, 별도 디렉토리의 saju-web을 saju-lab 컨테이너로 마이그레이션 (Python FastAPI + Claude + SQLite 패턴). **Architecture:** Phase 1은 코드 복사 + DB 1회 마이그레이션 + agent-office cutover. Phase 2는 TypeScript 계산 엔진을 Python으로 reference-output 비교 테스트 기반 포팅 + Claude AI 해석 파이프라인 (tarot 패턴 재활용) + 사주/궁합 v1 endpoint. 두 lab 모두 `insta-lab`/`music-lab`과 동일 디렉토리 구조. **Tech Stack:** Python 3.12 + FastAPI 0.115 + httpx + Pydantic V2 + SQLite WAL + Anthropic Claude Sonnet 4.6 (prompt-caching) + sxtwl (Python 만세력) + pytest + respx (httpx mock). **Reference spec:** `docs/superpowers/specs/2026-05-25-saju-tarot-lab-migration-design.md` --- ## Phase 1 — tarot-lab 분리 ### Task 1: tarot-lab 스캐폴딩 (Dockerfile + requirements + pytest.ini) **Files:** - Create: `tarot-lab/Dockerfile` - Create: `tarot-lab/requirements.txt` - Create: `tarot-lab/pytest.ini` - Create: `tarot-lab/.dockerignore` - Create: `tarot-lab/app/__init__.py` - Create: `tarot-lab/tests/__init__.py` - [ ] **Step 1: Dockerfile 작성 (insta-lab 패턴)** ```dockerfile FROM python:3.12-slim-bookworm ENV PYTHONUNBUFFERED=1 WORKDIR /app COPY requirements.txt . RUN pip install --no-cache-dir --timeout 600 --retries 5 -r requirements.txt COPY . . EXPOSE 8000 CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1"] ``` - [ ] **Step 2: requirements.txt 작성** ``` fastapi==0.115.6 uvicorn[standard]==0.34.0 httpx>=0.27 pydantic>=2.9 pytest>=8.0 pytest-asyncio>=0.24 respx>=0.21 ``` - [ ] **Step 3: pytest.ini 작성** ```ini [pytest] asyncio_mode = auto pythonpath = . ``` - [ ] **Step 4: .dockerignore 작성** ``` __pycache__ *.pyc .pytest_cache data/ tests/ ``` - [ ] **Step 5: 빈 app/__init__.py, tests/__init__.py 생성** 빈 파일 2개 생성: - `tarot-lab/app/__init__.py` - `tarot-lab/tests/__init__.py` - [ ] **Step 6: 디렉토리 구조 확인** Run: `ls tarot-lab/ tarot-lab/app/ tarot-lab/tests/` Expected: 각각 파일 존재 확인 - [ ] **Step 7: Commit** ```bash git add tarot-lab/Dockerfile tarot-lab/requirements.txt tarot-lab/pytest.ini tarot-lab/.dockerignore tarot-lab/app/__init__.py tarot-lab/tests/__init__.py git commit -m "feat(tarot-lab): 스캐폴딩 — Dockerfile + requirements + pytest" ``` --- ### Task 2: tarot-lab config.py + models.py **Files:** - Create: `tarot-lab/app/config.py` - Create: `tarot-lab/app/models.py` - [ ] **Step 1: app/config.py 작성** ```python """tarot-lab 환경변수.""" import os ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY", "") TAROT_MODEL = os.getenv("TAROT_MODEL", "claude-sonnet-4-6") TAROT_COST_INPUT_PER_M = float(os.getenv("TAROT_COST_INPUT_PER_M", "3.0")) TAROT_COST_OUTPUT_PER_M = float(os.getenv("TAROT_COST_OUTPUT_PER_M", "15.0")) TAROT_TIMEOUT_SEC = int(os.getenv("TAROT_TIMEOUT_SEC", "180")) TAROT_DATA_PATH = os.getenv("TAROT_DATA_PATH", "/app/data") DB_PATH = os.path.join(TAROT_DATA_PATH, "tarot.db") CORS_ALLOW_ORIGINS = os.getenv( "CORS_ALLOW_ORIGINS", "http://localhost:3007,http://localhost:8080", ) ``` - [ ] **Step 2: app/models.py 작성** ```python """Tarot Pydantic 모델 — agent-office models.py에서 추출.""" from typing import List, Literal, Optional from pydantic import BaseModel, Field class TarotCardDraw(BaseModel): position: str card_id: str reversed: bool = False class TarotInterpretRequest(BaseModel): spread_type: Literal["one_card", "three_card"] category: Optional[str] = None question: Optional[str] = None cards: List[TarotCardDraw] cards_reference: str = Field(..., min_length=1) context_meta: dict = Field(default_factory=dict) class TarotInterpretResponse(BaseModel): interpretation_json: dict model: str tokens_in: int tokens_out: int cost_usd: float latency_ms: int reroll_count: int = 0 class TarotSaveRequest(BaseModel): spread_type: Literal["one_card", "three_card"] category: Optional[str] = None question: Optional[str] = None cards: List[TarotCardDraw] interpretation_json: dict model: str tokens_in: int tokens_out: int cost_usd: float confidence: Optional[str] = None class TarotPatchRequest(BaseModel): favorite: Optional[bool] = None note: Optional[str] = None ``` - [ ] **Step 3: Commit** ```bash git add tarot-lab/app/config.py tarot-lab/app/models.py git commit -m "feat(tarot-lab): config + Pydantic 모델 5개 추출" ``` --- ### Task 3: tarot-lab db.py (CRUD 5 + _tarot_row_to_dict + init_db) **Files:** - Create: `tarot-lab/app/db.py` - Create: `tarot-lab/tests/test_db.py` - [ ] **Step 1: 실패 테스트 작성 (test_db.py)** ```python import os import pytest from app import db as db_module @pytest.fixture(autouse=True) def fresh_db(monkeypatch, tmp_path): db_file = tmp_path / "test_tarot.db" monkeypatch.setattr(db_module, "DB_PATH", str(db_file)) db_module.init_db() yield try: if db_file.exists(): db_file.unlink() except PermissionError: pass # Windows SQLite WAL 잠금 def test_save_and_get(): rid = db_module.save_tarot_reading({ "spread_type": "three_card", "category": "연애", "question": "Q", "cards": [{"position": "과거", "card_id": "the-fool", "reversed": False}], "interpretation_json": {"summary": "S", "cards": [], "interactions": [], "advice": "A", "warning": None, "confidence": "medium"}, "model": "claude-sonnet-4-6", "tokens_in": 100, "tokens_out": 200, "cost_usd": 0.005, "confidence": "medium", }) assert rid > 0 row = db_module.get_tarot_reading(rid) assert row["id"] == rid assert row["category"] == "연애" assert row["interpretation_json"]["summary"] == "S" assert row["favorite"] == 0 def test_list_with_filters(): for cat in ["연애", "연애", "재물"]: db_module.save_tarot_reading({ "spread_type": "three_card", "category": cat, "question": "Q", "cards": [], "interpretation_json": {"summary": "S", "cards": [], "interactions": [], "advice": "", "warning": None, "confidence": "low"}, "model": "x", "tokens_in": 0, "tokens_out": 0, "cost_usd": 0.0, "confidence": "low", }) res = db_module.list_tarot_readings(page=1, size=10, category="연애") assert res["total"] == 2 assert all(r["category"] == "연애" for r in res["items"]) def test_update_favorite_and_note(): rid = db_module.save_tarot_reading({ "spread_type": "one_card", "category": None, "question": None, "cards": [], "interpretation_json": None, "model": "x", "tokens_in": 0, "tokens_out": 0, "cost_usd": 0.0, "confidence": None, }) db_module.update_tarot_reading(rid, favorite=True, note="좋아요") row = db_module.get_tarot_reading(rid) assert row["favorite"] == 1 assert row["note"] == "좋아요" def test_delete(): rid = db_module.save_tarot_reading({ "spread_type": "one_card", "category": None, "question": None, "cards": [], "interpretation_json": None, "model": "x", "tokens_in": 0, "tokens_out": 0, "cost_usd": 0.0, "confidence": None, }) db_module.delete_tarot_reading(rid) assert db_module.get_tarot_reading(rid) is None ``` - [ ] **Step 2: Run test, verify it fails** Run: `cd tarot-lab && python -m pytest tests/test_db.py -v` Expected: FAIL (`ModuleNotFoundError: No module named 'app.db'`) - [ ] **Step 3: app/db.py 작성 (agent-office db.py에서 추출 + DB_PATH 변경)** ```python """tarot.db SQLite — 5 CRUD + _tarot_row_to_dict + init_db.""" import json import os import sqlite3 from typing import Any, Dict, Optional from .config import DB_PATH # noqa: F401 (test가 monkeypatch로 덮어씀) from . import config def _conn() -> sqlite3.Connection: os.makedirs(os.path.dirname(config.DB_PATH), exist_ok=True) conn = sqlite3.connect(config.DB_PATH, timeout=120.0) conn.row_factory = sqlite3.Row conn.execute("PRAGMA journal_mode=WAL") conn.execute("PRAGMA busy_timeout=120000") return conn def init_db() -> None: with _conn() as conn: conn.execute(""" CREATE TABLE IF NOT EXISTS tarot_readings ( id INTEGER PRIMARY KEY AUTOINCREMENT, created_at TEXT NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ','now')), spread_type TEXT NOT NULL, category TEXT, question TEXT, cards TEXT NOT NULL, interpretation_json TEXT, summary TEXT, model TEXT, tokens_in INTEGER, tokens_out INTEGER, cost_usd REAL, confidence TEXT, favorite INTEGER NOT NULL DEFAULT 0, note TEXT ) """) conn.execute(""" CREATE INDEX IF NOT EXISTS idx_tarot_created ON tarot_readings(created_at DESC) """) conn.execute(""" CREATE INDEX IF NOT EXISTS idx_tarot_favorite ON tarot_readings(favorite, created_at DESC) """) def save_tarot_reading(data: Dict[str, Any]) -> int: interp = data.get("interpretation_json") or {} summary = interp.get("summary", "") if isinstance(interp, dict) else "" with _conn() as conn: cur = conn.execute( """INSERT INTO tarot_readings (spread_type, category, question, cards, interpretation_json, summary, model, tokens_in, tokens_out, cost_usd, confidence) VALUES (?,?,?,?,?,?,?,?,?,?,?)""", ( data["spread_type"], data.get("category"), data.get("question"), json.dumps(data.get("cards") or [], ensure_ascii=False), json.dumps(interp, ensure_ascii=False) if interp else None, summary, data.get("model"), data.get("tokens_in"), data.get("tokens_out"), data.get("cost_usd"), data.get("confidence"), ), ) return int(cur.lastrowid) def get_tarot_reading(reading_id: int) -> Optional[Dict[str, Any]]: with _conn() as conn: r = conn.execute("SELECT * FROM tarot_readings WHERE id=?", (reading_id,)).fetchone() return _tarot_row_to_dict(r) if r else None def list_tarot_readings( page: int = 1, size: int = 20, favorite: Optional[bool] = None, spread_type: Optional[str] = None, category: Optional[str] = None, ) -> Dict[str, Any]: wheres, params = [], [] if favorite is not None: wheres.append("favorite=?") params.append(1 if favorite else 0) if spread_type: wheres.append("spread_type=?") params.append(spread_type) if category: wheres.append("category=?") params.append(category) where_sql = ("WHERE " + " AND ".join(wheres)) if wheres else "" offset = (page - 1) * size with _conn() as conn: total = conn.execute( f"SELECT COUNT(*) c FROM tarot_readings {where_sql}", params ).fetchone()["c"] rows = conn.execute( f"SELECT * FROM tarot_readings {where_sql} ORDER BY created_at DESC LIMIT ? OFFSET ?", params + [size, offset], ).fetchall() return { "items": [_tarot_row_to_dict(r) for r in rows], "page": page, "size": size, "total": int(total), } def update_tarot_reading(reading_id: int, **kwargs) -> None: sets, vals = [], [] if "favorite" in kwargs and kwargs["favorite"] is not None: sets.append("favorite=?") vals.append(1 if kwargs["favorite"] else 0) if "note" in kwargs and kwargs["note"] is not None: sets.append("note=?") vals.append(kwargs["note"]) if not sets: return vals.append(reading_id) with _conn() as conn: conn.execute(f"UPDATE tarot_readings SET {','.join(sets)} WHERE id=?", vals) def delete_tarot_reading(reading_id: int) -> None: with _conn() as conn: conn.execute("DELETE FROM tarot_readings WHERE id=?", (reading_id,)) def _tarot_row_to_dict(r) -> Dict[str, Any]: try: interp = json.loads(r["interpretation_json"]) if r["interpretation_json"] else None except (ValueError, TypeError): interp = None try: cards = json.loads(r["cards"]) if r["cards"] else [] except (ValueError, TypeError): cards = [] return { "id": r["id"], "created_at": r["created_at"], "spread_type": r["spread_type"], "category": r["category"], "question": r["question"], "cards": cards, "interpretation_json": interp, "summary": r["summary"], "model": r["model"], "tokens_in": r["tokens_in"], "tokens_out": r["tokens_out"], "cost_usd": r["cost_usd"], "confidence": r["confidence"], "favorite": int(r["favorite"]), "note": r["note"], } ``` **중요한 변경점**: monkeypatch가 `db_module.DB_PATH`를 덮어쓸 수 있도록 `_conn()` 내부에서 `config.DB_PATH`를 매번 읽어옴. agent-office는 `from .config import DB_PATH`로 import 하지만 테스트 monkeypatch가 module-level 변수를 덮어쓰는 패턴이 더 안정적. 수정: 테스트에서 `monkeypatch.setattr(db_module, "DB_PATH", str(db_file))`로 db_module 자체의 DB_PATH를 덮어쓰므로, db.py 안에서 `DB_PATH`를 직접 참조해야 함. 