Update app.py

app.py

@@ -94,20 +94,39 @@ except Exception as e:
 # LoRA 가중치 로드 부분 수정
 print("Loading LoRA weights...")
 try:
-    # 로컬 LoRA 파일 경로 지정
-    lora_path = "myt-flux-fantasy.safetensors"  # 현재 디렉토리의 파일 직접 사용
+    # 로컬 LoRA 파일의 절대 경로 확인
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    lora_path = os.path.join(current_dir, "myt-flux-fantasy.safetensors")
+    
+    if not os.path.exists(lora_path):
+        raise FileNotFoundError(f"LoRA file not found at: {lora_path}")
+    
+    print(f"Loading LoRA weights from: {lora_path}")
+    
+    # LoRA 가중치 로드 방식 수정
+    pipe.load_lora_weights(
+        lora_path,
+        adapter_name="fantasy"
+    )
+    
+    # LoRA 가중치 활성화
+    pipe.set_adapters(["fantasy"])
+    pipe.fuse_lora(lora_scale=0.75)  # lora_scale 값 조정
+    
+    # 메모리 정리
+    torch.cuda.empty_cache()
+    gc.collect()
     
-    print(f"Loading LoRA weights from local file: {lora_path}")
-    pipe.load_lora_weights(lora_path)
-    pipe.fuse_lora(lora_scale=0.125)
     print("LoRA weights loaded and fused successfully")
+    print(f"Current device: {pipe.device}")
+    print(f"Active adapters: {pipe.active_adapters}")
 
 except Exception as e:
     print(f"Error loading LoRA weights: {str(e)}")
-    raise ValueError(f"Failed to load LoRA weights from {lora_path}: {str(e)}")
+    print(f"Full error details: {repr(e)}")
+    raise ValueError(f"Failed to load LoRA weights: {str(e)}")
     
 
-# generate_image 함수 수정
 @spaces.GPU(duration=60)
 def generate_image(
     prompt: str,
@@ -124,12 +143,17 @@ def generate_image(
         
         translated_prompt = translate_to_english(prompt)
         print(f"Processing prompt: {translated_prompt}")
+        print(f"Active adapters before generation: {pipe.active_adapters}")
         
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
         
         generator = torch.Generator(device=device).manual_seed(seed)
         
+        # LoRA 설정 확인
+        print(f"LoRA scale: {pipe.lora_scale}")
+        print(f"Current device: {pipe.device}")
+        
         with torch.inference_mode(), torch.cuda.amp.autocast(enabled=True):
             image = pipe(
                 prompt=translated_prompt,
@@ -142,17 +166,16 @@ def generate_image(
             ).images[0]
         
         filepath = save_generated_image(image, translated_prompt)
+        print(f"Image generated and saved to: {filepath}")
         return image, seed
         
     except Exception as e:
         print(f"Generation error: {str(e)}")
+        print(f"Full error details: {repr(e)}")
         raise gr.Error(f"Image generation failed: {str(e)}")
     finally:
         clear_memory()
 
-
-
-
 # 저장 디렉토리 설정
 SAVE_DIR = "saved_images"
 if not os.path.exists(SAVE_DIR):