Create test_app.py with inline endpoints to isolate router import issue

main.py

@@ -1,6 +1,6 @@
-# Import the FastAPI app from app.py
-from app import app
+# Import the FastAPI app from test_app.py
+from test_app import app
 
 # This file exists to satisfy Hugging Face Spaces' Dockerfile
 # which expects: uvicorn main:app
-# The actual app is defined in app.py 
+# Using test_app.py to isolate the router import issue 

test_app.py

@@ -0,0 +1,76 @@
+from fastapi import FastAPI, File, UploadFile, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from typing import Dict, Any, List, Optional
+
+app = FastAPI(title="Health Assistant API - Test Version")
+
+# 配置 CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# 直接在這個檔案中定義 router 和端點
+class WeightEstimationResponse(BaseModel):
+    food_type: str
+    estimated_weight: float
+    weight_confidence: float
+    weight_error_range: List[float]
+    nutrition: Dict[str, Any]
+    reference_object: Optional[str] = None
+    note: str
+
+@app.get("/")
+async def root():
+    return {"message": "Health Assistant API - Test Version is running"}
+
+@app.get("/health")
+async def health_check():
+    return {
+        "status": "healthy",
+        "version": "test",
+        "endpoints": [
+            "/ai/analyze-food-image/",
+            "/ai/analyze-food-image-with-weight/",
+            "/ai/health"
+        ]
+    }
+
+@app.post("/ai/analyze-food-image/")
+async def analyze_food_image_endpoint(file: UploadFile = File(...)):
+    """測試食物圖片分析端點"""
+    if not file.content_type or not file.content_type.startswith("image/"):
+        raise HTTPException(status_code=400, detail="上傳的檔案不是圖片格式。")
+    
+    return {"food_name": "測試食物", "nutrition_info": {"calories": 100}}
+
+@app.post("/ai/analyze-food-image-with-weight/", response_model=WeightEstimationResponse)
+async def analyze_food_image_with_weight_endpoint(file: UploadFile = File(...)):
+    """測試重量估算端點"""
+    if not file.content_type or not file.content_type.startswith("image/"):
+        raise HTTPException(status_code=400, detail="上傳的檔案不是圖片格式。")
+    
+    return WeightEstimationResponse(
+        food_type="測試食物",
+        estimated_weight=150.0,
+        weight_confidence=0.85,
+        weight_error_range=[130.0, 170.0],
+        nutrition={"calories": 100, "protein": 5, "fat": 2, "carbs": 15},
+        reference_object="硬幣",
+        note="測試重量估算結果"
+    )
+
+@app.get("/ai/health")
+async def ai_health_check():
+    """AI 服務健康檢查"""
+    return {
+        "status": "healthy",
+        "services": {
+            "food_classification": "available",
+            "weight_estimation": "available"
+        }
+    }