feat: use mongodb

.github/workflows/main.yml

@@ -40,6 +40,7 @@ jobs:
           build-args: |
             OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY }}
             ACCESS_TOKEN=${{ secrets.ACCESS_TOKEN }}
+            MONGODB_URL=${{ secrets.MONGODB_URL }}
 
   deploy:
     needs: build
@@ -58,4 +59,5 @@ jobs:
           docker run -d -p 8001:8001 --name ${{ github.repository_id }} --restart always \
             -e OPENAI_API_KEYL=${{ secrets.OPENAI_API_KEY }} \
             -e ACCESS_TOKEN=${{ secrets.ACCESS_TOKEN }} \
+            -e MONGODB_URL=${{ secrets.MONGODB_URL }} \
             ${{ env.DOCKER_IMAGE }}:latest

Dockerfile

@@ -10,8 +10,10 @@ COPY ./app /code/app
 
 ARG OPENAI_API_KEY
 ARG ACCESS_TOKEN
+ARG MONGODB_URL
 
 ENV OPENAI_API_KEY=${OPENAI_API_KEY}
 ENV ACCESS_TOKEN=${ACCESS_TOKEN}
+ENV MONGODB_URL=${MONGODB_URL}
 
 CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8001"]

app/config.py

@@ -1,5 +1,6 @@
 import os
 from pathlib import Path
+
 from dotenv import load_dotenv
 from openai import OpenAI
 
@@ -10,4 +11,5 @@
 
 client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
 
-ACCESS_TOKEN = os.environ.get("ACCESS_TOKEN")
+ACCESS_TOKEN = os.environ.get("ACCESS_TOKEN")
+MONGODB_URL = os.environ.get("MONGODB_URL")

app/database.py

@@ -0,0 +1,9 @@
+from motor.motor_asyncio import AsyncIOMotorClient
+
+from app.config import MONGODB_URL
+
+client = AsyncIOMotorClient(MONGODB_URL)
+db = client.deening
+recipe_collection = db.recipes
+cooking_step_collection = db.cooking_steps
+ingredient_collection = db.ingredients

app/main.py

@@ -1,8 +1,9 @@
 from fastapi import FastAPI, Depends
+
+from app.dependencies.auth import verify_token
 from app.routes import ping
 from app.routes.food import ingredient_detect
 from app.routes.recipe import recipe, ingredient, cooking_step
-from app.dependencies.auth import verify_token
 
 app = FastAPI(
     title="Deening API",
@@ -26,4 +27,4 @@
 app.include_router(recipe.router, dependencies=[Depends(verify_token)])
 app.include_router(ingredient.router, dependencies=[Depends(verify_token)])
 app.include_router(cooking_step.router, dependencies=[Depends(verify_token)])
-app.include_router(ingredient_detect.router, dependencies=[Depends(verify_token)])
+app.include_router(ingredient_detect.router, dependencies=[Depends(verify_token)])

app/models/food/ingredient_detect_models.py

@@ -1,15 +1,20 @@
-from pydantic import BaseModel
 from typing import List
+
 from fastapi import UploadFile
+from pydantic import BaseModel
+
 
 class IngredientDetectRequest(BaseModel):
     image: UploadFile
 
+
 class DetectedIngredient(BaseModel):
     ingredient_name: str
 
+
 class IngredientDetectResponse(BaseModel):
     ingredients: List[DetectedIngredient]
 
+
 class NoIngredientsFoundResponse(BaseModel):
-    message: str = "No ingredients found in the image"
+    message: str = "No ingredients found in the image"

app/models/ping_models.py

@@ -1,4 +1,5 @@
 from pydantic import BaseModel
 
+
 class PingResponse(BaseModel):
-    message: str
+    message: str

app/models/recipe/cooking_step_models.py

@@ -1,10 +1,13 @@
-from pydantic import BaseModel
 from typing import List
 
+from pydantic import BaseModel
+
+
 class CookingStepRequest(BaseModel):
     recipe_id: str
     step_number: int
 
+
 class CookingStep(BaseModel):
     recipe_id: str
     step_number: int
@@ -14,6 +17,8 @@ class CookingStep(BaseModel):
     ingredients_used: List[str]
     tips: str
 
+
 class CookingStepResponse(BaseModel):
+    id: str
     cooking_step: CookingStep
-    image_url: str
+    image_url: str

app/models/recipe/ingredient_models.py

@@ -1,9 +1,12 @@
-from pydantic import BaseModel
 from typing import List
 
+from pydantic import BaseModel
+
+
 class IngredientRequest(BaseModel):
     ingredient_name: str
 
+
 class NutritionalInfo(BaseModel):
     calories: int
     protein: float
@@ -13,6 +16,7 @@ class NutritionalInfo(BaseModel):
     vitamins: str
     minerals: str
 