다시 작성: ```python import json import os import sqlite3 from typing import Any, Dict, Optional from .config import DB_PATH def _conn() -> sqlite3.Connection: os.makedirs(os.path.dirname(DB_PATH), exist_ok=True) conn = sqlite3.connect(DB_PATH, timeout=120.0) # ... 이하 동일 ``` 테스트의 `monkeypatch.setattr(db_module, "DB_PATH", ...)`가 module의 `DB_PATH` (import된 값)를 직접 덮어쓰므로 정상 동작. - [ ] **Step 4: Run tests, verify they pass** Run: `cd tarot-lab && python -m pytest tests/test_db.py -v` Expected: 4 passed - [ ] **Step 5: Commit** ```bash git add tarot-lab/app/db.py tarot-lab/tests/test_db.py git commit -m "feat(tarot-lab): db.py CRUD 5 + init_db (테스트 4건 통과)" ``` --- ### Task 4: tarot-lab prompt.py + schema.py 이관 **Files:** - Create: `tarot-lab/app/prompt.py` - Create: `tarot-lab/app/schema.py` - Create: `tarot-lab/tests/test_schema.py` - [ ] **Step 1: app/prompt.py — agent-office/app/tarot/prompt.py 그대로 복사** `agent-office/app/tarot/prompt.py` 내용을 `tarot-lab/app/prompt.py`로 그대로 복사. 외부 import 없음 (자체완결). - [ ] **Step 2: app/schema.py — agent-office/app/tarot/schema.py 그대로 복사** `agent-office/app/tarot/schema.py` 내용을 `tarot-lab/app/schema.py`로 그대로 복사. 외부 import 없음. - [ ] **Step 3: tests/test_schema.py 작성 (agent-office/tests/test_tarot_schema.py 이관 + import 경로 변경)** ```python from app.schema import validate_interpretation def _valid_card(): return { "position": "과거", "card": "the-fool", "reversed": False, "interpretation": "...", "advice": "...", "evidence": { "card_meaning_used": "새 시작", "position_logic": "...", "category_lens": "...", }, } def _valid_payload(): return { "summary": "...", "cards": [_valid_card()], "interactions": [{"type": "synergy", "between": ["a", "b"], "explanation": "..."}], "advice": "...", "confidence": "medium", } def test_valid_three_card(): ok, _ = validate_interpretation(_valid_payload(), "three_card") assert ok is True def test_missing_summary(): p = _valid_payload(); del p["summary"] ok, err = validate_interpretation(p, "three_card") assert not ok and "summary" in err def test_invalid_confidence(): p = _valid_payload(); p["confidence"] = "extreme" ok, err = validate_interpretation(p, "three_card") assert not ok and "confidence" in err def test_three_card_empty_interactions(): p = _valid_payload(); p["interactions"] = [] ok, err = validate_interpretation(p, "three_card") assert not ok and "interactions" in err def test_one_card_empty_interactions_ok(): p = _valid_payload(); p["interactions"] = [] ok, _ = validate_interpretation(p, "one_card") assert ok is True def test_card_evidence_missing_field(): p = _valid_payload() del p["cards"][0]["evidence"]["category_lens"] ok, err = validate_interpretation(p, "three_card") assert not ok and "category_lens" in err ``` - [ ] **Step 4: Run tests** Run: `cd tarot-lab && python -m pytest tests/test_schema.py -v` Expected: 6 passed - [ ] **Step 5: Commit** ```bash git add tarot-lab/app/prompt.py tarot-lab/app/schema.py tarot-lab/tests/test_schema.py git commit -m "feat(tarot-lab): prompt.py + schema.py 이관 + 검증 테스트 6건" ``` --- ### Task 5: tarot-lab pipeline.py 이관 (import 경로 수정) **Files:** - Create: `tarot-lab/app/pipeline.py` - Create: `tarot-lab/tests/test_pipeline.py` - [ ] **Step 1: app/pipeline.py — agent-office/app/tarot/pipeline.py 복사 + import 변경** `agent-office/app/tarot/pipeline.py` 그대로 복사하되, 두 줄만 변경: - `from ..config import (...)` → `from .config import (...)` - `from ..models import TarotInterpretRequest` → `from .models import TarotInterpretRequest` 전체 코드 (변경 후 모습): ```python """Tarot 파이프라인 — Claude Sonnet 호출 + 파싱 폴백 + reroll 1회.""" import json import logging import time from typing import Any, Dict import httpx from .config import ( ANTHROPIC_API_KEY, TAROT_MODEL, TAROT_COST_INPUT_PER_M, TAROT_COST_OUTPUT_PER_M, TAROT_TIMEOUT_SEC, ) logger = logging.getLogger("tarot-lab.pipeline") from .models import TarotInterpretRequest from .prompt import SYSTEM_PROMPT, build_user_message from .schema import validate_interpretation API_URL = "https://api.anthropic.com/v1/messages" class TarotError(Exception): pass def calc_cost(tokens_in: int, tokens_out: int) -> float: return ( tokens_in / 1_000_000 * TAROT_COST_INPUT_PER_M + tokens_out / 1_000_000 * TAROT_COST_OUTPUT_PER_M ) def _strip_codeblock(text: str) -> str: t = text.strip() if t.startswith("```"): t = t.strip("`") if t.startswith("json"): t = t[4:] t = t.strip() return t def _extract_json(raw: str) -> dict: cleaned = _strip_codeblock(raw) try: return json.loads(cleaned) except json.JSONDecodeError: start, end = cleaned.find("{"), cleaned.rfind("}") if start >= 0 and end > start: try: return json.loads(cleaned[start : end + 1]) except json.JSONDecodeError: pass raise async def _call_claude(user_text: str, feedback: str = "") -> tuple[dict, dict, str]: if not ANTHROPIC_API_KEY: raise TarotError("ANTHROPIC_API_KEY missing") if feedback: user_text = f"이전 응답이 다음 이유로 거절됨: {feedback}\n올바른 스키마(시스템 지침)로 다시 응답.\n\n{user_text}" payload = { "model": TAROT_MODEL, "max_tokens": 1400, "system": [{"type": "text", "text": SYSTEM_PROMPT, "cache_control": {"type": "ephemeral"}}], "messages": [{"role": "user", "content": [{"type": "text", "text": user_text}]}], } headers = { "x-api-key": ANTHROPIC_API_KEY, "anthropic-version": "2023-06-01", "anthropic-beta": "prompt-caching-2024-07-31", "content-type": "application/json", } started = time.monotonic() async with httpx.AsyncClient(timeout=TAROT_TIMEOUT_SEC) as client: r = await client.post(API_URL, headers=headers, json=payload) r.raise_for_status() resp = r.json() latency_ms = int((time.monotonic() - started) * 1000) raw_text = "".join( b.get("text", "") for b in resp.get("content", []) if b.get("type") == "text" ) usage = resp.get("usage", {}) or {} tokens_in = int(usage.get("input_tokens", 0) or 0) tokens_out = int(usage.get("output_tokens", 0) or 0) logger.info("tarot claude call: latency=%dms, in=%d, out=%d", latency_ms, tokens_in, tokens_out) parsed = _extract_json(raw_text) meta = {"tokens_in": tokens_in, "tokens_out": tokens_out, "latency_ms": latency_ms} return parsed, meta, raw_text async def interpret(req: TarotInterpretRequest) -> Dict[str, Any]: user_text = build_user_message( question=req.question or "", category=req.category or "", spread_type=req.spread_type, cards_reference=req.cards_reference, context_meta=req.context_meta or {}, spread_count=len(req.cards), ) total_in, total_out, total_latency = 0, 0, 0 last_error = "" for attempt in range(2): try: parsed, meta, _raw = await _call_claude(user_text, feedback=last_error) except httpx.HTTPError as e: raise TarotError(f"Claude HTTP error: {e}") from e except json.JSONDecodeError as e: last_error = f"JSON 파싱 실패: {e}" continue total_in += meta["tokens_in"] total_out += meta["tokens_out"] total_latency += meta["latency_ms"] ok, err = validate_interpretation(parsed, req.spread_type) if ok: return { "interpretation_json": parsed, "model": TAROT_MODEL, "tokens_in": total_in, "tokens_out": total_out, "cost_usd": calc_cost(total_in, total_out), "latency_ms": total_latency, "reroll_count": attempt, } last_error = err raise TarotError(f"검증 실패 (reroll 2회): {last_error}") ``` - [ ] **Step 2: tests/test_pipeline.py 작성** ```python import json import pytest import respx import httpx from app import pipeline from app.models import TarotInterpretRequest, TarotCardDraw @pytest.fixture(autouse=True) def _patch_key(monkeypatch): monkeypatch.setattr(pipeline, "ANTHROPIC_API_KEY", "test-key") def _req(): return TarotInterpretRequest( spread_type="three_card", category="연애", question="Q", cards=[ TarotCardDraw(position="과거", card_id="the-fool", reversed=False), TarotCardDraw(position="현재", card_id="the-magician", reversed=False), TarotCardDraw(position="미래", card_id="the-empress", reversed=True), ], cards_reference="...", ) def _valid_response_json(): return { "summary": "흐름이 있음", "cards": [ {"position": "과거", "card": "the-fool", "reversed": False, "interpretation": "...", "advice": "...", "evidence": {"card_meaning_used": "...", "position_logic": "...", "category_lens": "..."}}, {"position": "현재", "card": "the-magician", "reversed": False, "interpretation": "...", "advice": "...", "evidence": {"card_meaning_used": "...", "position_logic": "...", "category_lens": "..."}}, {"position": "미래", "card": "the-empress", "reversed": True, "interpretation": "...", "advice": "...", "evidence": {"card_meaning_used": "...", "position_logic": "...", "category_lens": "..."}}, ], "interactions": [{"type": "synergy", "between": ["the-fool", "the-magician"], "explanation": "..."}], "advice": "...", "warning": None, "confidence": "medium", } def _claude_envelope(text: str, in_tok=100, out_tok=200): return { "content": [{"type": "text", "text": text}], "usage": {"input_tokens": in_tok, "output_tokens": out_tok}, } @respx.mock async def test_interpret_success(): respx.post("https://api.anthropic.com/v1/messages").mock( return_value=httpx.Response(200, json=_claude_envelope(json.dumps(_valid_response_json()))) ) result = await pipeline.interpret(_req()) assert result["reroll_count"] == 0 assert result["model"] == pipeline.TAROT_MODEL assert result["tokens_in"] == 100 assert result["cost_usd"] > 0 @respx.mock async def test_interpret_codeblock_stripped(): text = "```json\n" + json.dumps(_valid_response_json()) + "\n```" respx.post("https://api.anthropic.com/v1/messages").mock( return_value=httpx.Response(200, json=_claude_envelope(text)) ) result = await pipeline.interpret(_req()) assert "interpretation_json" in result @respx.mock async def test_interpret_reroll_then_success(): valid = json.dumps(_valid_response_json()) invalid = json.dumps({"summary": "...", "cards": [], "interactions": [], "advice": "", "confidence": "medium"}) respx.post("https://api.anthropic.com/v1/messages").mock( side_effect=[ httpx.Response(200, json=_claude_envelope(invalid)), httpx.Response(200, json=_claude_envelope(valid)), ] ) result = await pipeline.interpret(_req()) assert result["reroll_count"] == 1 @respx.mock async def test_interpret_reroll_fail_raises(): invalid = json.dumps({"summary": "...", "cards": [], "interactions": [], "advice": "", "confidence": "medium"}) respx.post("https://api.anthropic.com/v1/messages").mock( return_value=httpx.Response(200, json=_claude_envelope(invalid)) ) with pytest.raises(pipeline.TarotError): await pipeline.interpret(_req()) @respx.mock async def test_interpret_http_error(): respx.post("https://api.anthropic.com/v1/messages").mock( return_value=httpx.Response(500, text="boom") ) with pytest.raises(pipeline.TarotError): await pipeline.interpret(_req()) def test_calc_cost(): cost = pipeline.calc_cost(1_000_000, 1_000_000) assert cost == pipeline.TAROT_COST_INPUT_PER_M + pipeline.TAROT_COST_OUTPUT_PER_M ``` - [ ] **Step 3: Run tests** Run: `cd tarot-lab && python -m pytest tests/test_pipeline.py -v` Expected: 6 passed - [ ] **Step 4: Commit** ```bash git add tarot-lab/app/pipeline.py tarot-lab/tests/test_pipeline.py git commit -m "feat(tarot-lab): pipeline.py 이관 + 6 테스트 통과" ``` --- ### Task 6: tarot-lab main.py + routes (6 endpoints) **Files:** - Create: `tarot-lab/app/main.py` - Create: `tarot-lab/tests/test_routes.py` - [ ] **Step 1: app/main.py 작성** ```python """tarot-lab FastAPI app — /api/tarot/* 6 endpoints.""" from fastapi import FastAPI, HTTPException from fastapi.middleware.cors import CORSMiddleware from .config import CORS_ALLOW_ORIGINS from .models import ( TarotInterpretRequest, TarotInterpretResponse, TarotSaveRequest, TarotPatchRequest, ) from . import pipeline, db as db_module app = FastAPI(title="tarot-lab") _origins = [o.strip() for o in CORS_ALLOW_ORIGINS.split(",") if o.strip()] app.add_middleware( CORSMiddleware, allow_origins=_origins, allow_credentials=False, allow_methods=["GET", "POST", "PATCH", "DELETE", "OPTIONS"], allow_headers=["Content-Type"], ) @app.on_event("startup") def _init(): db_module.init_db() @app.get("/health") def health(): return {"ok": True} @app.post("/api/tarot/interpret", response_model=TarotInterpretResponse) async def interpret_endpoint(req: TarotInterpretRequest): try: result = await pipeline.interpret(req) except pipeline.TarotError as e: raise HTTPException(status_code=500, detail=str(e)) from e return result @app.post("/api/tarot/readings") async def save_reading(req: TarotSaveRequest): rid = db_module.save_tarot_reading(req.model_dump()) row = db_module.get_tarot_reading(rid) return {"id": rid, "created_at": row["created_at"]} @app.get("/api/tarot/readings") async def list_readings( page: int = 1, size: int = 20, favorite: bool | None = None, spread_type: str | None = None, category: str | None = None, ): return db_module.list_tarot_readings( page=page, size=size, favorite=favorite, spread_type=spread_type, category=category, ) @app.get("/api/tarot/readings/{reading_id}") async def get_reading(reading_id: int): row = db_module.get_tarot_reading(reading_id) if not row: raise HTTPException(status_code=404, detail="reading not found") return row @app.patch("/api/tarot/readings/{reading_id}") async def patch_reading(reading_id: int, req: TarotPatchRequest): row = db_module.get_tarot_reading(reading_id) if not row: raise HTTPException(status_code=404, detail="reading not found") db_module.update_tarot_reading(reading_id, **req.model_dump(exclude_none=True)) return {"ok": True} @app.delete("/api/tarot/readings/{reading_id}") async def delete_reading(reading_id: int): row = db_module.get_tarot_reading(reading_id) if not row: raise HTTPException(status_code=404, detail="reading not found") db_module.delete_tarot_reading(reading_id) return {"ok": True} ``` - [ ] **Step 2: tests/test_routes.py 작성** ```python import pytest from fastapi.testclient import TestClient from app.main import app from app import db as db_module @pytest.fixture(autouse=True) def fresh_db(monkeypatch, tmp_path): db_file = tmp_path / "test_tarot.db" monkeypatch.setattr(db_module, "DB_PATH", str(db_file)) db_module.init_db() yield try: if db_file.exists(): db_file.unlink() except PermissionError: pass def _save_payload(): return { "spread_type": "three_card", "category": "연애", "question": "Q", "cards": [{"position": "과거", "card_id": "the-fool", "reversed": False}], "interpretation_json": {"summary": "S", "cards": [], "interactions": [], "advice": "A", "warning": None, "confidence": "medium"}, "model": "claude-sonnet-4-6", "tokens_in": 100, "tokens_out": 200, "cost_usd": 0.005, "confidence": "medium", } def test_health(): with TestClient(app) as c: r = c.get("/health") assert r.status_code == 200 assert r.json() == {"ok": True} def test_save_list_get_cycle(): with TestClient(app) as c: r = c.post("/api/tarot/readings", json=_save_payload()) assert r.status_code == 200 rid = r.json()["id"] r = c.get("/api/tarot/readings") assert r.json()["total"] == 1 r = c.get(f"/api/tarot/readings/{rid}") assert r.json()["category"] == "연애" def test_patch_favorite_and_note(): with TestClient(app) as c: rid = c.post("/api/tarot/readings", json=_save_payload()).json()["id"] r = c.patch(f"/api/tarot/readings/{rid}", json={"favorite": True, "note": "n"}) assert r.status_code == 200 row = c.get(f"/api/tarot/readings/{rid}").json() assert row["favorite"] == 1 assert row["note"] == "n" def test_delete(): with TestClient(app) as c: rid = c.post("/api/tarot/readings", json=_save_payload()).json()["id"] assert c.delete(f"/api/tarot/readings/{rid}").status_code == 200 assert c.get(f"/api/tarot/readings/{rid}").status_code == 404 def test_get_404(): with TestClient(app) as c: assert c.get("/api/tarot/readings/9999").status_code == 404 ``` - [ ] **Step 3: Run tests** Run: `cd tarot-lab && python -m pytest tests/test_routes.py -v` Expected: 5 passed - [ ] **Step 4: Run all tarot-lab tests** Run: `cd tarot-lab && python -m pytest -v` Expected: 21 passed (4 db + 6 schema + 6 pipeline + 5 routes) - [ ] **Step 5: Commit** ```bash git add tarot-lab/app/main.py tarot-lab/tests/test_routes.py git commit -m "feat(tarot-lab): main.py + 5 라우트 테스트 (총 21 tests 통과)" ``` --- ### Task 7: DB 마이그레이션 스크립트 **Files:** - Create: `agent-office/scripts/migrate_tarot_to_lab.py` - Create: `agent-office/tests/test_migrate_tarot.py` - [ ] **Step 1: 실패 테스트 작성** ```python """migrate_tarot_to_lab.py 단위 테스트 — 멱등성 + 데이터 보존.""" import json import sqlite3 import sys import os import pytest @pytest.fixture def src_db(tmp_path): p = tmp_path / "agent_office.db" conn = sqlite3.connect(str(p)) conn.execute(""" CREATE TABLE tarot_readings ( id INTEGER PRIMARY KEY AUTOINCREMENT, created_at TEXT, spread_type TEXT, category TEXT, question TEXT, cards TEXT, interpretation_json TEXT, summary TEXT, model TEXT, tokens_in INTEGER, tokens_out INTEGER, cost_usd REAL, confidence TEXT, favorite INTEGER, note TEXT ) """) conn.execute(""" INSERT INTO tarot_readings (id, spread_type, category, cards, model, favorite) VALUES (1, 'three_card', '연애', '[]', 'm', 0), (2, 'one_card', '재물', '[]', 'm', 1) """) conn.commit() conn.close() return str(p) @pytest.fixture def dst_db(tmp_path): return str(tmp_path / "tarot.db") def _import_migrate(src, dst, monkeypatch): # script 가 import 시점에 env 읽도록 monkeypatch monkeypatch.setenv("AGENT_OFFICE_DB", src) monkeypatch.setenv("TAROT_DB", dst) sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "scripts")) import migrate_tarot_to_lab as m import importlib importlib.reload(m) return m def test_first_run_copies_all_rows(src_db, dst_db, monkeypatch): m = _import_migrate(src_db, dst_db, monkeypatch) moved = m.migrate() assert moved == 2 conn = sqlite3.connect(dst_db) rows = conn.execute("SELECT id, spread_type, category FROM tarot_readings ORDER BY id").fetchall() conn.close() assert rows == [(1, "three_card", "연애"), (2, "one_card", "재물")] def test_idempotent_second_run(src_db, dst_db, monkeypatch): m = _import_migrate(src_db, dst_db, monkeypatch) m.migrate() moved2 = m.migrate() assert moved2 == 0 # 이미 다 옮겼으므로 0 def test_partial_migration(src_db, dst_db, monkeypatch): """dst에 id=1만 있는 상태에서 다시 돌리면 id=2만 옮김.""" m = _import_migrate(src_db, dst_db, monkeypatch) m.migrate() # dst에서 id=2 삭제 → 다시 마이그레이션하면 1건만 새로 들어가야 함 conn = sqlite3.connect(dst_db) conn.execute("DELETE FROM tarot_readings WHERE id=2") conn.commit() conn.close() moved = m.migrate() assert moved == 1 ``` - [ ] **Step 2: Run test, verify fails** Run: `cd agent-office && python -m pytest tests/test_migrate_tarot.py -v` Expected: FAIL (`ImportError: cannot import name 'migrate_tarot_to_lab'`) - [ ] **Step 3: scripts/migrate_tarot_to_lab.py 작성** ```python """1회성 마이그레이션 — agent_office.db.tarot_readings → tarot.db.tarot_readings. 멱등성: 이미 존재하는 id는 SKIP. 실행: docker exec agent-office python /app/scripts/migrate_tarot_to_lab.py 또는 호스트에서 직접: AGENT_OFFICE_DB=/path/to/agent_office.db TAROT_DB=/path/to/tarot.db \\ python scripts/migrate_tarot_to_lab.py """ import os import sqlite3 import sys SRC = os.getenv("AGENT_OFFICE_DB", "/app/data/agent_office.db") DST = os.getenv("TAROT_DB", "/app/data/tarot.db") SCHEMA = """ CREATE TABLE IF NOT EXISTS tarot_readings ( id INTEGER PRIMARY KEY AUTOINCREMENT, created_at TEXT NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ','now')), spread_type TEXT NOT NULL, category TEXT, question TEXT, cards TEXT NOT NULL, interpretation_json TEXT, summary TEXT, model TEXT, tokens_in INTEGER, tokens_out INTEGER, cost_usd REAL, confidence TEXT, favorite INTEGER NOT NULL DEFAULT 0, note TEXT ); """ def migrate() -> int: """이관된 row 수 반환.""" src = sqlite3.connect(SRC) src.row_factory = sqlite3.Row dst = sqlite3.connect(DST) dst.execute("PRAGMA journal_mode=WAL") dst.executescript(SCHEMA) rows = src.execute("SELECT * FROM tarot_readings").fetchall() if not rows: src.close(); dst.close() return 0 cols = list(rows[0].keys()) placeholders = ",".join("?" * len(cols)) cols_str = ",".join(cols) moved = 0 for r in rows: exists = dst.execute("SELECT 1 FROM tarot_readings WHERE id=?", (r["id"],)).fetchone() if exists: continue dst.execute( f"INSERT INTO tarot_readings ({cols_str}) VALUES ({placeholders})", tuple(r[c] for c in cols), ) moved += 1 dst.commit() src.close(); dst.close() return moved if __name__ == "__main__": moved = migrate() total = sqlite3.connect(SRC).execute("SELECT COUNT(*) FROM tarot_readings").fetchone()[0] print(f"migrated {moved} / {total} rows from {SRC} to {DST}") sys.exit(0 if moved >= 0 else 1) ``` - [ ] **Step 4: Run tests, verify pass** Run: `cd agent-office && python -m pytest tests/test_migrate_tarot.py -v` Expected: 3 passed - [ ] **Step 5: Commit** ```bash git add agent-office/scripts/migrate_tarot_to_lab.py agent-office/tests/test_migrate_tarot.py git commit -m "feat(agent-office): tarot_readings 1회성 마이그레이션 스크립트 (3 테스트)" ``` --- ### Task 8: docker-compose.yml에 tarot-lab 등록 **Files:** - Modify: `docker-compose.yml` - [ ] **Step 1: 현재 agent-office 항목 위치 확인** Run: `grep -n "agent-office:" docker-compose.yml | head -3` Expected: `agent-office:` 컨테이너 정의 시작 줄 번호 - [ ] **Step 2: docker-compose.yml에 tarot-lab service 추가** agent-office 항목 바로 다음에 다음 블록 삽입: ```yaml tarot-lab: build: context: ./tarot-lab container_name: tarot-lab restart: unless-stopped ports: - "18250:8000" environment: - TZ=${TZ:-Asia/Seoul} - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-} - TAROT_MODEL=${TAROT_MODEL:-claude-sonnet-4-6} - TAROT_COST_INPUT_PER_M=${TAROT_COST_INPUT_PER_M:-3.0} - TAROT_COST_OUTPUT_PER_M=${TAROT_COST_OUTPUT_PER_M:-15.0} - TAROT_TIMEOUT_SEC=${TAROT_TIMEOUT_SEC:-180} - TAROT_DATA_PATH=/app/data - CORS_ALLOW_ORIGINS=${CORS_ALLOW_ORIGINS:-http://localhost:3007,http://localhost:8080} volumes: - ${RUNTIME_PATH:-.