fix: use USDA API for nutrition, update Dockerfile for Hugging Face

Dockerfile

@@ -7,4 +7,13 @@ RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .
 
+# Create data directory
+RUN mkdir -p /tmp/data
+
+# Initialize database
+RUN python init_db.py
+
+# Expose port 7860 for Hugging Face Spaces
+EXPOSE 7860
+
 CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

env_example.txt

@@ -0,0 +1,8 @@
+# USDA API Key for nutrition data (get from https://fdc.nal.usda.gov/api-key-signup.html)
+USDA_API_KEY=your_usda_api_key_here
+
+# Database configuration (optional, defaults to SQLite)
+DATABASE_URL=sqlite:///tmp/data/health_assistant.db
+
+# Hugging Face Spaces configuration
+HF_SPACE_ID=your_space_id 

init_db.py

@@ -1,70 +1,13 @@
-from .database import Base, engine, SessionLocal
-from .models.meal_log import MealLog
-from .models.nutrition import Nutrition
-import json
+from database import engine
+from models.nutrition import Base
+from models.meal_log import Base as MealBase
 
-def init_db():
-    """初始化資料庫並填入初始營養數據"""
+def init_database():
+    """Initialize database tables"""
     print("Creating database tables...")
-    # 根據模型建立所有表格
     Base.metadata.create_all(bind=engine)
+    MealBase.metadata.create_all(bind=engine)
     print("Database tables created successfully!")
 
-    # 檢查是否已有資料，避免重複新增
-    db = SessionLocal()
-    if db.query(Nutrition).count() == 0:
-        print("Populating nutrition table with initial data...")
-        
-        # 從 main.py 移植過來的模擬資料
-        mock_nutrition_data = [
-            {
-                "food_name": "hamburger", "chinese_name": "漢堡", "calories": 540, "protein": 25, "fat": 31, "carbs": 40,
-                "fiber": 3, "sugar": 6, "sodium": 1040, "health_score": 45,
-                "recommendations": ["脂肪和鈉含量過高，建議減少食用頻率。"],
-                "warnings": ["高熱量", "高脂肪", "高鈉"]
-            },
-            {
-                "food_name": "pizza", "chinese_name": "披薩", "calories": 266, "protein": 11, "fat": 10, "carbs": 33,
-                "fiber": 2, "sugar": 4, "sodium": 598, "health_score": 65,
-                "recommendations": ["可搭配沙拉以增加纖維攝取。"],
-                "warnings": ["高鈉"]
-            },
-            {
-                "food_name": "sushi", "chinese_name": "壽司", "calories": 200, "protein": 12, "fat": 8, "carbs": 20,
-                "fiber": 1, "sugar": 2, "sodium": 380, "health_score": 85,
-                "recommendations": ["優質的蛋白質和碳水化合物來源。"],
-                "warnings": []
-            },
-            {
-                "food_name": "fried rice", "chinese_name": "炒飯", "calories": 238, "protein": 8, "fat": 12, "carbs": 26,
-                "fiber": 2, "sugar": 3, "sodium": 680, "health_score": 60,
-                "recommendations": ["注意油脂和鈉含量。"],
-                "warnings": ["高鈉"]
-            },
-            {
-                "food_name": "chicken wings", "chinese_name": "雞翅", "calories": 203, "protein": 18, "fat": 14, "carbs": 0,
-                "fiber": 0, "sugar": 0, "sodium": 380, "health_score": 70,
-                "recommendations": ["蛋白質的良好來源。"],
-                "warnings": []
-            },
-            {
-                "food_name": "salad", "chinese_name": "沙拉", "calories": 33, "protein": 3, "fat": 0.2, "carbs": 6,
-                "fiber": 3, "sugar": 3, "sodium": 65, "health_score": 95,
-                "recommendations": ["低熱量高纖維，是健康的選擇。"],
-                "warnings": []
-            }
-        ]
-
-        for food_data in mock_nutrition_data:
-            db_item = Nutrition(**food_data)
-            db.add(db_item)
-        
-        db.commit()
-        print(f"{len(mock_nutrition_data)} items populated.")
-    else:
-        print("Nutrition table already contains data. Skipping population.")
-    
-    db.close()
-
 if __name__ == "__main__":
-    init_db()
+    init_database()

main.py

@@ -206,5 +206,5 @@ def generate_warnings(nutrition: Dict[str, Any]) -> List[str]:
     return warnings
 
 if __name__ == "__main__":
-    # It's better to run with `uvicorn backend.main:app --reload` from the project root.
-    uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)
+    # For Hugging Face Spaces deployment
+    uvicorn.run("main:app", host="0.0.0.0", port=7860, reload=False)

services/nutrition_api_service.py

@@ -12,7 +12,7 @@ logger = logging.getLogger(__name__)
 load_dotenv()
 
 # 從環境變數中獲取 API 金鑰
-USDA_API_KEY = os.getenv("USDA_API_KEY", "DEMO_KEY")
+USDA_API_KEY = os.getenv("USDA_API_KEY")
 USDA_API_URL = "https://api.nal.usda.gov/fdc/v1/foods/search"
 
 # 我們關心的主要營養素及其在 USDA API 中的名稱或編號
@@ -35,7 +35,7 @@ def fetch_nutrition_data(food_name: str):
     :return: 包含營養資訊的字典，如果找不到則返回 None。
     """
     if not USDA_API_KEY:
-        logger.error("USDA_API_KEY 未設定，無法查詢營養資訊。")
+        logger.error("USDA_API_KEY 未設定，無法查詢營養資訊。請在環境變數中設定 USDA_API_KEY")
         return None
 
     params = {