Update app.py from anycoder

app.py

@@ -1,41 +1,28 @@
 """
-GLM-Image to Image Editing App (ZeroGPU Version)
-A Gradio 6 application for image-to-image editing using the GLM-Image model with ZeroGPU support.
+GLM-Image to Image Editing App
+A Gradio 6 application for image-to-image editing using the GLM-Image model.
 
 This app allows users to upload an image and provide a prompt to transform
-the image using the GLM-Image diffusion model with dynamic GPU allocation.
+the image using the GLM-Image diffusion model.
 """
 
 import gradio as gr
 import torch
 from diffusers.pipelines.glm_image import GlmImagePipeline
 from PIL import Image
-import os
-from datetime import datetime
 
-# Import ZeroGPU
-import spaces
-
-# Initialize the model (lazy loading for better startup performance)
-pipe = None
-
-def load_model():
-    """Load the GLM-Image model with proper configuration."""
-    global pipe
-    if pipe is None:
-        pipe = GlmImagePipeline.from_pretrained(
-            "zai-org/GLM-Image",
-            torch_dtype=torch.bfloat16,
-            device_map="cuda"
-        )
-    return pipe
+# Initialize the model at startup
+pipe = GlmImagePipeline.from_pretrained(
+    "zai-org/GLM-Image",
+    torch_dtype=torch.bfloat16,
+    device_map="cuda"
+)
 
 def validate_dimensions(height: int, width: int) -> tuple:
     """
     Validate and adjust dimensions to be multiples of 32.
     GLM-Image requires height and width to be multiples of 32.
     """
-    # Adjust to nearest multiples of 32
     adjusted_height = (height // 32 + (1 if height % 32 != 0 else 0)) * 32
     adjusted_width = (width // 32 + (1 if width % 32 != 0 else 0)) * 32
     return adjusted_height, adjusted_width
@@ -44,34 +31,6 @@ def get_image_dimensions(image: Image.Image) -> tuple:
     """Get the dimensions of an uploaded PIL image."""
     return image.size[1], image.size[0]  # height, width
 
-def estimate_duration(num_inference_steps: int, height: int, width: int) -> int:
-    """
-    Estimate the duration needed for the GPU task based on complexity.
-    
-    Args:
-        num_inference_steps: Number of diffusion steps
-        height: Image height
-        width: Image width
-    
-    Returns:
-        Estimated duration in seconds
-    """
-    # Base time per step (adjust based on testing)
-    base_time_per_step = 3.5  # seconds
-    
-    # Complexity factor based on image size (larger images take more time)
-    size_factor = (height * width) / (1024 * 1024)  # relative to 1024x1024
-    
-    # Estimate total time
-    estimated_time = num_inference_steps * base_time_per_step * size_factor
-    
-    # Add buffer for image processing overhead
-    total_duration = int(estimated_time) + 30  # +30 seconds buffer
-    
-    # Ensure minimum duration and cap at reasonable max
-    return max(60, min(total_duration, 180))  # Between 60s and 180s
-
-@spaces.GPU(duration=estimate_duration)
 def process_image(
     image: Image.Image,
     prompt: str,
@@ -84,7 +43,6 @@ def process_image(
 ) -> tuple:
     """
     Process the image through the GLM-Image pipeline.
-    Decorated with @spaces.GPU for ZeroGPU dynamic allocation.
     
     Args:
         image: Input PIL Image
@@ -100,33 +58,24 @@ def process_image(
         Tuple of (output_image, status_message)
     """
     try:
-        # Validate inputs
         if image is None:
             raise ValueError("Please upload an image first.")
         
         if not prompt or not prompt.strip():
             raise ValueError("Please enter a prompt describing the image transformation.")
         
-        # Adjust dimensions to be multiples of 32
         adjusted_height, adjusted_width = validate_dimensions(height, width)
         
         if adjusted_height != height or adjusted_width != width:
             height, width = adjusted_height, adjusted_width
         
-        # Load model if not already loaded
-        progress(0.1, desc="Loading model...")
-        model = load_model()
-        
-        # Prepare image
-        progress(0.2, desc="Processing image...")
+        progress(0.1, desc="Processing image...")
         input_image = image.convert("RGB")
         
-        # Create generator with seed
         generator = torch.Generator(device="cuda").manual_seed(seed)
         
-        # Run the pipeline
         progress(0.3, desc="Generating image...")
-        result = model(
+        result = pipe(
             prompt=prompt,
             image=[input_image],
             height=height,
@@ -152,7 +101,6 @@ def update_dimensions_from_image(image: Image.Image) -> tuple:
     if image is None:
         return 1024, 1024
     h, w = get_image_dimensions(image)
-    # Adjust to nearest multiples of 32
     adjusted_h = (h // 32 + (1 if h % 32 != 0 else 0)) * 32
     adjusted_w = (w // 32 + (1 if w % 32 != 0 else 0)) * 32
     return adjusted_h, adjusted_w
@@ -162,7 +110,6 @@ def generate_random_seed() -> int:
     import random
     return random.randint(0, 2**32 - 1)
 
-# Custom theme with modern design
 custom_theme = gr.themes.Soft(
     primary_hue="indigo",
     secondary_hue="blue",
@@ -183,10 +130,8 @@ custom_theme = gr.themes.Soft(
     input_focus_border_color="*primary_400",
 )
 
-# Build the Gradio 6 application
 with gr.Blocks(fill_height=True) as demo:
     
-    # Header with branding
     gr.Markdown(
         """
         # 🎨 GLM-Image Editor
@@ -199,23 +144,10 @@ with gr.Blocks(fill_height=True) as demo:
         elem_classes=["header-markdown"]
     )
     