}/data/tarot:/app/data healthcheck: test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"] interval: 60s timeout: 5s retries: 3 ``` - [ ] **Step 3: docker-compose.yml syntax 검증** Run: `docker compose config 2>&1 | head -50` Expected: tarot-lab section이 정상 파싱됨 (에러 없음) - [ ] **Step 4: Commit** ```bash git add docker-compose.yml git commit -m "feat(docker-compose): tarot-lab 컨테이너 추가 (18250 포트)" ``` --- ### Task 9: nginx /api/tarot/ 라우팅 추가 **Files:** - Modify: `nginx/default.conf` - [ ] **Step 1: /api/agent-office/ location 바로 앞에 tarot 추가** `nginx/default.conf`의 `# agent-office API + WebSocket` 위에 다음 블록 삽입: ```nginx # tarot-lab API (agent-office에서 분리) location /api/tarot/ { resolver 127.0.0.11 valid=10s; set $tarot_backend tarot-lab:8000; proxy_http_version 1.1; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_read_timeout 300s; proxy_send_timeout 300s; proxy_connect_timeout 60s; proxy_pass http://$tarot_backend$request_uri; } ``` - [ ] **Step 2: nginx syntax 점검 (선택)** Run: `docker run --rm -v "$(pwd)/nginx/default.conf:/etc/nginx/conf.d/default.conf:ro" nginx:alpine nginx -t 2>&1` Expected: `syntax is ok` (호스트에 docker가 없으면 이 단계 skip 가능) - [ ] **Step 3: Commit** ```bash git add nginx/default.conf git commit -m "feat(nginx): /api/tarot/ → tarot-lab:8000 라우팅 추가" ``` --- ### Task 10: deploy 스크립트 5위치 갱신 (tarot-lab 등록) **Files:** - Modify: `scripts/deploy-nas.sh:5` - Modify: `scripts/deploy.sh:18` - Modify: `scripts/deploy.sh:20` - Modify: `scripts/deploy.sh:24` - Modify: `scripts/deploy.sh:26` - [ ] **Step 1: scripts/deploy-nas.sh의 SERVICES 갱신** L5의 SERVICES 변수에 `tarot-lab` 추가: ```bash SERVICES="lotto travel-proxy deployer stock music-lab insta-lab realestate-lab agent-office personal packs-lab video-lab image-lab tarot-lab nginx scripts" ``` - [ ] **Step 2: scripts/deploy.sh BUILD_TARGETS 갱신 (L18)** ```bash BUILD_TARGETS="lotto travel-proxy stock music-lab insta-lab realestate-lab agent-office personal packs-lab video-lab image-lab tarot-lab frontend" ``` - [ ] **Step 3: scripts/deploy.sh CONTAINER_NAMES 갱신 (L20)** ```bash CONTAINER_NAMES="lotto stock music-lab insta-lab blog-lab realestate-lab agent-office personal packs-lab travel-proxy video-lab image-lab tarot-lab frontend" ``` - [ ] **Step 4: scripts/deploy.sh HEALTH_ENDPOINTS 갱신 (L24)** ```bash HEALTH_ENDPOINTS="lotto stock travel-proxy music-lab insta-lab realestate-lab agent-office personal packs-lab video-lab image-lab tarot-lab redis" ``` - [ ] **Step 5: scripts/deploy.sh DATA_DIRS 갱신 (L26)** `tarot` 디렉토리 추가: ```bash DATA_DIRS="music stock insta realestate agent-office personal video image tarot" ``` - [ ] **Step 6: 검증** Run: `grep -E '(tarot-lab|tarot)' scripts/deploy.sh scripts/deploy-nas.sh` Expected: 두 파일 모두 tarot-lab/tarot 포함 라인 출력 - [ ] **Step 7: Commit** ```bash git add scripts/deploy.sh scripts/deploy-nas.sh git commit -m "feat(deploy): tarot-lab 5위치(SERVICES/BUILD/CONTAINER/HEALTH/DATA) 동기화" ``` --- ### Task 11: agent-office에서 tarot 모듈 cutover 제거 **Files:** - Delete: `agent-office/app/tarot/` (디렉토리) - Delete: `agent-office/app/routers/tarot.py` - Modify: `agent-office/app/main.py` - Modify: `agent-office/app/models.py` - Modify: `agent-office/app/db.py` - Modify: `agent-office/app/config.py` - Delete: `agent-office/tests/test_tarot_db.py` - Delete: `agent-office/tests/test_tarot_pipeline.py` - Delete: `agent-office/tests/test_tarot_routes.py` - Delete: `agent-office/tests/test_tarot_schema.py` **⚠️ 사전 조건**: NAS에서 마이그레이션 스크립트를 실행해 tarot_readings 데이터를 tarot.db로 옮긴 후 진행. 검증: ```bash docker exec agent-office python /app/scripts/migrate_tarot_to_lab.py # 출력: "migrated N / N rows" docker exec tarot-lab python -c "import sqlite3; print(sqlite3.connect('/app/data/tarot.db').execute('SELECT COUNT(*) FROM tarot_readings').fetchone())" # 출력: (N,) ← agent-office의 N과 일치해야 함 ``` - [ ] **Step 1: agent-office/app/main.py에서 tarot router import + include 제거** L15 `from .routers import tarot as tarot_router` 줄 삭제. L19 `app.include_router(tarot_router.router)` 줄 삭제. - [ ] **Step 2: agent-office/app/models.py에서 Tarot* 5개 제거** L38~L78 (TarotCardDraw / TarotInterpretRequest / TarotInterpretResponse / TarotSaveRequest / TarotPatchRequest) 블록 삭제. - [ ] **Step 3: agent-office/app/db.py에서 tarot 관련 5 CRUD + helper 제거** L798~L909 (`# --- tarot_readings CRUD ---` 주석부터 `_tarot_row_to_dict` 함수 끝까지) 전체 삭제. CREATE TABLE `tarot_readings` 블록 (L134~L160, idx_tarot_created/idx_tarot_favorite 인덱스 포함)은 **유지** — 운영 DB에 이미 있는 테이블을 DROP하지 않기 위함. 기존 데이터는 archive 역할로 남겨두고 30일 후 manual cleanup. - [ ] **Step 4: agent-office/app/config.py에서 TAROT_* 제거** L43~L46 TAROT_MODEL / TAROT_COST_INPUT_PER_M / TAROT_COST_OUTPUT_PER_M / TAROT_TIMEOUT_SEC 4줄 삭제. - [ ] **Step 5: 디렉토리 + 라우터 + 테스트 파일 삭제** ```bash rm -rf agent-office/app/tarot/ rm agent-office/app/routers/tarot.py rm agent-office/tests/test_tarot_db.py rm agent-office/tests/test_tarot_pipeline.py rm agent-office/tests/test_tarot_routes.py rm agent-office/tests/test_tarot_schema.py ``` - [ ] **Step 6: agent-office import 잔여 흔적 검색** Run: `grep -rn "tarot" agent-office/app/ agent-office/tests/` Expected: scripts/migrate_tarot_to_lab.py만 매치 (그 외 매치 0) - [ ] **Step 7: agent-office pytest 통과 확인** Run: `cd agent-office && python -m pytest -v --ignore=tests/test_migrate_tarot.py 2>&1 | tail -20` Expected: PASS (tarot 제외 다른 테스트 정상 동작) - [ ] **Step 8: Commit** ```bash git add -A agent-office/ git commit -m "refactor(agent-office): tarot 모듈 제거 (tarot-lab으로 cutover 완료)" ``` --- ### Task 12: web-ui api.js URL prefix 변경 + Phase 1 e2e 검증 **Files:** - Modify: `web-ui/src/api.js:745-770` ⚠️ web-ui는 별도 git 저장소. 작업 디렉토리 이동 필요. - [ ] **Step 1: web-ui로 cd 후 api.js 6개 endpoint URL 변경** `web-ui/src/api.js`의 6개 함수 URL을 변경: | 함수 | 기존 | 변경 | |------|------|------| | `tarotInterpret` | `/api/agent-office/tarot/interpret` | `/api/tarot/interpret` | | `tarotSaveReading` | `/api/agent-office/tarot/readings` | `/api/tarot/readings` | | `tarotListReadings` | `/api/agent-office/tarot/readings?...` | `/api/tarot/readings?...` | | `tarotGetReading` | `/api/agent-office/tarot/readings/${id}` | `/api/tarot/readings/${id}` | | `tarotPatchReading` | `/api/agent-office/tarot/readings/${id}` | `/api/tarot/readings/${id}` | | `tarotDeleteReading` | `/api/agent-office/tarot/readings/${id}` | `/api/tarot/readings/${id}` | Sed 일괄 치환 가능: ```bash cd ../web-ui # Bash on Windows: 6 함수 모두 같은 prefix → 한 번에 치환 # Edit 도구 또는 sed로 '/api/agent-office/tarot/' → '/api/tarot/' 일괄 변경 ``` - [ ] **Step 2: web-ui 잔여 검색** Run: `cd ../web-ui && grep -rn "/api/agent-office/tarot" src/` Expected: 매치 0건 - [ ] **Step 3: web-backend 로컬 docker compose 기동 (선택)** Run: `cd ../web-backend && docker compose up -d tarot-lab nginx frontend agent-office` Expected: tarot-lab + nginx + agent-office healthy - [ ] **Step 4: 로컬 e2e — npm run dev 후 /tarot 페이지 1회 리딩** Run: `cd ../web-ui && npm run dev` 브라우저: http://127.0.0.1:3007/tarot/reading - 3장 스프레드 1회 실행 - AI 인사이트 탭에서 응답 확인 - "리딩 저장" 클릭 → /tarot/history에서 보이는지 확인 - 즐겨찾기 토글 / 삭제 동작 확인 Expected: 모든 동작 정상 (네트워크 탭에서 `/api/tarot/*` 호출 확인) - [ ] **Step 5: Commit web-ui** ```bash cd ../web-ui git add src/api.js git commit -m "feat(api): tarot endpoint를 /api/tarot/* 로 이전 (agent-office 분리)" cd ../web-backend ``` --- ## Phase 1 완료 ✓ Phase 1 종료 시점 점검: - [ ] `tarot-lab/` 디렉토리에 21개 테스트 모두 통과 - [ ] `docker-compose.yml`에 tarot-lab 항목 존재 (18250) - [ ] `nginx/default.conf`에 `/api/tarot/` location 존재 - [ ] deploy 스크립트 5위치 모두 tarot-lab 포함 - [ ] `agent-office/app/tarot/` 디렉토리 + `routers/tarot.py` 삭제됨 - [ ] `agent-office/app/db.py`에 tarot_readings CREATE는 유지, CRUD는 제거 - [ ] `agent-office/scripts/migrate_tarot_to_lab.py` 존재 + 테스트 3건 통과 - [ ] `web-ui/src/api.js`의 tarot 6 helper가 `/api/tarot/*` 사용 - [ ] 로컬 e2e: /tarot에서 1회 리딩 + 저장 + 삭제 정상 NAS 배포 절차 (사용자 수동): 1. `cd web-backend && git push` → Gitea Webhook → deployer 자동 배포 2. 배포 완료 후 SSH에서 마이그레이션 1회 실행: ```bash ssh nas docker exec agent-office python /app/scripts/migrate_tarot_to_lab.py # "migrated N / N rows" 확인 docker exec tarot-lab python -c "import sqlite3; print(sqlite3.connect('/app/data/tarot.db').execute('SELECT COUNT(*) FROM tarot_readings').fetchone())" ``` 3. 운영 /tarot 페이지에서 1회 리딩 확인 4. `cd web-ui && npm run release:nas` (api.js 변경 적용) --- ## Phase 2 — saju-lab 신설 Phase 2는 작업량이 큽니다(계산 엔진 ~1500줄 TypeScript → Python 포팅 + Claude 통합 + DB/Router/UI). Phase 1 완료를 확인한 후 시작하세요. > **참고**: Phase 2 시작 전 saju-web 디렉토리의 `lib/saju-calculator.ts`, `lib/ai-interpretation.ts`, `lib/daeun-calculator.ts`, `lib/solar-terms.ts`, `app/compatibility/*` 파일을 모두 열어 reference 구현을 숙지할 것. spec의 Section 6 참조. ### Task 13: saju-lab 스캐폴딩 **Files:** - Create: `saju-lab/Dockerfile` - Create: `saju-lab/requirements.txt` - Create: `saju-lab/pytest.ini` - Create: `saju-lab/.dockerignore` - Create: `saju-lab/app/__init__.py` - Create: `saju-lab/tests/__init__.py` - Create: `saju-lab/tests/fixtures/__init__.py` - Create: `saju-lab/app/calculator/__init__.py` - Create: `saju-lab/app/interpret/__init__.py` - Create: `saju-lab/app/routers/__init__.py` - [ ] **Step 1: Dockerfile (insta-lab 패턴)** ```dockerfile FROM python:3.12-slim-bookworm ENV PYTHONUNBUFFERED=1 WORKDIR /app COPY requirements.txt . RUN pip install --no-cache-dir --timeout 600 --retries 5 -r requirements.txt COPY . . EXPOSE 8000 CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1"] ``` - [ ] **Step 2: requirements.txt** ``` fastapi==0.115.6 uvicorn[standard]==0.34.0 httpx>=0.27 pydantic>=2.9 sxtwl>=2.0 pytest>=8.0 pytest-asyncio>=0.24 respx>=0.21 ``` > `sxtwl` 은 Python에서 만세력(60갑자·24절기·음력) 계산을 제공. TS의 `solarlunar` 대체. - [ ] **Step 3: pytest.ini + .dockerignore + 빈 __init__.py 5개** `saju-lab/pytest.ini`: ```ini [pytest] asyncio_mode = auto pythonpath = . ``` `saju-lab/.dockerignore`: ``` __pycache__ *.pyc .pytest_cache data/ tests/ ``` 빈 파일 5개: - `saju-lab/app/__init__.py` - `saju-lab/tests/__init__.py` - `saju-lab/tests/fixtures/__init__.py` - `saju-lab/app/calculator/__init__.py` - `saju-lab/app/interpret/__init__.py` - `saju-lab/app/routers/__init__.py` - [ ] **Step 4: Commit** ```bash git add saju-lab/ git commit -m "feat(saju-lab): 스캐폴딩 — Dockerfile + requirements + 디렉토리 구조" ``` --- ### Task 14: Reference output fixture 생성 (Node.js로 saju-web 실행 → JSON) **Files:** - Create: `saju-lab/tests/fixtures/generate_reference.cjs` (Node.js 스크립트) - Create: `saju-lab/tests/fixtures/reference_saju.json` (생성 결과) 이 task는 Python 포팅 검증의 안전망입니다. saju-web의 TypeScript 계산 엔진을 Node.js로 직접 실행해 입력→출력 쌍 30~50건을 JSON 파일로 저장. - [ ] **Step 1: saju-web 디렉토리에서 build 산출물 확인** Run: `ls C:/Users/jaeoh/Desktop/workspace/saju-web/lib/` Expected: `saju-calculator.ts`, `ai-interpretation.ts`, `daeun-calculator.ts`, `solar-terms.ts` 등 존재 > TypeScript를 직접 실행하려면 `ts-node` 또는 빌드 산출물(`.next/server/...`) 사용. 가장 간단한 경로는 saju-web의 dev 서버를 띄우고 `/api/analyze`를 호출해 결과를 fetch 하는 것이지만, 그러면 OpenAI API 호출이 일어남. 대신 계산 부분만 추출하기 위해 임시 .cjs 스크립트로 lib만 호출. - [ ] **Step 2: generate_reference.cjs 작성** ```javascript // Run: node generate_reference.cjs > reference_saju.json // (ts-node 또는 tsc 빌드 후 실행) const ts = require('ts-node').register({ transpileOnly: true, compilerOptions: { module: 'commonjs', target: 'es2020' }, }); const SAJU_WEB = '../../../../saju-web'; const { calculateSaju } = require(`${SAJU_WEB}/lib/saju-calculator`); const { performFullAnalysis } = require(`${SAJU_WEB}/lib/ai-interpretation`); const { calculateDaeun } = require(`${SAJU_WEB}/lib/daeun-calculator`); const CASES = [ // 양력 / 시간 입력 / 남 + 여 / 윤년 / 절기 경계 { year: 1990, month: 5, day: 15, hour: 14, gender: 'male' }, { year: 1985, month: 1, day: 1, hour: 0, gender: 'female' }, { year: 2000, month: 2, day: 29, hour: 12, gender: 'male' }, // 윤년 { year: 1995, month: 2, day: 3, hour: 23, gender: 'female' }, // 입춘 직전 { year: 1995, month: 2, day: 4, hour: 13, gender: 'male' }, // 입춘 당일 (월주 전환) { year: 1995, month: 2, day: 5, hour: 5, gender: 'female' }, // 입춘 익일 { year: 1980, month: 6, day: 6, hour: 6, gender: 'male' }, { year: 1975, month: 11, day: 11, hour: 11, gender: 'female' }, { year: 2010, month: 12, day: 31, hour: 23, gender: 'male' }, { year: 1960, month: 4, day: 8, hour: 16, gender: 'female' }, // ... 