🐛 fix: 실행되다 멈추는 오류 수정

.github/workflows/cicd.yml

@@ -37,6 +37,7 @@ jobs:
           context: .
           file: ./Dockerfile
           push: true
+          no-cache: true
           tags: |
             ${{ env.IMAGE }}:latest
             ${{ env.IMAGE }}:${{ github.sha }}
@@ -45,7 +46,6 @@ jobs:
     name: Deploy to Server
     needs: docker-build-push
     runs-on: ubuntu-latest
-    if: github.ref == 'refs/heads/main'
 
     steps:
       - name: Deploy via SSH
@@ -62,4 +62,6 @@ jobs:
               -p 8000:8000 \
               -e OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY }} \
               -e OPENAI_MODEL=${{ secrets.OPENAI_MODEL }} \
-              ${{ env.IMAGE }}:latest
+              ${{ env.IMAGE }}:latest
+
+            docker image prune -af || true

Dockerfile

@@ -6,4 +6,6 @@ COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .
+
+RUN python -m leftovers.domain.recommend.service.train
 CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

app/core/exception/global_error_handler.py → leftovers/core/exception/global_error_handler.py

@@ -2,7 +2,7 @@
 from fastapi.responses import JSONResponse
 from pydantic import ValidationError
 
-from app.core.response.api_response import fail
+from leftovers.core.response.api_response import fail
 
 # 공통 응답 포맷 생성기
 def error_response(status: int, message: str, extra: dict = None):

app/core/external/open_ai_client.py → leftovers/core/external/open_ai_client.py

@@ -1,5 +1,5 @@
 from openai import OpenAI
-from app.core.config.config import settings # 환경설정 로더 가져오기
+from leftovers.core.config.config import settings # 환경설정 로더 가져오기
 
 _cfg = settings() # settings
 

app/domain/recommend/api/recommend_api.py → leftovers/domain/recommend/api/recommend_api.py

@@ -1,8 +1,8 @@
 from fastapi import APIRouter
-from app.core.response.api_response import Envelope, ok, fail
-from app.domain.recommend.schemas.recommend_request import RecommendReq
-from app.domain.recommend.schemas.recommend_response import RecommendRes
-from app.domain.recommend.service import evaluator, loader
+from leftovers.core.response.api_response import Envelope, ok, fail
+from leftovers.domain.recommend.schemas.recommend_request import RecommendReq
+from leftovers.domain.recommend.schemas.recommend_response import RecommendRes
+from leftovers.domain.recommend.service import evaluator, loader
 
 router = APIRouter(prefix="/menus")
 

app/domain/recommend/service/evaluator.py → leftovers/domain/recommend/service/evaluator.py

@@ -1,7 +1,7 @@
 import numpy as np
-from app.domain.recommend.service.scoring import compute_score
-from app.domain.recommend.schemas.recommend_response import MatchItem
-from app.domain.recommend.service import loader, matcher
+from leftovers.domain.recommend.service.scoring import compute_score
+from leftovers.domain.recommend.schemas.recommend_response import MatchItem
+from leftovers.domain.recommend.service import loader, matcher
 
 # 음식 영양 성분을 딕셔너리에서 numpy 배열로 변환(ML 모델 입력은 항상 숫자여야 하므로)
 def to_feat(n: dict) -> np.ndarray:

app/domain/recommend/service/loader.py → leftovers/domain/recommend/service/loader.py

@@ -1,10 +1,10 @@
 from typing import List
 import joblib
 
-from app.domain.recommend.service.food_kfda_loader import load_kfda_excels
+from leftovers.domain.recommend.service.food_kfda_loader import load_kfda_excels
 
-FOOD_FILES = ["app/domain/recommend/data/foodData1.xlsx", "app/domain/recommend/data/foodData2.xlsx"]
-MODEL_DIR = "app/domain/recommend/model_store"
+FOOD_FILES = ["leftovers/domain/recommend/data/foodData1.xlsx", "leftovers/domain/recommend/data/foodData2.xlsx"]
+MODEL_DIR = "leftovers/domain/recommend/model_store"
 
