Update app.py

app.py

@@ -8,15 +8,14 @@ import transformers
 import os
 
 # HF_TOKEN 설정
-os.environ["HF_TOKEN"] = "YOUR_TOKEN_HERE"
+if os.getenv("HF_TOKEN") is None:
+    raise ValueError("HF_TOKEN is not set")
 
 # xformers 라이브러리 설치
 try:
     import xformers
 except ImportError:
-    print("xformers 라이브러리를 설치합니다.")
-    os.system("pip install xformers")
-    import xformers
+    raise ImportError("xformers is not installed. Please install it using pip install xformers")
 
 transformers.utils.move_cache()  # 캐시 업데이트를 강제로 진행
 
@@ -25,14 +24,20 @@ torch_device = torch.device(device)
 
 if torch.cuda.is_available():
     torch.cuda.max_memory_allocated(device=device, max_memory_allocated=1024*1024*2)  # 2GB 메모리 할당량 설정
-    pipe = DiffusionPipeline.from_pretrained("stable-diffusion-3-medium", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+    try:
+        pipe = DiffusionPipeline.from_pretrained("stable-diffusion-3-medium", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+    except Exception as e:
+        raise ValueError("Failed to load DiffusionPipeline: {}".format(e))
     try:
         pipe.enable_xformers_memory_efficient_attention()
     except ImportError:
         print("xformers 라이브러리가 설치되지 않았습니다.")
     pipe = pipe.to(device)
 else: 
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
+    try:
+        pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
+    except Exception as e:
+        raise ValueError("Failed to load DiffusionPipeline: {}".format(e))
     pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -56,9 +61,10 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     
     return image
 
-client = InferenceClient("NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", token=os.getenv("HF_TOKEN"))
-if client is None:
-    print("HF_TOKEN이 설정되지 않았습니다.")
+try:
+    client = InferenceClient("NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", token=os.getenv("HF_TOKEN"))
+except Exception as e:
+    raise ValueError("Failed to create InferenceClient: {}".format(e))
 
 def respond(input):
     return client.chat_completion(