-    # GPU Status indicator
-    gr.Markdown(
-        """
-        <div class="gpu-status">
-        🚀 <strong>ZeroGPU Enabled</strong> - Dynamic GPU allocation for optimal performance
-        </div>
-        """,
-        elem_classes=["gpu-status-markdown"]
-    )
-    
-    # Main content in a row
     with gr.Row(equal_height=True):
-        # Left column - Input controls
         with gr.Column(scale=1, min_width=350):
             gr.Markdown("### 📤 Input")
             
-            # Image upload
             input_image = gr.Image(
                 label="Upload Image",
                 type="pil",
@@ -224,7 +156,6 @@ with gr.Blocks(fill_height=True) as demo:
                 height=300
             )
             
-            # Prompt input
             prompt = gr.Textbox(
                 label="Prompt",
                 placeholder="Describe how you want to transform the image...\n\nExample: Replace the background with an underground station featuring an automatic escalator.",
@@ -233,7 +164,6 @@ with gr.Blocks(fill_height=True) as demo:
                 info="Be specific about what you want to change"
             )
             
-            # Advanced settings accordion
             with gr.Accordion("⚙️ Advanced Settings", open=False):
                 with gr.Row():
                     height = gr.Number(
@@ -286,7 +216,6 @@ with gr.Blocks(fill_height=True) as demo:
                         variant="secondary"
                     )
             
-            # Action buttons
             with gr.Row():
                 generate_btn = gr.Button(
                     "✨ Generate Image",
@@ -295,18 +224,15 @@ with gr.Blocks(fill_height=True) as demo:
                     full_width=True
                 )
             
-            # Clear button
             clear_btn = gr.Button(
                 "🗑️ Clear All",
                 variant="stop",
                 size="sm"
             )
         
-        # Right column - Output
         with gr.Column(scale=1, min_width=350):
             gr.Markdown("### 📥 Output")
             
-            # Output image display
             output_image = gr.Image(
                 label="Generated Image",
                 type="pil",
@@ -315,15 +241,13 @@ with gr.Blocks(fill_height=True) as demo:
                 interactive=False
             )
             
-            # Status message
             status = gr.Textbox(
                 label="Status",
-                value="Ready to generate! GPU will be allocated automatically.",
+                value="Ready to generate!",
                 interactive=False,
                 show_label=True
             )
             
-            # Download button
             download_btn = gr.DownloadButton(
                 "💾 Download Image",
                 value=None,
@@ -331,7 +255,6 @@ with gr.Blocks(fill_height=True) as demo:
                 interactive=False
             )
             
-            # Tips section
             with gr.Accordion("💡 Tips for Better Results", open=False):
                 gr.Markdown(
                     """
@@ -348,7 +271,6 @@ with gr.Blocks(fill_height=True) as demo:
                     """
                 )
     
-    # Example prompts section
     with gr.Accordion("📝 Example Prompts", open=False):
         gr.Markdown(
             """
@@ -364,9 +286,6 @@ with gr.Blocks(fill_height=True) as demo:
             """
         )
     
-    # Event handlers
-    
-    # Update dimensions when image is uploaded
     input_image.change(
         fn=update_dimensions_from_image,
         inputs=input_image,
@@ -374,14 +293,12 @@ with gr.Blocks(fill_height=True) as demo:
         api_visibility="private"
     )
     
-    # Random seed generation
     random_seed_btn.click(
         fn=generate_random_seed,
         outputs=seed,
         api_visibility="private"
     )
     
-    # Generate button handler - uses ZeroGPU via @spaces.GPU decorator
     generate_btn.click(
         fn=process_image,
         inputs=[
@@ -397,7 +314,6 @@ with gr.Blocks(fill_height=True) as demo:
         progress=gr.Progress()
     )
     
-    # Update download button when output is generated
     def enable_download(img):
         if img is not None:
             return gr.DownloadButton(value=img, interactive=True)
@@ -410,13 +326,12 @@ with gr.Blocks(fill_height=True) as demo:
         api_visibility="private"
     )
     
-    # Clear button handler
     def clear_all():
         return {
             input_image: None,
             prompt: "",
             output_image: None,
-            status: "Ready to generate! GPU will be allocated automatically.",
+            status: "Ready to generate!",
             download_btn: gr.DownloadButton(interactive=False)
         }
     
@@ -432,7 +347,6 @@ with gr.Blocks(fill_height=True) as demo:
         api_visibility="private"
     )
 
-# Gradio 6 - ALL app parameters go in launch()!
 demo.launch(
     theme=custom_theme,
     css="""
@@ -455,17 +369,6 @@ demo.launch(
         color: #ffd700 !important;
         text-decoration: underline;
     }
-    .gpu-status-markdown {
-        background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%);
-        padding: 0.75rem;
-        border-radius: 0.5rem;
-        margin-bottom: 1rem;
-        text-align: center;
-        color: white;
-    }
-    .gpu-status-markdown strong {
-        color: #fff;
-    }
     #input-image, #output-image {
         border: 2px dashed var(--neutral-300);
         border-radius: var(--radius-lg);
@@ -477,7 +380,6 @@ demo.launch(
     footer_links=[
         {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"},
         {"label": "GLM-Image Model", "url": "https://huggingface.co/zai-org/GLM-Image"},
-        {"label": "ZeroGPU", "url": "https://huggingface.co/spaces/zero-gpu-explorers/README"},
         {"label": "Diffusers Library", "url": "https://github.com/huggingface/diffusers"}
     ],
     server_name="0.0.0.0",