+
 class Ingredient(BaseModel):
     name: str
     description: str
@@ -21,6 +25,8 @@ class Ingredient(BaseModel):
     storage_tips: str
     culinary_uses: List[str]
 
+
 class IngredientResponse(BaseModel):
+    id: str
     ingredient: Ingredient
-    image_url: str
+    image_url: str

app/models/recipe/recipe_models.py

@@ -1,21 +1,25 @@
 from pydantic import BaseModel
 from typing import List
 
+
 class Ingredient(BaseModel):
     name: str
     amount: float
     unit: str
 
+
 class Instruction(BaseModel):
     step: int
     description: str
 
+
 class Nutrition(BaseModel):
     calories: int
     protein: str
     carbohydrates: str
     fat: str
 
+
 class Recipe(BaseModel):
     name: str
     description: str
@@ -30,10 +34,12 @@ class Recipe(BaseModel):
     tags: List[str]
     source: str
 
+
 class RecipeRequest(BaseModel):
     food_name: str
 
+
 class RecipeResponse(BaseModel):
     id: str
     recipe: Recipe
-    image_url: str
+    image_url: str

app/routes/food/ingredient_detect.py

@@ -1,18 +1,23 @@
-from fastapi import APIRouter, File, UploadFile, HTTPException
-from pydantic import BaseModel
-import json
 import base64
+import json
 import logging
 
+from fastapi import APIRouter, File, UploadFile, HTTPException
+from pydantic import BaseModel
+
 from app.config import client
-from app.models.food.ingredient_detect_models import IngredientDetectResponse, DetectedIngredient, IngredientDetectRequest, NoIngredientsFoundResponse
+from app.models.food.ingredient_detect_models import IngredientDetectResponse, DetectedIngredient, \
+    NoIngredientsFoundResponse
 
 router = APIRouter()
 
+
 class ErrorResponse(BaseModel):
     error: str
 
-@router.post("/ingredient_detect", tags=["Food"], response_model=IngredientDetectResponse, responses={400: {"model": ErrorResponse}, 404: {"model": NoIngredientsFoundResponse}})
+
+@router.post("/ingredient_detect", tags=["Food"], response_model=IngredientDetectResponse,
+             responses={400: {"model": ErrorResponse}, 404: {"model": NoIngredientsFoundResponse}})
 async def ingredient_detect(image: UploadFile = File(...)):
     """
     업로드된 이미지 파일에서 식재료를 탐색해 반환합니다.
@@ -68,7 +73,8 @@ async def ingredient_detect(image: UploadFile = File(...)):
         except json.JSONDecodeError:
             raise HTTPException(status_code=400, detail="생성된 식재료 정보를 JSON으로 파싱할 수 없습니다.")
 
-        detected_ingredients = [DetectedIngredient(**ingredient) for ingredient in ingredient_detect_json["ingredients"]]
+        detected_ingredients = [DetectedIngredient(**ingredient) for ingredient in
+                                ingredient_detect_json["ingredients"]]
 
         if not detected_ingredients:
             return NoIngredientsFoundResponse(status_code=404)
@@ -79,4 +85,4 @@ async def ingredient_detect(image: UploadFile = File(...)):
         raise http_ex
     except Exception as e:
         logging.error(f"Unexpected error: {str(e)}")
-        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")

app/routes/ping.py

@@ -1,11 +1,13 @@
 from fastapi import APIRouter
+
 from app.models.ping_models import PingResponse
 
 router = APIRouter()
 
+
 @router.get("/ping", response_model=PingResponse)
 async def ping():
     """
     Health check endpoint
     """
-    return {"message": "pong"}
+    return {"message": "pong"}

app/routes/recipe/cooking_step.py

@@ -1,29 +1,47 @@
+import json
+
+from bson import ObjectId
 from fastapi import APIRouter, HTTPException
-from app.models.recipe.cooking_step_models import CookingStepRequest, CookingStep, CookingStepResponse
 from pydantic import BaseModel
-from app.config import client
-import json
 
-from app.routes.recipe.recipe import recipe_store
+from app.config import client as openai_client
+from app.database import recipe_collection, cooking_step_collection
+from app.models.recipe.cooking_step_models import CookingStepRequest, CookingStep, CookingStepResponse
 
 router = APIRouter()
 