 # 컨셉
 CONCEPTS = {"diet", "keto", "low_sodium", "glycemic", "bulking"}

app/domain/recommend/service/matcher.py → leftovers/domain/recommend/service/matcher.py

@@ -1,6 +1,6 @@
 import numpy as np
 from sklearn.metrics.pairwise import cosine_similarity
-from app.domain.recommend.service import loader
+from leftovers.domain.recommend.service import loader
 
 # 메뉴 이름이 유사한 것 찾기
 def match_top1(query: str):

app/domain/recommend/service/train.py → leftovers/domain/recommend/service/train.py

@@ -8,11 +8,11 @@
 from sklearn.metrics import mean_absolute_error
 from sklearn.impute import SimpleImputer
 
-from app.domain.recommend.service.food_kfda_loader import load_kfda_excels
-from app.domain.recommend.service.scoring import fit_calibration, compute_score
+from leftovers.domain.recommend.service.food_kfda_loader import load_kfda_excels
+from leftovers.domain.recommend.service.scoring import fit_calibration, compute_score
 
-FOOD_FILES = ["app/domain/recommend/data/foodData1.xlsx", "app/domain/recommend/data/foodData2.xlsx"]
-MODEL_DIR = Path("app/domain/recommend/model_store")
+FOOD_FILES = ["leftovers/domain/recommend/data/foodData1.xlsx", "leftovers/domain/recommend/data/foodData2.xlsx"]
+MODEL_DIR = Path("leftovers/domain/recommend/model_store")
 MODEL_DIR.mkdir(parents=True, exist_ok=True)
 
 # 컨셉

app/domain/tip/api/tip_api.py → leftovers/domain/tip/api/tip_api.py

@@ -1,10 +1,10 @@
 from fastapi import APIRouter, HTTPException
 from typing import List
 
-from app.core.response.api_response import Envelope, ok
-from app.domain.tip.schemas.tip_request import TipRequest
-from app.domain.tip.schemas.tip_response import TipItem
-from app.domain.tip.service.prompt import chatForTip
+from leftovers.core.response.api_response import Envelope, ok
+from leftovers.domain.tip.schemas.tip_request import TipRequest
+from leftovers.domain.tip.schemas.tip_response import TipItem
+from leftovers.domain.tip.service.prompt import chatForTip
 
 import json
 from json import JSONDecodeError

app/domain/tip/service/prompt.py → leftovers/domain/tip/service/prompt.py

@@ -1,5 +1,5 @@
-from app.core.external.open_ai_client import client
-from app.core.config.config import settings
+from leftovers.core.external.open_ai_client import client
+from leftovers.core.config.config import settings
 
 # OpenAI Responses API의 structured outputs 기능에서 쓰는 JSON Schema
 # TIp SCHEMA의 형태로 응답을 제공함

main.py

@@ -2,10 +2,10 @@
 from pydantic import ValidationError
 from contextlib import asynccontextmanager
 
-from app.domain.recommend.service import loader
-from app.domain.tip.api import tip_api
-from app.domain.recommend.api import recommend_api
-from app.core.exception.global_error_handler import (
+from leftovers.domain.recommend.service import loader
+from leftovers.domain.tip.api import tip_api
+from leftovers.domain.recommend.api import recommend_api
+from leftovers.core.exception.global_error_handler import (
     validation_error_handler,
     http_exception_handler,
     global_exception_handler,
@@ -17,7 +17,6 @@
 async def lifespan(app: FastAPI):
     loop = asyncio.get_event_loop()
     await loop.run_in_executor(None, loader.load_all)  
-    loader.load_all()
     print("모델/DB 로딩 완료")
 
     yield # 여기까지 오면 서버 실행