Update app.py from anycoder

app.py

@@ -11,23 +11,18 @@ import gradio as gr
 import torch
 from diffusers.pipelines.glm_image import GlmImagePipeline
 from PIL import Image
-from gradio import spaces
+import spaces
 import time
 import random
 
-# Global pipeline variable
-pipe = None
-
-def load_model():
-    """Load the GLM-Image model with bfloat16 precision."""
-    global pipe
-    if pipe is None:
-        pipe = GlmImagePipeline.from_pretrained(
-            "zai-org/GLM-Image",
-            torch_dtype=torch.bfloat16,
-            device_map="auto"
-        )
-    return pipe
+# Load the GLM-Image model directly with bfloat16 precision
+print("Loading GLM-Image model... This may take a few minutes.")
+pipe = GlmImagePipeline.from_pretrained(
+    "zai-org/GLM-Image",
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+print("Model loaded successfully!")
 
 def calculate_duration(num_inference_steps: int) -> int:
     """
@@ -135,7 +130,6 @@ def process_image(
             height, width = adjusted_height, adjusted_width
         
         progress(0.1, desc="Loading model...")
-        pipeline = load_model()
         
         progress(0.2, desc="Preparing image...")
         input_image = image.convert("RGB")
@@ -143,7 +137,7 @@ def process_image(
         generator = torch.Generator(device="cuda").manual_seed(seed)
         
         progress(0.4, desc="Generating image...", visible=True)
-        result = pipeline(
+        result = pipe(
             prompt=prompt,
             image=[input_image],
             height=height,