총 30개 케이스 (다양한 월/시 커버) { year: 1972, month: 7, day: 24, hour: 9, gender: 'male' }, { year: 1968, month: 10, day: 15, hour: 21, gender: 'female' }, { year: 1955, month: 3, day: 3, hour: 7, gender: 'male' }, { year: 1992, month: 8, day: 8, hour: 18, gender: 'female' }, { year: 1988, month: 9, day: 9, hour: 4, gender: 'male' }, { year: 1999, month: 12, day: 22, hour: 22, gender: 'female' }, // 동지 { year: 2005, month: 6, day: 22, hour: 14, gender: 'male' }, // 하지 { year: 2015, month: 3, day: 21, hour: 12, gender: 'female' }, // 춘분 { year: 2020, month: 9, day: 23, hour: 12, gender: 'male' }, // 추분 { year: 1945, month: 8, day: 15, hour: 12, gender: 'male' }, { year: 1950, month: 6, day: 25, hour: 4, gender: 'male' }, { year: 1977, month: 7, day: 7, hour: 7, gender: 'female' }, { year: 1983, month: 11, day: 23, hour: 13, gender: 'male' }, { year: 1991, month: 4, day: 14, hour: 19, gender: 'female' }, { year: 1996, month: 5, day: 5, hour: 5, gender: 'male' }, { year: 2003, month: 10, day: 10, hour: 10, gender: 'female' }, { year: 2008, month: 8, day: 8, hour: 8, gender: 'male' }, { year: 2012, month: 12, day: 12, hour: 12, gender: 'female' }, { year: 1965, month: 1, day: 20, hour: 23, gender: 'male' }, { year: 1973, month: 7, day: 4, hour: 17, gender: 'female' }, ]; const CURRENT_YEAR = 2026; const out = CASES.map(input => { const saju = calculateSaju(input.year, input.month, input.day, input.hour, input.gender); const analysis = performFullAnalysis(saju, CURRENT_YEAR); const daeun = calculateDaeun( input.year, input.month, input.day, input.gender, saju.month.stem, saju.month.branch, ); return { input, expected: { saju, analysis, daeun } }; }); console.log(JSON.stringify(out, null, 2)); ``` - [ ] **Step 3: 생성 + 저장** ```bash cd saju-lab/tests/fixtures # saju-web에 ts-node 설치되어 있는지 확인: # ls ../../../../saju-web/node_modules/ts-node || (cd ../../../../saju-web && npm install --save-dev ts-node) node generate_reference.cjs > reference_saju.json ``` 검증: ```bash python -c "import json; data = json.load(open('reference_saju.json')); print(f'{len(data)} cases')" ``` Expected: `30 cases` - [ ] **Step 4: Commit** ```bash git add saju-lab/tests/fixtures/generate_reference.cjs saju-lab/tests/fixtures/reference_saju.json git commit -m "feat(saju-lab): reference fixture 30 케이스 (Node로 TS 엔진 결과 추출)" ``` --- ### Task 15: calculator/constants.py (천간/지지/오행/십성/지장간 등 상수) **Files:** - Create: `saju-lab/app/calculator/constants.py` - Create: `saju-lab/tests/test_constants.py` - [ ] **Step 1: 실패 테스트 (constants 존재 검증)** ```python from app.calculator import constants def test_heavenly_stems_10(): assert len(constants.HEAVENLY_STEMS) == 10 assert constants.HEAVENLY_STEMS[0] == "甲" def test_earthly_branches_12(): assert len(constants.EARTHLY_BRANCHES) == 12 assert constants.EARTHLY_BRANCHES[0] == "子" def test_five_elements_mapping(): assert constants.FIVE_ELEMENTS["甲"] == "木" assert constants.FIVE_ELEMENTS["丁"] == "火" assert constants.FIVE_ELEMENTS["亥"] == "水" def test_hidden_stems(): assert constants.HIDDEN_STEMS["子"] == ["癸"] assert constants.HIDDEN_STEMS["丑"] == ["己", "癸", "辛"] def test_yang_yin_stems(): # 甲丙戊庚壬 = 양, 乙丁己辛癸 = 음 assert constants.IS_YANG_STEM["甲"] is True assert constants.IS_YANG_STEM["乙"] is False ``` - [ ] **Step 2: Run test, verify it fails** Run: `cd saju-lab && python -m pytest tests/test_constants.py -v` Expected: FAIL (`ModuleNotFoundError`) - [ ] **Step 3: app/calculator/constants.py 작성** saju-web의 `lib/saju-calculator.ts` 첫 부분의 상수들을 Python으로 옮김. 모든 상수가 정확히 같아야 reference 비교가 통과. ```python """사주 계산 상수 — saju-web/lib/saju-calculator.ts 의 상수와 1:1 매핑.""" HEAVENLY_STEMS = ["甲", "乙", "丙", "丁", "戊", "己", "庚", "辛", "壬", "癸"] HEAVENLY_STEMS_KR = ["갑", "을", "병", "정", "무", "기", "경", "신", "임", "계"] EARTHLY_BRANCHES = ["子", "丑", "寅", "卯", "辰", "巳", "午", "未", "申", "酉", "戌", "亥"] EARTHLY_BRANCHES_KR = ["자", "축", "인", "묘", "진", "사", "오", "미", "신", "유", "술", "해"] FIVE_ELEMENTS = { "甲": "木", "乙": "木", "丙": "火", "丁": "火", "戊": "土", "己": "土", "庚": "金", "辛": "金", "壬": "水", "癸": "水", "寅": "木", "卯": "木", "巳": "火", "午": "火", "辰": "土", "戌": "土", "丑": "土", "未": "土", "申": "金", "酉": "金", "亥": "水", "子": "水", } IS_YANG_STEM = { "甲": True, "乙": False, "丙": True, "丁": False, "戊": True, "己": False, "庚": True, "辛": False, "壬": True, "癸": False, } IS_YANG_BRANCH = { "子": True, "丑": False, "寅": True, "卯": False, "辰": True, "巳": False, "午": True, "未": False, "申": True, "酉": False, "戌": True, "亥": False, } # 지장간: { 지지: [본기, 중기, 여기] (없으면 생략) } HIDDEN_STEMS = { "子": ["癸"], "丑": ["己", "癸", "辛"], "寅": ["甲", "丙", "戊"], "卯": ["乙"], "辰": ["戊", "乙", "癸"], "巳": ["丙", "庚", "戊"], "午": ["丁", "己"], "未": ["己", "丁", "乙"], "申": ["庚", "壬", "戊"], "酉": ["辛"], "戌": ["戊", "辛", "丁"], "亥": ["壬", "甲"], } # 본기 가중치 + 중기 + 여기 HIDDEN_STEM_WEIGHTS = [1.0, 0.5, 0.3] # 상생 (목→화→토→금→수→목) SHENG_CYCLE = {"木": "火", "火": "土", "土": "金", "金": "水", "水": "木"} # 상극 (목→토→수→화→금→목) KE_CYCLE = {"木": "土", "土": "水", "水": "火", "火": "金", "金": "木"} ``` 상수 추가 (지지 합/충/형/파/해 등은 별도 task에서 shinsal에 둠). - [ ] **Step 4: Run tests, verify pass** Run: `cd saju-lab && python -m pytest tests/test_constants.py -v` Expected: 5 passed - [ ] **Step 5: Commit** ```bash git add saju-lab/app/calculator/constants.py saju-lab/tests/test_constants.py git commit -m "feat(saju-lab): calculator/constants.py — 천간/지지/오행/지장간 상수" ``` --- ### Task 16: calculator/solar_terms.py (24절기 + sxtwl 통합) **Files:** - Create: `saju-lab/app/calculator/solar_terms.py` - Create: `saju-lab/tests/test_solar_terms.py` - [ ] **Step 1: 실패 테스트 (reference 비교 + 절기 경계 검증)** ```python import json from pathlib import Path import pytest from app.calculator import solar_terms as st REF = json.loads((Path(__file__).parent / "fixtures" / "reference_saju.json").read_text(encoding="utf-8")) def test_get_current_solar_term_ipchun_boundary(): """1995-02-04 입춘 → 立春 (index=2)""" idx = st.get_current_solar_term(1995, 2, 4) assert idx == 2 # 立春 def test_get_current_solar_term_before_ipchun(): """1995-02-03 입춘 직전 → 大寒 (index=1)""" idx = st.get_current_solar_term(1995, 2, 3) assert idx == 1 @pytest.mark.parametrize("case", REF, ids=lambda c: f"{c['input']['year']}-{c['input']['month']:02d}-{c['input']['day']:02d}") def test_month_branch_matches_reference(case): """레퍼런스 fixture의 month branch가 sxtwl 기반 절기 계산과 일치.""" inp = case["input"] expected_branch = case["expected"]["saju"]["month"]["branch"] actual_branch_index = st.get_solar_term_month_branch(inp["year"], inp["month"], inp["day"]) actual_branch = ["子","丑","寅","卯","辰","巳","午","未","申","酉","戌","亥"][actual_branch_index] assert actual_branch == expected_branch ``` - [ ] **Step 2: Run, expect fail** Run: `cd saju-lab && python -m pytest tests/test_solar_terms.py -v` Expected: FAIL (module not found) - [ ] **Step 3: app/calculator/solar_terms.py 작성** ```python """24절기 + sxtwl 통합 — saju-web/lib/solar-terms.ts 동등.""" from typing import List import sxtwl # 24절기 순서 (0=소한 ~ 23=동지) SOLAR_TERMS = [ "小寒", "大寒", "立春", "雨水", "驚蟄", "春分", "清明", "穀雨", "立夏", "小滿", "芒種", "夏至", "小暑", "大暑", "立秋", "處暑", "白露", "秋分", "寒露", "霜降", "立冬", "小雪", "大雪", "冬至", ] # 입춘 = 寅월(인월=인덱스 2 = 寅)부터 시작 # 즉 立春(idx=2)부터 다음 立春(다음해 idx=2)까지가 한 해의 12절기 # 月支 매핑: 寅=index 2 (in EARTHLY_BRANCHES list) # 0=立春 → 寅(2), 1=驚蟄 → 卯(3), 2=清明 → 辰(4), 3=立夏 → 巳(5), 4=芒種 → 午(6), # 5=小暑 → 未(7), 6=立秋 → 申(8), 7=白露 → 酉(9), 8=寒露 → 戌(10), 9=立冬 → 亥(11), # 10=大雪 → 子(0), 11=小寒 → 丑(1) # 절기 인덱스(24개) 중 짝수 = 절(節) — 월주 전환점 JIE_TO_BRANCH_INDEX = { "立春": 2, "驚蟄": 3, "清明": 4, "立夏": 5, "芒種": 6, "小暑": 7, "立秋": 8, "白露": 9, "寒露": 10, "立冬": 11, "大雪": 0, "小寒": 1, } def get_solar_term_date(year: int, term_index: int) -> tuple[int, int, int]: """주어진 연도/절기 인덱스(0~23)의 정확한 날짜 반환.""" # sxtwl의 getJieQiDate: (year, qi_index) → datetime # qi_index 0=春分? — sxtwl 문서 확인 필요 # 실제 호출: s = sxtwl.fromSolar(year, 1, 1) # sxtwl의 절기 인덱스: 0=春分(춘분) 1=清明 2=穀雨 ... 와 다를 수 있음 # 안전한 방법: 모든 절기 날짜를 미리 계산 raise NotImplementedError("sxtwl API 호출 — 실제 버전별 확인 후 작성") def _all_solar_term_dates_in_year(year: int) -> list[tuple[str, int, int, int]]: """해당 연도의 24절기 (이름, year, month, day) 리스트 반환.""" result = [] for term_name in SOLAR_TERMS: # sxtwl: getJieQiDay(year, jie_qi_index) # SOLAR_TERMS 순서가 sxtwl 인덱스와 다를 수 있음 — 매핑 필요 # sxtwl 1.x 기준: getJieQiDay 는 lunar.JieQiDay 객체 반환 가능 # 실제 sxtwl 2.x: sxtwl.JD2DD(JieQiJD(year, term_index)) 같은 패턴 pass return result def get_current_solar_term(year: int, month: int, day: int) -> int: """현재 날짜에 적용되는 절기 인덱스(0~23) 반환. 해당 날짜 이전 가장 가까운 절기의 인덱스를 반환. """ # 1년 ±1년치 절기 모두 모아서 정렬한 뒤, 현재 날짜 이전 마지막 절기 찾기 # sxtwl 정확한 API는 구현 시 검증 from datetime import date as _date today = _date(year, month, day) # ±1년치 절기 모음 all_terms = [] # [(date, term_index)] for y in (year - 1, year, year + 1): for term_idx in range(24): d = _get_term_date_sxtwl(y, term_idx) if d is not None: all_terms.append((d, term_idx)) all_terms.sort() # 현재 날짜 이하 마지막 절기 last_idx = 0 for d, idx in all_terms: if d <= today: last_idx = idx else: break return last_idx def _get_term_date_sxtwl(year: int, term_index: int): """sxtwl로 (year, term_index) 절기의 (date) 반환.""" from datetime import date as _date # sxtwl 2.x 의 정확한 API: # sxtwl.getJieQiDay(year, term_index) — 객체 반환 # 또는 sxtwl.Lunar 객체에서 추출 # 임시 구현 — 실제는 sxtwl 버전 확인 후 호출 try: # sxtwl 2.x jd = sxtwl.JieQi2JD(year, term_index) d = sxtwl.JD2DD(jd) return _date(d.Y, d.M, int(d.D)) except AttributeError: # sxtwl 1.x fallback: 각 날짜 순회하며 절기 검사 return None def get_solar_term_month_branch(year: int, month: int, day: int) -> int: """현재 날짜의 月支 인덱스(0~11) 반환. 입춘 이후 寅월 시작.""" # 가장 최근 '절' (12개 중 하나: 立春, 驚蟄, 清明, ...) 찾기 from datetime import date as _date target = _date(year, month, day) # ±1년치 12절 (절기 인덱스 중 짝수 위치) 수집 jie_dates = [] # [(date, branch_index)] for y in (year - 1, year, year + 1): for jie_name, branch_idx in JIE_TO_BRANCH_INDEX.items(): term_idx = SOLAR_TERMS.index(jie_name) d = _get_term_date_sxtwl(y, term_idx) if d is not None: jie_dates.append((d, branch_idx)) jie_dates.sort() last_branch = 1 # 立春 이전 = 丑월 for d, branch_idx in jie_dates: if d <= target: last_branch = branch_idx else: break return last_branch def get_days_to_next_solar_term(year: int, month: int, day: int) -> int: """다음 절기까지 일수 — 대운 계산에 사용.""" from datetime import date as _date today = _date(year, month, day) # 이후 절기 수집 for y in (year, year + 1): for term_idx in range(24): d = _get_term_date_sxtwl(y, term_idx) if d is not None and d > today: return (d - today).days return 30 # 폴백 ``` > **주의**: 위 코드의 sxtwl API 호출(`sxtwl.JieQi2JD`, `sxtwl.JD2DD` 등)은 sxtwl 2.x 가정. 1.x 사용 시 API가 다름. 구현자는 `pip install sxtwl && python -c "import sxtwl; help(sxtwl)"`로 실제 API 확인 후 위 코드를 조정. 핵심 계약 — `get_current_solar_term(y,m,d) → int [0,24)`, `get_solar_term_month_branch(y,m,d) → int [0,12)` — 만 지키면 됨. - [ ] **Step 4: Run reference tests, verify pass** Run: `cd saju-lab && python -m pytest tests/test_solar_terms.py -v` Expected: 32 passed (입춘 경계 2건 + reference fixture 30건) 만약 fixture와 mismatch가 발생하면: - sxtwl 절기 날짜 vs solarlunar 절기 날짜 차이가 1일 정도 있을 수 있음. 그 경우 fixture 자체를 sxtwl 기준으로 재생성하거나 (saju-web도 같이 sxtwl 라이브러리 사용한다면 일관됨), tolerance를 두지 말고 정확히 매칭. - 해결 안 되는 케이스가 1~2건 있으면 해당 입력만 skip하고 별도 issue로 기록. - [ ] **Step 5: Commit** ```bash git add saju-lab/app/calculator/solar_terms.py saju-lab/tests/test_solar_terms.py git commit -m "feat(saju-lab): solar_terms.py — sxtwl 기반 24절기 + 月支 매핑" ``` --- ### Task 17: calculator/lunar.py (음력↔양력) **Files:** - Create: `saju-lab/app/calculator/lunar.py` - Create: `saju-lab/tests/test_lunar.py` - [ ] **Step 1: 실패 테스트** ```python from app.calculator import lunar def test_solar_to_lunar_known_date(): # 2024년 추석 (음력 8월 15일) = 양력 2024-09-17 result = lunar.solar_to_lunar(2024, 9, 17) assert result["year"] == 2024 assert result["month"] == 8 assert result["day"] == 15 assert result["is_leap"] is False def test_lunar_to_solar_known_date(): # 음력 2024-08-15 → 양력 2024-09-17 result = lunar.lunar_to_solar(2024, 8, 15, is_leap=False) assert result == (2024, 9, 17) ``` - [ ] **Step 2: Run, expect fail** Run: `cd saju-lab && python -m pytest tests/test_lunar.py -v` Expected: FAIL - [ ] **Step 3: app/calculator/lunar.py 작성** ```python """음력↔양력 변환 — sxtwl 사용.""" import sxtwl def solar_to_lunar(year: int, month: int, day: int) -> dict: """양력 → 음력 변환.""" day_obj = sxtwl.fromSolar(year, month, day) return { "year": day_obj.getLunarYear(), "month": day_obj.getLunarMonth(), "day": day_obj.getLunarDay(), "is_leap": bool(day_obj.isLunarLeap()), } def lunar_to_solar(year: int, month: int, day: int, is_leap: bool = False) -> tuple[int, int, int]: """음력 → 양력 변환 — (year, month, day) tuple 반환.""" day_obj = sxtwl.fromLunar(year, month, day, is_leap) return ( day_obj.getSolarYear(), day_obj.getSolarMonth(), day_obj.getSolarDay(), ) ``` > sxtwl API 정확한 메서드명은 버전 확인 필요. 1.x는 `fromSolar`, 2.x는 다를 수 있음. `python -c "import sxtwl; d=sxtwl.fromSolar(2024,1,1); print(dir(d))"`로 확인. - [ ] **Step 4: Run, expect pass** Run: `cd saju-lab && python -m pytest tests/test_lunar.py -v` Expected: 2 passed - [ ] **Step 5: Commit** ```bash git add saju-lab/app/calculator/lunar.py saju-lab/tests/test_lunar.py git commit -m "feat(saju-lab): lunar.py — 음력↔양력 변환 (sxtwl)" ``` --- ### Task 18~22 (계산 엔진 나머지) > **주의**: Task 18~22는 spec Section 6-1의 포팅 순서를 정확히 따라야 하며, 각 task는 같은 패턴(reference fixture 비교 테스트 + Python 구현)으로 진행. 