Update app.py

app.py

@@ -80,6 +80,15 @@ orange_red_theme = OrangeRedTheme()
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
+print("CUDA_VISIBLE_DEVICES=", os.environ.get("CUDA_VISIBLE_DEVICES"))
+print("torch.__version__ =", torch.__version__)
+print("torch.version.cuda =", torch.version.cuda)
+print("cuda available:", torch.cuda.is_available())
+print("cuda device count:", torch.cuda.device_count())
+if torch.cuda.is_available():
+    print("current device:", torch.cuda.current_device())
+    print("device name:", torch.cuda.get_device_name(torch.cuda.current_device()))
+
 print("Using device:", device)
 
 from diffusers import FlowMatchEulerDiscreteScheduler
@@ -100,29 +109,15 @@ pipe = QwenImageEditPlusPipeline.from_pretrained(
     torch_dtype=dtype
 ).to(device)
 
-try:
-    pipe.enable_vae_tiling()
-except Exception as e:
-    print(f"VAE Tiling warning: {e}")
-
-pipe.load_lora_weights("lightx2v/Qwen-Image-Lightning",
-                       weight_name="Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors",
-                       adapter_name="lightning")
-pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
-
 try:
     pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
+    print("Flash Attention 3 Processor set successfully.")
 except Exception as e:
-    print(f"FA3 Warning: {e}")
+    print(f"Warning: Could not set FA3 processor: {e}")
 
 MAX_SEED = np.iinfo(np.int32).max
 
 ADAPTER_SPECS = {
-    "Base Model": {
-        "repo": None,
-        "weights": None,
-        "adapter_name": "base"
-    },
     "Photo-to-Anime": {
         "repo": "autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime",
         "weights": "Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors",
@@ -169,15 +164,15 @@ def infer(
     if input_image is None:
         raise gr.Error("Please upload an image to edit.")
 
-    spec = ADAPTER_SPECS.get(lora_adapter)
-    if not spec:
-        raise gr.Error(f"Configuration not found for: {lora_adapter}")
-
-    adapter_name = spec["adapter_name"]
-
-    if adapter_name == "base":
+    if lora_adapter == "Base Model":
         pipe.set_adapters([], adapter_weights=[])
     else:
+        spec = ADAPTER_SPECS.get(lora_adapter)
+        if not spec:
+            raise gr.Error(f"Configuration not found for: {lora_adapter}")
+
+        adapter_name = spec["adapter_name"]
+
         if adapter_name not in LOADED_ADAPTERS:
             print(f"--- Downloading and Loading Adapter: {lora_adapter} ---")
             try:
@@ -189,7 +184,9 @@ def infer(
                 LOADED_ADAPTERS.add(adapter_name)
             except Exception as e:
                 raise gr.Error(f"Failed to load adapter {lora_adapter}: {e}")
-        
+        else:
+            print(f"--- Adapter {lora_adapter} is already loaded. ---")
+
         pipe.set_adapters([adapter_name], adapter_weights=[1.0])
 
     if randomize_seed:
@@ -242,8 +239,8 @@ css="""
 
 with gr.Blocks() as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown("# **Qwen-Image-Edit-2511-LoRAs-Fast**", elem_id="main-title")
-        gr.Markdown("Perform diverse image edits using specialized [LoRA](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2509) adapters for the [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) model.")
+        gr.Markdown("# **Qwen-Image-Edit-2511-LoRA**", elem_id="main-title")
+        gr.Markdown("Perform diverse image edits using the **Qwen-Image-Edit-2511** model with optional LoRA adapters.")
 
         with gr.Row(equal_height=True):
             with gr.Column():
@@ -252,7 +249,7 @@ with gr.Blocks() as demo:
                 prompt = gr.Text(
                     label="Edit Prompt",
                     show_label=True,
-                    placeholder="e.g., transform into anime..",
+                    placeholder="e.g., make it look cinematic...",
                 )
 
                 run_button = gr.Button("Edit Image", variant="primary")
@@ -263,7 +260,7 @@ with gr.Blocks() as demo:
                 with gr.Row():
                     lora_adapter = gr.Dropdown(
                         label="Choose Editing Style",
-                        choices=list(ADAPTER_SPECS.keys()),
+                        choices=["Base Model", "Photo-to-Anime"],
                         value="Base Model"
                     )
                 with gr.Accordion("Advanced Settings", open=False, visible=False):
@@ -274,8 +271,8 @@ with gr.Blocks() as demo:
         
         gr.Examples(
             examples=[
-                ["examples/1.jpg", "Make it snowy.", "Base Model"],
-                ["examples/1.jpg", "Transform into anime.", "Photo-to-Anime"],
+                ["examples/1.jpg", "A cinematic shot of a cyberpunk city.", "Base Model"],
+                ["examples/2.jpg", "Transform into anime style.", "Photo-to-Anime"],
             ],
             inputs=[input_image, prompt, lora_adapter],
             outputs=[output_image, seed],