+
 class ErrorResponse(BaseModel):
     error: str
 
-@router.post("/cooking_step", tags=["Recipe"],  response_model=CookingStepResponse, responses={400: {"model": ErrorResponse}, 404: {"model": ErrorResponse}})
-async def get_cooking_step_info(request: CookingStepRequest):
+
+@router.post("/cooking_step", tags=["Recipe"], response_model=CookingStepResponse,
+             responses={400: {"model": ErrorResponse}, 404: {"model": ErrorResponse}})
+async def get_or_create_cooking_step_info(request: CookingStepRequest):
     """
-    레시피의 특정 조리 단계에 대한 상세 정보를 생성합니다.
+    레시피의 특정 조리 단계에 대한 상세 정보를 반환하거나 생성합니다.
     """
-    if request.recipe_id not in recipe_store:
-        raise HTTPException(status_code=404, detail="레시피를 찾을 수 없습니다.")
-
-    stored_data = recipe_store[request.recipe_id]
-    recipe = stored_data["recipe"]
-
     try:
-        # 조리 과정 정보 생성 프롬프트
+        # 기존 조리 단계 정보 검색
+        existing_step = await cooking_step_collection.find_one({
+            "recipe_id": request.recipe_id,
+            "step_number": request.step_number
+        })
+
+        if existing_step:
+            # 기존 정보가 있으면 그대로 반환
+            cooking_step = CookingStep(**existing_step)
+            return CookingStepResponse(
+                id=str(existing_step['_id']),
+                cooking_step=cooking_step,
+                image_url=existing_step.get('image_url')
+            )
+
+        # 기존 정보가 없으면 새로 생성
+        recipe = await recipe_collection.find_one({"_id": ObjectId(request.recipe_id)})
+        if not recipe:
+            raise HTTPException(status_code=404, detail="레시피를 찾을 수 없습니다.")
+
         cooking_step_prompt = f"""제공된 레시피에 대한 자세한 조리 과정 정보를 JSON 형식으로 생성해주세요. 다음 구조를 따라주세요:
 
         {{
@@ -43,8 +61,7 @@ async def get_cooking_step_info(request: CookingStepRequest):
         주의: 반드시 다른 텍스트 없이 유효한 JSON 형식으로만 응답해주세요.
         """
 
-        # 조리 과정 정보 생성
-        cooking_step_response = client.chat.completions.create(
+        cooking_step_response = openai_client.chat.completions.create(
             model="chatgpt-4o-latest",
             messages=[
                 {"role": "system", "content": "당신은 전문 요리사입니다. 주어진 레시피의 특정 조리 단계에 대한 상세한 정보를 JSON 형식으로 제공합니다."},
@@ -55,8 +72,7 @@ async def get_cooking_step_info(request: CookingStepRequest):
         cooking_step_json = json.loads(cooking_step_response.choices[0].message.content)
         cooking_step = CookingStep(**cooking_step_json)
 
-        # 이미지 생성 프롬프트
-        image_prompt = f"""A high-quality, detailed photo demonstrating the cooking step for {recipe.name}, step number {cooking_step.step_number}:
+        image_prompt = f"""A high-quality, detailed photo demonstrating the cooking step for {recipe['name']}, step number {cooking_step.step_number}:
 
         - Description: {cooking_step.description}
         - Tools used: {', '.join(cooking_step.tools_needed)}
@@ -67,20 +83,44 @@ async def get_cooking_step_info(request: CookingStepRequest):
         The image should be from a slightly elevated angle to give a clear view of the cooking surface and the chef's hands (if applicable).
         """
 
-        # DALL-E를 사용한 이미지 생성
-        image_response = client.images.generate(
+        image_response = openai_client.images.generate(
             model="dall-e-3",
             prompt=image_prompt,
             size="1024x1024",
             quality="standard",
             n=1,
         )
 
-        # 이미지 URL 가져오기
         image_url = image_response.data[0].url
 
-        return CookingStepResponse(cooking_step=cooking_step, image_url=image_url)
+        cooking_step_dict = cooking_step.dict()
+        cooking_step_dict['image_url'] = image_url
+        result = await cooking_step_collection.insert_one(cooking_step_dict)
+        cooking_step_id = str(result.inserted_id)
+
+        print(cooking_step_response)
+        print(image_response)
+
+        return CookingStepResponse(id=cooking_step_id, cooking_step=cooking_step, image_url=image_url)
     except json.JSONDecodeError:
         raise HTTPException(status_code=400, detail="생성된 조리 과정 정보를 JSON으로 파싱할 수 없습니다.")
     except Exception as e:
-        raise HTTPException(status_code=400, detail=str(e))
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@router.get("/cooking_step/{cooking_step_id}", tags=["Recipe"], response_model=CookingStepResponse,
+            responses={404: {"model": ErrorResponse}})
+async def get_cooking_step_by_id(cooking_step_id: str):
+    """
+    주어진 ID에 대한 조리 단계 정보를 반환합니다.
+    """
+    try:
+        cooking_step_data = await cooking_step_collection.find_one({"_id": ObjectId(cooking_step_id)})
+        if not cooking_step_data:
+            raise HTTPException(status_code=404, detail="조리 단계 정보를 찾을 수 없습니다.")
+
+        image_url = cooking_step_data.pop('image_url', None)
+        cooking_step = CookingStep(**cooking_step_data)
+        return CookingStepResponse(id=str(cooking_step_data['_id']), cooking_step=cooking_step, image_url=image_url)
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))