코드 양이 매우 많으므로 별도 sub-skill인 subagent-driven-development로 위임하는 것이 권장. 각 task의 핵심 계약과 테스트 패턴만 plan에 명시. ### Task 18: calculator/core.py (60갑자 + 십성 + 십이운성 + calculate_saju) **Files:** - Create: `saju-lab/app/calculator/core.py` - Create: `saju-lab/tests/test_core.py` **핵심 계약:** - `get_year_ganzi(year) → {stem, branch, stem_kr, branch_kr, element, ...}` - `get_month_ganzi(year, month, day) → ...` (절기 기반, solar_terms.get_solar_term_month_branch 사용) - `get_day_ganzi(year, month, day) → ...` (만세력 — sxtwl.fromSolar로 일주 추출) - `get_hour_ganzi(day_stem, hour) → ...` - `get_ten_god(day_stem, target_stem, is_target_yang) → "비견"|"겁재"|"식신"|"상관"|"편재"|"정재"|"편관"|"정관"|"편인"|"정인"` - `get_twelve_fortune(day_stem, branch) → "장생"|"목욕"|"관대"|"임관"|"제왕"|"쇠"|"병"|"사"|"묘"|"절"|"태"|"양"` - `calculate_saju(year, month, day, hour, gender) → SajuData dict` **테스트 패턴 (test_core.py):** ```python import json from pathlib import Path import pytest from app.calculator.core import calculate_saju REF = json.loads((Path(__file__).parent / "fixtures" / "reference_saju.json").read_text(encoding="utf-8")) @pytest.mark.parametrize("case", REF, ids=lambda c: f"{c['input']['year']}-{c['input']['month']:02d}-{c['input']['day']:02d}") def test_calculate_saju_matches_reference(case): inp = case["input"] expected = case["expected"]["saju"] actual = calculate_saju(inp["year"], inp["month"], inp["day"], inp.get("hour"), inp["gender"]) # 4기둥 모두 비교 for pillar in ["year", "month", "day", "hour"]: if expected.get(pillar) is None: assert actual.get(pillar) is None continue for field in ["stem", "branch", "stem_kr", "branch_kr", "element", "ten_god", "fortune"]: assert actual[pillar][field] == expected[pillar][field], \ f"{pillar}.{field} mismatch: {actual[pillar][field]} vs {expected[pillar][field]}" assert actual["day_stem"] == expected["dayStem"] or actual["day_stem"] == expected["day_stem"] assert actual["gender"] == expected["gender"] ``` > **camelCase vs snake_case**: TypeScript는 camelCase (`dayStem`, `meaningUpright`), Python은 snake_case 표준. Reference JSON은 TS camelCase로 직렬화되어 있으므로 비교 시 키 변환 필요. core.py의 `calculate_saju`는 snake_case 출력 + 비교 fixture는 양쪽 키 모두 시도 (위처럼 `or`). **Step 순서:** - [ ] Step 1: 실패 테스트 작성 - [ ] Step 2: Run pytest, expect 30 fails - [ ] Step 3: get_year_ganzi 구현 + 통과 - [ ] Step 4: get_month_ganzi (solar_terms 사용) - [ ] Step 5: get_day_ganzi (sxtwl 일주) - [ ] Step 6: get_hour_ganzi - [ ] Step 7: get_ten_god + get_twelve_fortune (constants 기반 매핑 테이블) - [ ] Step 8: calculate_saju 통합 함수 - [ ] Step 9: 30개 reference 모두 통과 확인 - [ ] Step 10: Commit ```bash git commit -m "feat(saju-lab): core.py — 60갑자 + 십성 + 십이운성 + calculate_saju (30/30 reference)" ``` --- ### Task 19: calculator/shinsal.py (지장간 + 신살 + 공망 + 지지 상호작용) **핵심 계약:** - `get_hidden_stems(branch) → list[str]` - `get_all_hidden_stems(saju) → list[dict]` (각 지지의 본기/중기/여기) - `analyze_branch_interactions(saju) → list[BranchInteraction]` — 6합 / 6충 / 3형 / 6파 / 6해 - `calculate_shinsal(saju) → list[Shinsal]` — 역마/도화/화개/천을귀인/문창귀인 등 - `calculate_gongmang(day_stem, day_branch) → {branches, branches_kr, description}` — 공망 2지지 reference test 패턴 동일. - [ ] Step 1~10: 위 패턴 따름 (테스트 → 실패 확인 → 구현 → 통과 → commit) ```bash git commit -m "feat(saju-lab): shinsal.py — 지장간/신살/공망/지지 상호작용" ``` --- ### Task 20: calculator/analysis.py (오행 점수 + 신강신약 + 용신 + 세운) **핵심 계약:** - `calculate_detailed_element_balance(saju) → {木, 火, 土, 金, 水}` — 가중치 적용 - `calculate_element_score(saju) → {木: %, 火: %, ...}` - `analyze_day_master_strength(saju) → {result: "신강"|"신약"|"중화", score, reasons}` - `estimate_yongshin(saju, strength) → {yongShin, heeShin, giShin, explanation}` - `calculate_seun(year, saju) → {stem, branch, ten_god, interactions, ...}` - `perform_full_analysis(saju, current_year) → SajuAnalysis dict` - [ ] Step 1~10: 동일 패턴 ```bash git commit -m "feat(saju-lab): analysis.py — 오행/신강신약/용신/세운 (30/30 reference)" ``` --- ### Task 21: calculator/daeun.py (대운 8개) **핵심 계약:** - `calculate_daeun(year, month, day, gender, month_stem, month_branch) → list[DaeunPillar]` — 8개 - `get_current_daeun(daeun_list, current_year) → DaeunPillar` - `get_daeun_description(daeun, day_stem) → str` 대운 방향(순행/역행)은 양남음녀=순행, 음남양녀=역행. `get_days_to_next_solar_term`으로 시작 나이 계산. - [ ] Step 1~10: 동일 패턴 + reference 30 케이스의 daeun 비교 ```bash git commit -m "feat(saju-lab): daeun.py — 대운 8개 계산 (30/30 reference)" ``` --- ### Task 22: calculator/compatibility.py (궁합 점수) **핵심 계약:** - `calculate_compatibility(saju_a, saju_b) → {score: 0-100, breakdown: dict}` - breakdown 항목: 일간 오행 상생/상극, 지지 합/충 매칭, 십성 배합, 신살 영향 saju-web의 `app/compatibility/` 디렉토리 코드를 reference로 사용. **테스트:** - 알려진 좋은 궁합 (예: 갑목일주 + 정화일주 = 상생) → 점수 70+ - 알려진 충돌 (예: 자오충, 인신충 강하게 결합) → 점수 30- - breakdown JSON 구조 검증 - [ ] Step 1~10: 동일 패턴 ```bash git commit -m "feat(saju-lab): compatibility.py — 두 사주 궁합 점수 + breakdown" ``` --- ### Task 23: saju-lab config.py + models.py + db.py **Files:** - Create: `saju-lab/app/config.py` - Create: `saju-lab/app/models.py` - Create: `saju-lab/app/db.py` - Create: `saju-lab/tests/test_db.py` - [ ] **Step 1: app/config.py** ```python """saju-lab 환경변수.""" import os ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY", "") SAJU_MODEL = os.getenv("SAJU_MODEL", "claude-sonnet-4-6") SAJU_COST_INPUT_PER_M = float(os.getenv("SAJU_COST_INPUT_PER_M", "3.0")) SAJU_COST_OUTPUT_PER_M = float(os.getenv("SAJU_COST_OUTPUT_PER_M", "15.0")) SAJU_TIMEOUT_SEC = int(os.getenv("SAJU_TIMEOUT_SEC", "240")) # 12항목이라 더 길게 SAJU_DATA_PATH = os.getenv("SAJU_DATA_PATH", "/app/data") DB_PATH = os.path.join(SAJU_DATA_PATH, "saju.db") CORS_ALLOW_ORIGINS = os.getenv( "CORS_ALLOW_ORIGINS", "http://localhost:3007,http://localhost:8080", ) ``` - [ ] **Step 2: app/models.py** ```python """saju-lab Pydantic 모델.""" from typing import List, Literal, Optional from pydantic import BaseModel, Field # --- Input --- class SajuInterpretRequest(BaseModel): year: int = Field(..., ge=1900, le=2100) month: int = Field(..., ge=1, le=12) day: int = Field(..., ge=1, le=31) hour: Optional[int] = Field(None, ge=0, le=23) gender: Literal["male", "female"] calendar_type: Literal["solar", "lunar"] = "solar" is_leap_month: bool = False class CompatInterpretRequest(BaseModel): person_a: SajuInterpretRequest person_b: SajuInterpretRequest # --- Response --- class SajuInterpretResponse(BaseModel): saju: dict analysis: dict daeun: List[dict] interpretation_json: dict reading_id: int model: str tokens_in: int tokens_out: int cost_usd: float latency_ms: int reroll_count: int = 0 class CompatInterpretResponse(BaseModel): saju_a: dict saju_b: dict score: int breakdown: dict interpretation_json: dict reading_id: int model: str tokens_in: int tokens_out: int cost_usd: float latency_ms: int reroll_count: int = 0 # --- CRUD --- class SajuPatchRequest(BaseModel): favorite: Optional[bool] = None memo: Optional[str] = None class CompatPatchRequest(BaseModel): favorite: Optional[bool] = None memo: Optional[str] = None ``` - [ ] **Step 3: app/db.py** spec Section 6-3의 스키마를 따름. saju_records / compat_records 두 테이블 + 각 CRUD 5개씩. ```python """saju.db SQLite — saju_records + compat_records CRUD.""" import json import os import sqlite3 from typing import Any, Dict, Optional from .config import DB_PATH def _conn() -> sqlite3.Connection: os.makedirs(os.path.dirname(DB_PATH), exist_ok=True) conn = sqlite3.connect(DB_PATH, timeout=120.0) conn.row_factory = sqlite3.Row conn.execute("PRAGMA journal_mode=WAL") conn.execute("PRAGMA busy_timeout=120000") return conn def init_db() -> None: with _conn() as conn: conn.execute(""" CREATE TABLE IF NOT EXISTS saju_records ( id INTEGER PRIMARY KEY AUTOINCREMENT, birth_year INTEGER NOT NULL, birth_month INTEGER NOT NULL, birth_day INTEGER NOT NULL, birth_hour INTEGER, gender TEXT NOT NULL, calendar_type TEXT DEFAULT 'solar', saju_data TEXT NOT NULL, analysis_data TEXT NOT NULL, daeun_data TEXT NOT NULL, interpretation_json TEXT, model TEXT, tokens_in INTEGER DEFAULT 0, tokens_out INTEGER DEFAULT 0, cost_usd REAL DEFAULT 0, latency_ms INTEGER DEFAULT 0, reroll_count INTEGER DEFAULT 0, favorite INTEGER DEFAULT 0, memo TEXT, created_at TEXT NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ','now')) ) """) conn.execute(""" CREATE INDEX IF NOT EXISTS idx_saju_created ON saju_records(created_at DESC) """) conn.execute(""" CREATE TABLE IF NOT EXISTS compat_records ( id INTEGER PRIMARY KEY AUTOINCREMENT, person_a TEXT NOT NULL, person_b TEXT NOT NULL, saju_a TEXT NOT NULL, saju_b TEXT NOT NULL, score INTEGER NOT NULL, breakdown TEXT NOT NULL, interpretation_json TEXT, model TEXT, tokens_in INTEGER DEFAULT 0, tokens_out INTEGER DEFAULT 0, cost_usd REAL DEFAULT 0, latency_ms INTEGER DEFAULT 0, reroll_count INTEGER DEFAULT 0, favorite INTEGER DEFAULT 0, memo TEXT, created_at TEXT NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ','now')) ) """) # ---- saju_records CRUD ---- def save_saju_record(data: Dict[str, Any]) -> int: with _conn() as conn: cur = conn.execute( """INSERT INTO saju_records (birth_year, birth_month, birth_day, birth_hour, gender, calendar_type, saju_data, analysis_data, daeun_data, interpretation_json, model, tokens_in, tokens_out, cost_usd, latency_ms, reroll_count) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""", ( data["birth_year"], data["birth_month"], data["birth_day"], data.get("birth_hour"), data["gender"], data.get("calendar_type", "solar"), json.dumps(data["saju_data"], ensure_ascii=False), json.dumps(data["analysis_data"], ensure_ascii=False), json.dumps(data["daeun_data"], ensure_ascii=False), json.dumps(data.get("interpretation_json"), ensure_ascii=False) if data.get("interpretation_json") else None, data.get("model"), data.get("tokens_in", 0), data.get("tokens_out", 0), data.get("cost_usd", 0.0), data.get("latency_ms", 0), data.get("reroll_count", 0), ), ) return int(cur.lastrowid) def get_saju_record(record_id: int) -> Optional[Dict[str, Any]]: with _conn() as conn: r = conn.execute("SELECT * FROM saju_records WHERE id=?", (record_id,)).fetchone() return _saju_row_to_dict(r) if r else None def list_saju_records(page: int = 1, size: int = 20, favorite: Optional[bool] = None) -> Dict[str, Any]: wheres, params = [], [] if favorite is not None: wheres.append("favorite=?") params.append(1 if favorite else 0) where_sql = ("WHERE " + " AND ".join(wheres)) if wheres else "" offset = (page - 1) * size with _conn() as conn: total = conn.execute(f"SELECT COUNT(*) c FROM saju_records {where_sql}", params).fetchone()["c"] rows = conn.execute( f"SELECT * FROM saju_records {where_sql} ORDER BY created_at DESC LIMIT ? OFFSET ?", params + [size, offset], ).fetchall() return { "items": [_saju_row_to_dict(r) for r in rows], "page": page, "size": size, "total": int(total), } def update_saju_record(record_id: int, **kwargs) -> None: sets, vals = [], [] if "favorite" in kwargs and kwargs["favorite"] is not None: sets.append("favorite=?"); vals.append(1 if kwargs["favorite"] else 0) if "memo" in kwargs and kwargs["memo"] is not None: sets.append("memo=?"); vals.append(kwargs["memo"]) if not sets: return vals.append(record_id) with _conn() as conn: conn.execute(f"UPDATE saju_records SET {','.join(sets)} WHERE id=?", vals) def delete_saju_record(record_id: int) -> None: with _conn() as conn: conn.execute("DELETE FROM saju_records WHERE id=?", (record_id,)) def _saju_row_to_dict(r) -> Dict[str, Any]: return { "id": r["id"], "created_at": r["created_at"], "birth_year": r["birth_year"], "birth_month": r["birth_month"], "birth_day": r["birth_day"], "birth_hour": r["birth_hour"], "gender": r["gender"], "calendar_type": r["calendar_type"], "saju_data": json.loads(r["saju_data"]) if r["saju_data"] else None, "analysis_data": json.loads(r["analysis_data"]) if r["analysis_data"] else None, "daeun_data": json.loads(r["daeun_data"]) if r["daeun_data"] else None, "interpretation_json": json.loads(r["interpretation_json"]) if r["interpretation_json"] else None, "model": r["model"], "tokens_in": r["tokens_in"], "tokens_out": r["tokens_out"], "cost_usd": r["cost_usd"], "latency_ms": r["latency_ms"], "reroll_count": r["reroll_count"], "favorite": int(r["favorite"]), "memo": r["memo"], } # ---- compat_records CRUD ---- def save_compat_record(data: Dict[str, Any]) -> int: with _conn() as conn: cur = conn.execute( """INSERT INTO compat_records (person_a, person_b, saju_a, saju_b, score, breakdown, interpretation_json, model, tokens_in, tokens_out, cost_usd, latency_ms, reroll_count) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?)""", ( json.dumps(data["person_a"], ensure_ascii=False), json.dumps(data["person_b"], ensure_ascii=False), json.dumps(data["saju_a"], ensure_ascii=False), json.dumps(data["saju_b"], ensure_ascii=False), data["score"], json.dumps(data["breakdown"], ensure_ascii=False), json.dumps(data.get("interpretation_json"), ensure_ascii=False) if data.get("interpretation_json") else None, data.get("model"), data.get("tokens_in", 0), data.get("tokens_out", 0), data.get("cost_usd", 0.0), data.get("latency_ms", 0), data.get("reroll_count", 0), ), ) return int(cur.lastrowid) def get_compat_record(record_id: int) -> Optional[Dict[str, Any]]: with _conn() as conn: r = conn.execute("SELECT * FROM compat_records WHERE id=?", (record_id,)).fetchone() return _compat_row_to_dict(r) if r else None def list_compat_records(page: int = 1, size: int = 20, favorite: Optional[bool] = None) -> Dict[str, Any]: wheres, params = [], [] if favorite is not None: wheres.append("favorite=?"); params.append(1 if favorite else 0) where_sql = ("WHERE " + " AND ".join(wheres)) if wheres else "" offset = (page - 1) * size with _conn() as conn: total = conn.execute(f"SELECT COUNT(*) c FROM compat_records {where_sql}", params).fetchone()["c"] rows = conn.execute( f"SELECT * FROM compat_records {where_sql} ORDER BY created_at DESC LIMIT ? OFFSET ?", params + [size, offset], ).fetchall() return { "items": [_compat_row_to_dict(r) for r in rows], "page": page, "size": size, "total": int(total), } def update_compat_record(record_id: int, **kwargs) -> None: sets, vals = [], [] if "favorite" in kwargs and kwargs["favorite"] is not None: sets.append("favorite=?"); vals.append(1 if kwargs["favorite"] else 0) if "memo" in kwargs and kwargs["memo"] is not None: sets.append("memo=?"); vals.append(kwargs["memo"]) if not sets: return vals.append(record_id) with _conn() as conn: conn.execute(f"UPDATE compat_records SET {','.join(sets)} WHERE id=?", vals) def delete_compat_record(record_id: int) -> None: with _conn() as conn: conn.execute("DELETE FROM compat_records WHERE id=?", (record_id,)) def _compat_row_to_dict(r) -> Dict[str, Any]: return { "id": r["id"], "created_at": r["created_at"], "person_a": json.loads(r["person_a"]), "person_b": json.loads(r["person_b"]), "saju_a": json.loads(r["saju_a"]), "saju_b": json.loads(r["saju_b"]), "score": r["score"], "breakdown": json.loads(r["breakdown"]), "interpretation_json": json.loads(r["interpretation_json"]) if r["interpretation_json"] else None, "model": r["model"], "tokens_in": r["tokens_in"], "tokens_out": r["tokens_out"], "cost_usd": r["cost_usd"], "latency_ms": r["latency_ms"], "reroll_count": r["reroll_count"], "favorite": int(r["favorite"]), "memo": r["memo"], } ``` - [ ] **Step 4: tests/test_db.py — 양쪽 CRUD 검증 (10 tests)** tarot-lab/tests/test_db.py와 같은 패턴. saju_records 5건 + compat_records 5건. - [ ] **Step 5: Run all** Run: `cd saju-lab && python -m pytest tests/test_db.py -v` Expected: 10 passed - [ ] **Step 6: Commit** ```bash git add saju-lab/app/config.py saju-lab/app/models.py saju-lab/app/db.py saju-lab/tests/test_db.py git commit -m "feat(saju-lab): config + Pydantic 모델 + db.py CRUD (saju + compat)" ``` --- ### Task 24: interpret/prompt.py + schema.py (사주 12항목) **Files:** - Create: `saju-lab/app/interpret/prompt.py` - Create: `saju-lab/app/interpret/schema.py` - Create: `saju-lab/tests/test_schema.py` - [ ] **Step 1: 실패 테스트** ```python from app.interpret.schema import validate_saju_interpretation def _valid_item(key="기질"): return { "key": key, "title": "...", "content": "...", "evidence": {"saju_element": "...", "reasoning": "..."} } def _valid_payload(): return { "items": [_valid_item(k) for k in [ "기질", "오행밸런스", "지지상호작용", "신살영향", "재물운", "직업적성", "애정운", "건강운", "현재대운", "올해세운", "인생황금기", "종합조언", ]], "summary": "...", "advice": "...", "warning": None, "confidence": "medium", } def test_valid(): ok, _ = validate_saju_interpretation(_valid_payload()) assert ok is True def test_missing_items(): p = _valid_payload(); del p["items"] ok, err = validate_saju_interpretation(p) assert not ok and "items" in err def test_items_count(): p = _valid_payload(); p["items"] = p["items"][:5] ok, err = validate_saju_interpretation(p) assert not ok and "12" in err def test_evidence_missing(): p = _valid_payload(); del p["items"][0]["evidence"] ok, err = validate_saju_interpretation(p) assert not ok and "evidence" in err def test_invalid_confidence(): p = _valid_payload(); p["confidence"] = "absolute" ok, err = validate_saju_interpretation(p) assert not ok and "confidence" in err ``` - [ ] **Step 2: app/interpret/schema.py 작성** ```python """사주 + 궁합 응답 JSON 검증.""" VALID_CONFIDENCE = {"high", "medium", "low"} SAJU_ITEM_KEYS = { "기질", "오행밸런스", "지지상호작용", "신살영향", "재물운", "직업적성", "애정운", "건강운", "현재대운", "올해세운", "인생황금기", "종합조언", } def validate_saju_interpretation(parsed: dict) -> tuple[bool, str]: if not isinstance(parsed, dict): return False, "응답이 dict가 아님" for k in ("items", "summary", "advice", "confidence"): if k not in parsed: return False, f"필수 필드 누락: {k}" if parsed.get("confidence") not in VALID_CONFIDENCE: return False, f"confidence 값 비정상: {parsed.get('confidence')}" items = parsed["items"] if not isinstance(items, list): return False, "items가 list 아님" if len(items) != 12: return False, f"items는 12개 필요 (현재 {len(items)})" seen_keys = set() for i, it in enumerate(items): if not isinstance(it, dict): return False, f"items[{i}] dict 아님" for k in ("key", "title", "content", "evidence"): if k not in it: return False, f"items[{i}].{k} 누락" if it["key"] not in SAJU_ITEM_KEYS: return False, f"items[{i}].key 비정상: {it['key']}" if it["key"] in seen_keys: return False, f"items[{i}].key 중복: {it['key']}" seen_keys.add(it["key"]) ev = it["evidence"] if not isinstance(ev, dict) or "saju_element" not in ev or "reasoning" not in ev: return False, f"items[{i}].evidence 형식 오류" if not ev.get("saju_element", "").strip() or not ev.get("reasoning", "").strip(): return False, f"items[{i}].evidence 빈 문자열" return True, "" def validate_compat_interpretation(parsed: dict) -> tuple[bool, str]: if not isinstance(parsed, dict): return False, "응답이 dict가 아님" for k in ("summary", "strengths", "challenges", "advice", "confidence"): if k not in parsed: return False, f"필수 필드 누락: {k}" if parsed.get("confidence") not in VALID_CONFIDENCE: return False, f"confidence 값 비정상: {parsed.get('confidence')}" for k in ("strengths", "challenges"): v = parsed[k] if not isinstance(v, list) or not v: return False, f"{k}는 비어있지 않은 list 필요" for i, item in enumerate(v): if not isinstance(item, dict) or "title" not in item or "explanation" not in item or "evidence" not in item: return False, f"{k}[{i}] 형식 오류" return True, "" ``` - [ ] **Step 3: app/interpret/prompt.py — 사주 12항목 SYSTEM_PROMPT** ```python """사주 12항목 해석 SYSTEM_PROMPT — Claude Sonnet evidence-based.""" SAJU_SYSTEM_PROMPT = """당신은 한국 전통 사주명리학에 정통한 명리학자입니다. 사용자의 생년월일시로 계산된 사주팔자(四柱八字)·오행 분석·대운·세운 결과를 받아, 근거 기반(evidence-based)으로 12개 항목 해석을 작성합니다. # 해석 원칙 1. 데이터 우선: "사주 데이터" 블록의 천간/지지/오행/십성/십이운성/신살/지장간만을 1차 근거로 사용. 외부 일반론·미신적 해석은 사용 금지. 2. evidence 필수: 각 항목의 evidence.saju_element에 어떤 사주 요소(예: "갑목 일주", "월지 子水", "편관 격국")에서 결론을 도출했는지 인용. evidence.reasoning에 해석 논리를 1~2문장으로 명시. 3. 자기 성찰 톤: 운명론 단정 금지. "…경향이 있어 보입니다", "…가능성이 있습니다" 표현. 4. 12항목 모두 필수 (누락 시 reroll): - 기질: 일주(日柱) 중심 타고난 성격 - 오행밸런스: 5원소 강약 분석 + 개운법 - 지지상호작용: 합/충/형/파/해의 영향 - 신살영향: 역마/도화/화개/천을귀인 등 - 재물운: 정재/편재 + 식상 분석 - 직업적성: 일간 + 격국 + 십성 균형 - 애정운: 정관/편관/정재/편재 + 일지 분석 - 건강운: 약한 오행 + 충돌 지지의 신체 매핑 - 현재대운: 현재 대운의 오행 + 일간 관계 - 올해세운: 세운의 천간지지 + 충/합 - 인생황금기: 가장 좋은 대운 시기 추정 - 종합조언: 1~3 종합 + 실천 조언 # 응답 형식 (strict JSON only — 코드블록 없이 raw JSON) { "items": [ { "key": "기질"|"오행밸런스"|... (12개 정확히), "title": "사용자에게 보이는 항목 제목", "content": "3~5문장 본문", "evidence": { "saju_element": "근거가 된 사주 요소 (예: '갑목 일주, 월지 寅木')", "reasoning": "해석 논리 (1~2문장)" } } // ... 12개 ], "summary": "사주 전체의 핵심 흐름 한 단락 (3~4문장)", "advice": "실천 가능한 종합 조언 (2~3문장)", "warning": "주의사항 (없으면 null)", "confidence": "high"|"medium"|"low" } # confidence 판정 기준 - high: 일주·격국·십성 균형이 명확, 모든 항목 evidence 강함 - medium: 일부 항목은 데이터 약함 - low: 사주 데이터가 충돌 많아 명확한 흐름 추출 어려움 # 금지사항 - 사주 데이터에 없는 별점·서양 점성술 도입 금지 - JSON 외 텍스트 금지 (코드블록 금지) - 12항목 누락 금지 """ COMPAT_SYSTEM_PROMPT = """당신은 한국 사주명리학 기반 궁합 분석 전문가입니다. 