Update app.py

app.py

@@ -6,8 +6,6 @@ import torch
 import random
 from PIL import Image
 from typing import Iterable
-
-# --- Gradio Theme ---
 from gradio.themes import Soft
 from gradio.themes.utils import colors, fonts, sizes
 
@@ -67,7 +65,6 @@ class SteelBlueTheme(Soft):
 
 steel_blue_theme = SteelBlueTheme()
 
-# --- Model Loading ---
 from diffusers import FlowMatchEulerDiscreteScheduler
 # from optimization import optimize_pipeline_ # Assuming this is a custom file, if not available, comment out the call
 from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
@@ -88,7 +85,6 @@ pipe = QwenImageEditPlusPipeline.from_pretrained(
     torch_dtype=dtype
 ).to(device)
 
-# Load all LoRA adapters
 pipe.load_lora_weights("autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime",
                        weight_name="Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors",
                        adapter_name="anime")
@@ -105,7 +101,6 @@ pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight",
 pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
 MAX_SEED = np.iinfo(np.int32).max
 
-# --- Main Inference Function (Corrected) ---
 @spaces.GPU
 def infer(
     input_image,
@@ -120,7 +115,6 @@ def infer(
     if input_image is None:
         raise gr.Error("Please upload an image to edit.")
 
-    # Dynamically set the adapter
     if lora_adapter == "Photo-to-Anime":
         pipe.set_adapters(["anime"], adapter_weights=[1.0])
     elif lora_adapter == "Multiple-Angles":
@@ -136,7 +130,6 @@ def infer(
     generator = torch.Generator(device=device).manual_seed(seed)
     negative_prompt = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
 
-    # *** FIX: Get dimensions directly from the input image to preserve aspect ratio ***
     original_image = input_image.convert("RGB")
     width, height = original_image.size
 
@@ -153,18 +146,15 @@ def infer(
 
     return result, seed
 
-# --- Wrapper for Examples (Corrected) ---
 @spaces.GPU
 def infer_example(input_image, prompt, lora_adapter):
     input_pil = input_image.convert("RGB")
-    # Set reasonable default values for example inference
     guidance_scale = 1.0
     steps = 4
-    # Call the main infer function
     result, seed = infer(input_pil, prompt, lora_adapter, 0, True, guidance_scale, steps)
     return result, seed
 
-# --- UI Layout ---
+
 css="""
 #col-container {
     margin: 0 auto;
@@ -226,13 +216,10 @@ with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
             label="Examples"
         )
 
-    # --- Event Handlers (Corrected) ---
     run_button.click(
         fn=infer,
         inputs=[input_image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
         outputs=[output_image, seed]
     )
     
-    # No longer need the upload handler for dimensions
-
-demo.launch()
+demo.launch(mcp_server=True, ssr_mode=False, show_error=True)