Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py (English LTR Version)
+# app.py (النسخة النهائية - بالثيم الذهبي)
 
 import gradio as gr
 import numpy as np
@@ -11,10 +11,12 @@ import time
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 DTYPE = torch.float16 if torch.cuda.is_available() else torch.float32
 
-MODEL_ID = "YourUsername/Takween-v1"  # IMPORTANT: Replace with your model's name on Hugging Face
+# IMPORTANT: Replace "YourUsername/Takween-v1" with your model's name on Hugging Face
+MODEL_ID = "YourUsername/Takween-v1" 
 BASE_MODEL_ID = "runwayml/stable-diffusion-v1-5"
 MAX_SEED = np.iinfo(np.int32).max
 
+# Project Logo (Embedded SVG)
 LOGO_SVG = """
 <svg xmlns="http://www.w3.org/2000/svg" width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
   <path d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2z"></path>
@@ -33,9 +35,9 @@ except Exception:
 
 pipe = pipe.to(DEVICE)
 
-# --- 3. Professional Theme ---
+# --- 3. Professional Theme (Golden Version) ---
 theme = gr.themes.Base(
-    primary_hue=gr.themes.colors.purple,
+    primary_hue=gr.themes.colors.amber,  # Golden Theme Primary Color
     secondary_hue=gr.themes.colors.neutral,
     font=[gr.themes.GoogleFont("IBM Plex Sans"), "system-ui", "sans-serif"],
 ).set(
@@ -54,11 +56,13 @@ def infer(prompt, negative_prompt, guidance_scale, num_inference_steps, seed, ra
     
     generator = torch.Generator(device=DEVICE).manual_seed(seed)
     
+    # Update UI to show loading state
     yield {
         output_image: gr.update(value=None, interactive=False, visible=True),
         run_button: gr.update(interactive=False, value="Generating..."),
     }
     
+    # Generate the image
     image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -67,6 +71,7 @@ def infer(prompt, negative_prompt, guidance_scale, num_inference_steps, seed, ra
         generator=generator,
     ).images[0]
     
+    # Update UI with the final result
     yield {
         output_image: gr.update(value=image, interactive=True),
         output_seed: gr.update(value=seed),