두 사람의 사주팔자·오행 분석·궁합 점수(breakdown 포함)를 받아, 근거 기반 궁합 해석을 작성합니다. # 응답 형식 (strict JSON only) { "summary": "두 사람 궁합의 핵심 흐름 (3~4문장)", "strengths": [ { "title": "...", "explanation": "...", "evidence": "오행 상생 또는 지지 합 등 근거" } ], "challenges": [ { "title": "...", "explanation": "...", "evidence": "오행 상극 또는 지지 충 등 근거" } ], "advice": "관계 개선 조언 (2~3문장)", "warning": "심각한 충돌 (없으면 null)", "confidence": "high"|"medium"|"low" } # 원칙 - strengths/challenges 각각 최소 2개 이상 - evidence는 두 사주의 오행 매칭, 지지 합/충, 일간 관계 인용 - JSON 외 텍스트 금지 """ def build_saju_user_message(saju: dict, analysis: dict, daeun: list[dict], current_year: int) -> str: """사주/분석/대운 데이터를 user 메시지로 직렬화.""" import json as _json return f"""# 사주 데이터 {_json.dumps(saju, ensure_ascii=False, indent=2)} # 종합 분석 {_json.dumps(analysis, ensure_ascii=False, indent=2)} # 대운 (8개) {_json.dumps(daeun, ensure_ascii=False, indent=2)} # 현재 연도 {current_year} # 작업 시스템 지침의 12항목 JSON으로 응답하세요. - 각 항목의 evidence는 위 데이터에서 인용된 요소를 반드시 포함. - confidence는 데이터 강도에 따라 정직하게 판정. """ def build_compat_user_message( saju_a: dict, saju_b: dict, analysis_a: dict, analysis_b: dict, score: int, breakdown: dict, ) -> str: import json as _json return f"""# A의 사주 {_json.dumps(saju_a, ensure_ascii=False, indent=2)} # A의 분석 {_json.dumps(analysis_a, ensure_ascii=False, indent=2)} # B의 사주 {_json.dumps(saju_b, ensure_ascii=False, indent=2)} # B의 분석 {_json.dumps(analysis_b, ensure_ascii=False, indent=2)} # 궁합 점수 + breakdown 점수: {score}/100 {_json.dumps(breakdown, ensure_ascii=False, indent=2)} # 작업 시스템 지침의 JSON으로 strengths/challenges 각각 최소 2개 이상, evidence 인용 포함. """ ``` - [ ] **Step 4: Run schema tests** Run: `cd saju-lab && python -m pytest tests/test_schema.py -v` Expected: 5 passed - [ ] **Step 5: Commit** ```bash git add saju-lab/app/interpret/prompt.py saju-lab/app/interpret/schema.py saju-lab/tests/test_schema.py git commit -m "feat(saju-lab): interpret/prompt.py + schema.py — 12항목 + 궁합 SYSTEM_PROMPT" ``` --- ### Task 25: interpret/pipeline.py (사주 + 궁합 Claude 호출) **Files:** - Create: `saju-lab/app/interpret/pipeline.py` - Create: `saju-lab/tests/test_pipeline.py` - [ ] **Step 1~5: tarot-lab/app/pipeline.py 패턴 그대로 재활용** `saju-lab/app/interpret/pipeline.py`: - `interpret_saju(saju, analysis, daeun, current_year) → dict` (tokens, cost, latency 포함) - `interpret_compat(saju_a, saju_b, analysis_a, analysis_b, score, breakdown) → dict` - 두 함수 모두 같은 `_call_claude` helper 공유 (system/user_text/validate만 다름) - `max_tokens=2400` (12항목이라 더 길게) - reroll 1회 - prompt-caching `cache_control: ephemeral` 테스트(`tests/test_pipeline.py`): respx mock으로 success/codeblock/reroll/validate-fail/http-error/cost 6 case + compat 동일 6 case = 총 12 case. - [ ] **Step 6: Run + Commit** ```bash git add saju-lab/app/interpret/pipeline.py saju-lab/tests/test_pipeline.py git commit -m "feat(saju-lab): interpret/pipeline.py — Claude 호출 + reroll (12 tests)" ``` --- ### Task 26: routers/saju.py + routers/compat.py + app/main.py **Files:** - Create: `saju-lab/app/routers/saju.py` - Create: `saju-lab/app/routers/compat.py` - Create: `saju-lab/app/main.py` - Create: `saju-lab/tests/test_routes.py` **API 엔드포인트:** `routers/saju.py` 6개: - `POST /api/saju/interpret` — 입력 → calculate_saju + perform_full_analysis + calculate_daeun + Claude interpret → DB save → 응답 - `GET /api/saju/readings` — list - `GET /api/saju/readings/{id}` — get - `PATCH /api/saju/readings/{id}` — favorite/memo - `DELETE /api/saju/readings/{id}` - `GET /api/saju/current-fortune?reading_id={id}` — 저장된 사주의 오늘 세운만 실시간 (AI 없음) `routers/compat.py` 5개: - `POST /api/saju/compat/interpret` — 두 사람 입력 → 두 사주 계산 + compatibility 점수 + Claude → DB save - `GET /api/saju/compat/readings` - `GET /api/saju/compat/readings/{id}` - `PATCH /api/saju/compat/readings/{id}` - `DELETE /api/saju/compat/readings/{id}` `main.py`는 tarot-lab과 동일 구조 + 두 router include. 테스트(`tests/test_routes.py`): TestClient + Claude pipeline mock으로 11 endpoint 모두 검증 (interpret 호출 시 pipeline.interpret_saju/compat을 monkeypatch). - [ ] **Step 1~10**: 6 endpoint(saju) + 5(compat) 각각 작성/테스트 - [ ] **Step 11: Run all saju-lab tests** Run: `cd saju-lab && python -m pytest -v` Expected: 70+ tests passing (constants 5 + solar_terms 32 + lunar 2 + core 30 + shinsal 10+ + analysis 30 + daeun 30 + compatibility 10+ + db 10 + schema 5 + pipeline 12 + routes 11) - [ ] **Step 12: Commit** ```bash git add saju-lab/app/main.py saju-lab/app/routers/ saju-lab/tests/test_routes.py git commit -m "feat(saju-lab): main.py + routers (saju 6 + compat 5) + 11 route tests" ``` --- ### Task 27: docker-compose.yml + nginx + deploy scripts (saju-lab 등록) **Files:** - Modify: `docker-compose.yml` - Modify: `nginx/default.conf` - Modify: `scripts/deploy.sh` (5 위치 추가) - Modify: `scripts/deploy-nas.sh` (SERVICES 추가) - [ ] **Step 1: docker-compose.yml에 saju-lab 추가 (tarot-lab 다음)** ```yaml saju-lab: build: context: ./saju-lab container_name: saju-lab restart: unless-stopped ports: - "18300:8000" environment: - TZ=${TZ:-Asia/Seoul} - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-} - SAJU_MODEL=${SAJU_MODEL:-claude-sonnet-4-6} - SAJU_COST_INPUT_PER_M=${SAJU_COST_INPUT_PER_M:-3.0} - SAJU_COST_OUTPUT_PER_M=${SAJU_COST_OUTPUT_PER_M:-15.0} - SAJU_TIMEOUT_SEC=${SAJU_TIMEOUT_SEC:-240} - SAJU_DATA_PATH=/app/data - CORS_ALLOW_ORIGINS=${CORS_ALLOW_ORIGINS:-http://localhost:3007,http://localhost:8080} volumes: - ${RUNTIME_PATH:-.}/data/saju:/app/data healthcheck: test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"] interval: 60s timeout: 5s retries: 3 ``` - [ ] **Step 2: nginx/default.conf — tarot 다음에 saju 추가** ```nginx # saju-lab API location /api/saju/ { resolver 127.0.0.11 valid=10s; set $saju_backend saju-lab:8000; proxy_http_version 1.1; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_read_timeout 300s; proxy_send_timeout 300s; proxy_connect_timeout 60s; proxy_pass http://$saju_backend$request_uri; } ``` - [ ] **Step 3: scripts/deploy-nas.sh SERVICES에 saju-lab 추가** ```bash SERVICES="lotto travel-proxy deployer stock music-lab insta-lab realestate-lab agent-office personal packs-lab video-lab image-lab tarot-lab saju-lab nginx scripts" ``` - [ ] **Step 4: scripts/deploy.sh 4개 변수에 saju-lab + saju 디렉토리** ```bash BUILD_TARGETS="lotto travel-proxy stock music-lab insta-lab realestate-lab agent-office personal packs-lab video-lab image-lab tarot-lab saju-lab frontend" CONTAINER_NAMES="lotto stock music-lab insta-lab blog-lab realestate-lab agent-office personal packs-lab travel-proxy video-lab image-lab tarot-lab saju-lab frontend" HEALTH_ENDPOINTS="lotto stock travel-proxy music-lab insta-lab realestate-lab agent-office personal packs-lab video-lab image-lab tarot-lab saju-lab redis" DATA_DIRS="music stock insta realestate agent-office personal video image tarot saju" ``` - [ ] **Step 5: Commit** ```bash git add docker-compose.yml nginx/default.conf scripts/deploy.sh scripts/deploy-nas.sh git commit -m "feat(deploy): saju-lab 컨테이너 + nginx + 5위치 동기화" ``` --- ### Task 28: web-ui api.js + routes.jsx + Icons (saju helpers) **Files (web-ui repo):** - Modify: `web-ui/src/api.js` - Modify: `web-ui/src/routes.jsx` - Modify: `web-ui/src/components/Icons.jsx` - [ ] **Step 1: api.js에 saju + compat helpers 추가 (tarot helper 다음에)** ```javascript // ====== Saju ====== export function sajuInterpret(body) { return apiPost('/api/saju/interpret', body); } export function sajuListReadings({ page = 1, size = 20, favorite } = {}) { const qs = new URLSearchParams(); qs.set('page', page); qs.set('size', size); if (favorite !== undefined) qs.set('favorite', favorite); return apiGet(`/api/saju/readings?${qs.toString()}`); } export function sajuGetReading(id) { return apiGet(`/api/saju/readings/${id}`); } export function sajuPatchReading(id, body) { return apiPatch(`/api/saju/readings/${id}`, body); } export function sajuDeleteReading(id) { return apiDelete(`/api/saju/readings/${id}`); } export function sajuCurrentFortune(readingId) { return apiGet(`/api/saju/current-fortune?reading_id=${readingId}`); } // ====== Compatibility ====== export function compatInterpret(body) { return apiPost('/api/saju/compat/interpret', body); } export function compatListReadings({ page = 1, size = 20, favorite } = {}) { const qs = new URLSearchParams(); qs.set('page', page); qs.set('size', size); if (favorite !== undefined) qs.set('favorite', favorite); return apiGet(`/api/saju/compat/readings?${qs.toString()}`); } export function compatGetReading(id) { return apiGet(`/api/saju/compat/readings/${id}`); } export function compatPatchReading(id, body) { return apiPatch(`/api/saju/compat/readings/${id}`, body); } export function compatDeleteReading(id) { return apiDelete(`/api/saju/compat/readings/${id}`); } ``` - [ ] **Step 2: routes.jsx에 saju 라우트 4개 + navLinks 추가** 기존 tarot 라우트 패턴 따라: - `/saju` → SajuLanding - `/saju/reading` → Saju (입력 + 결과) - `/saju/compatibility` → Compatibility - `/saju/history` → SajuHistory > **참고**: 실제 React 컴포넌트 파일(Saju.jsx, Compatibility.jsx 등)은 시안 받은 후 작성. 현재 task는 라우트 등록 + 빈 placeholder 컴포넌트만 추가. - [ ] **Step 3: Icons.jsx에 IconSaju 추가** (임시 SVG — 8괘 또는 음양 심볼) - [ ] **Step 4: Commit (web-ui)** ```bash cd ../web-ui git add src/api.js src/routes.jsx src/components/Icons.jsx git commit -m "feat(saju): api helpers (saju + compat) + 라우트 + 아이콘" cd ../web-backend ``` --- ### Task 29: web-ui /saju UI 페이지 (시안 받은 후) **Files (web-ui repo):** - Create: `web-ui/src/pages/saju/Saju.jsx` - Create: `web-ui/src/pages/saju/SajuForm.jsx` - Create: `web-ui/src/pages/saju/SajuResult.jsx` - Create: `web-ui/src/pages/saju/Compatibility.jsx` - Create: `web-ui/src/pages/saju/CompatibilityResult.jsx` - Create: `web-ui/src/pages/saju/SajuHistory.jsx` - Create: `web-ui/src/pages/saju/Saju.css` - Create: `web-ui/src/pages/saju/data/constants.js` - Create: `web-ui/src/pages/saju/hooks/useSajuForm.js` - Create: `web-ui/src/pages/saju/hooks/useSajuInterpretation.js` - Create: `web-ui/src/pages/saju/components/SajuBoard.jsx` - Create: `web-ui/src/pages/saju/components/ElementChart.jsx` - Create: `web-ui/src/pages/saju/components/DaeunTimeline.jsx` - Create: `web-ui/src/pages/saju/components/InterpretationPanel.jsx` **⚠️ 이 Task는 사용자로부터 UI 시안 이미지를 받은 후 진행**합니다. 시안 없이 진행하면 재작업 가능성이 높음. 시안 받으면 tarot 페이지(`web-ui/src/pages/tarot/`) 구조를 참조하여 동일 패턴으로 구성: - 입력 폼 → useSajuForm hook - API 호출 → useSajuInterpretation hook (sajuInterpret 호출, AI 응답 도착 시 자동 탭 전환) - 결과 페이지: 4기둥 시각화 + 오행 차트 + 대운 타임라인 + 12항목 아코디언 - 디자인은 saju-web 디자인 시스템(딥 네이비 + 골드)을 web-ui에 맞춰 조정 상세 컴포넌트 명세는 시안 + spec Section 6-6 + saju-web 디렉토리 참고. - [ ] **Step 1~N**: 시안 도착 후 별도 mini-plan으로 진행 ```bash git commit -m "feat(saju): web-ui /saju 페이지 — 입력/결과/궁합/히스토리" ``` --- ## Phase 2 완료 ✓ Phase 2 종료 시점 점검: - [ ] `saju-lab/`에 모든 테스트 통과 (목표: 130+ tests) - [ ] Reference fixture 30 케이스 모두 saju 계산 일치 - [ ] `docker-compose.yml`에 saju-lab 항목 존재 (18300) - [ ] `nginx/default.conf`에 `/api/saju/` location 존재 - [ ] deploy 스크립트 5위치 모두 saju-lab 포함 - [ ] `web-ui/src/api.js`에 saju + compat helpers - [ ] `web-ui/src/routes.jsx`에 /saju 라우트 (UI는 시안 후) NAS 배포 절차: 1. `cd web-backend && git push` → 자동 배포 2. 배포 완료 후 SSH: ```bash docker logs -f saju-lab # 시작 확인 curl http://localhost:18300/health ``` 3. 시안 받으면 web-ui Phase 2 UI 진행 --- ## 전체 검증 체크리스트 ### Phase 1 검증 - [ ] tarot-lab pytest 21 passed - [ ] agent-office migrate_tarot pytest 3 passed - [ ] agent-office에서 tarot import 0건 (grep 검색) - [ ] 로컬 e2e: /tarot 리딩 1회 성공 - [ ] git log: 12 commit (Task 1~12) ### Phase 2 검증 - [ ] saju-lab pytest 130+ passed - [ ] reference fixture 30 케이스 일치 - [ ] 로컬 e2e: /api/saju/interpret + /api/saju/compat/interpret 각 1회 성공 (curl 또는 Swagger) - [ ] git log: Phase 1 + Phase 2 총 28+ commit ### NAS 배포 후 - [ ] 두 컨테이너 모두 healthy - [ ] 데이터 마이그레이션 후 tarot.db 행 수 = agent_office.db 의 tarot_readings 행 수 - [ ] /api/tarot/* 5분 SLA (504 없음) - [ ] /api/saju/* 5분 SLA --- ## 위험 + 대응 | 위험 | 대응 | |------|------| | sxtwl API가 saju-web의 solarlunar와 절기 일자 1일 차이 | reference fixture 재생성 (Node→Python 모두 sxtwl 호환되도록) 또는 saju-web에 sxtwl 동등 라이브러리 적용 | | 계산 엔진 포팅 reference 일부 mismatch | 해당 input 별도 issue 기록 + 30개 중 28~29건 통과 시 우선 통과로 처리 (다음 cycle에서 보강) | | docker-compose의 RUNTIME_PATH가 호스트마다 다름 | `${RUNTIME_PATH:-.}/data/...` 패턴 (이미 다른 lab에서 사용 중) | | Phase 2 UI 시안 지연 | Phase 2 백엔드만 먼저 배포 → /api/saju/* 사용 가능 (Swagger UI 또는 curl). UI는 시안 받은 후 | | agent-office cutover 시점에 운영 tarot 요청 끊김 | nginx /api/tarot/ → tarot-lab 라우팅이 cutover 전에 추가되어 있어 끊김 없음 | --- ## 참고 자료 - spec: `docs/superpowers/specs/2026-05-25-saju-tarot-lab-migration-design.md` - tarot 원본 구현: `agent-office/app/tarot/`, `agent-office/app/routers/tarot.py` - saju-web: `C:/Users/jaeoh/Desktop/workspace/saju-web/` - 다른 lab 패턴: `web-backend/insta-lab/`, `music-lab/`, `realestate-lab/` - sxtwl 라이브러리: https://github.com/yuangu/sxtwl_cpp (Python binding) - 배포 스크립트 동기화 memory: `~/.claude/.../memory/feedback_deploy_script_sync.md`