Update main_app.py

main_app.py

@@ -37,19 +37,16 @@ style_list = [
         "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
         "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
     },
-
     {
         "name": "Photo",
         "prompt": "cinematic photo {prompt}. 35mm photograph, film, bokeh, professional, 4k, highly detailed",
         "negative_prompt": "drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly",
-    },   
-
+    },
     {
         "name": "Cinematic",
         "prompt": "cinematic still {prompt}. emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
         "negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
     },
-
     {
         "name": "Anime",
         "prompt": "anime artwork {prompt}. anime style, key visual, vibrant, studio anime, highly detailed",
@@ -77,25 +74,11 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
         negative = ""
     return p.replace("{prompt}", positive), n + negative
 
-DESCRIPTIONs = """
-# 🖼️ AI Image Generator
-
-Generate stunning images using various styles with advanced AI technology. Customize prompts, negative prompts, and other parameters to create your unique masterpiece.
-
-*Note: Running on CPU may take longer than on GPU.*
-"""
-
-DESCRIPTION = """
-### Powered by AI
-
-This application leverages cutting-edge AI models to produce high-quality images based on your prompts.
-
----
-
-"""
+DESCRIPTIONs = """ㅤㅤㅤ """
+DESCRIPTION = """ㅤㅤㅤ """
 
 if not torch.cuda.is_available():
-    DESCRIPTION += "<p style='color: red;'><strong>⚠️ Warning:</strong> Running on CPU, this may take longer to generate images.</p>"
+    DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
 
 MAX_SEED = np.iinfo(np.int32).max
 CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
@@ -126,30 +109,14 @@ if torch.cuda.is_available():
         pipe.enable_model_cpu_offload()
         pipe2.enable_model_cpu_offload()
     else:
-        pipe.to(device)    
-        pipe2.to(device)    
+        pipe.to(device)
+        pipe2.to(device)
         print("Loaded on Device!")
     
     if USE_TORCH_COMPILE:
         pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
         pipe2.unet = torch.compile(pipe2.unet, mode="reduce-overhead", fullgraph=True)
         print("Model Compiled!")
-else:
-    pipe = DiffusionPipeline.from_pretrained(
-        "SG161222/RealVisXL_V4.0",
-        torch_dtype=torch.float32,
-        use_safetensors=True,
-        add_watermarker=False
-    )
-    pipe2 = DiffusionPipeline.from_pretrained(
-        "SG161222/RealVisXL_V3.0",
-        torch_dtype=torch.float32,
-        use_safetensors=True,
-        add_watermarker=False
-    )
-    pipe.to(device)
-    pipe2.to(device)
-    print("Loaded on Device!")
 
 def save_image(img):
     unique_name = str(uuid.uuid4()) + ".png"
@@ -161,7 +128,7 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
         seed = random.randint(0, MAX_SEED)
     return seed
 
-@spaces.GPU(enable_queue=True)
+@spaces.GPU()
 def generate(
     prompt: str,
     negative_prompt: str = "",
@@ -184,7 +151,7 @@ def generate(
 
     if not use_negative_prompt:
         negative_prompt = ""  # type: ignore
-    negative_prompt += default_negative    
+    negative_prompt += default_negative
 
     options = {
         "prompt": prompt,
@@ -212,66 +179,78 @@ examples = [
 ]
 
 css = '''
-body {
-    background: #2e2e2e;
-    color: #f0f0f0;
-    font-family: 'Arial', sans-serif;
-}
-
 .gradio-container {
     max-width: 800px !important;
-    margin: 0 auto;
-    padding: 20px;
-    border: 2px solid #444;
-    border-radius: 10px;
-    box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
+    margin: auto;
 }
-
-.gradio-button {
-    background-color: #5a9;
+h1 {
+    text-align: center;
+    font-size: 2.5em;
+    color: #4CAF50;
+}
+#duplicate-button {
+    display: block;
+    margin: 10px auto;
+    padding: 10px 20px;
+    background-color: #4CAF50;
+    color: white;
     border: none;
+    border-radius: 5px;
+    cursor: pointer;
+}
+#duplicate-button:hover {
+    background-color: #45a049;
+}
+.gradio-button {
+    display: block;
+    margin: 20px auto;
     padding: 10px 20px;
-    font-size: 16px;
+    background-color: #2196F3;
     color: white;
+    border: none;
     border-radius: 5px;
     cursor: pointer;
-    margin-top: 10px;
 }
-
 .gradio-button:hover {
-    background-color: #48c;
+    background-color: #0b7dda;
 }
-
-h1, h2, h3, h4, h5, h6 {
-    color: #ddd;
+.gradio-gallery {
+    width: 100%;
+    display: flex;
+    flex-wrap: wrap;
+    gap: 10px;
 }
-
-.gradio-textbox {
-    background-color: #444;
-    color: #f0f0f0;
-    border: 1px solid #555;
+.gradio-gallery img {
+    width: calc(50% - 10px);
+    height: auto;
+    border-radius: 5px;
 }
-
-.gradio-slider {
-    background-color: #444;
-    color: #f0f0f0;
+.gradio-accordion, .gradio-slider, .gradio-radio {
+    margin-bottom: 20px;
 }
-
-.gradio-radio {
-    background-color: #444;
-    color: #f0f0f0;
+.gradio-checkbox {
+    margin-top: 10px;
+    margin-bottom: 10px;
 }
-
-.gradio-gallery {
-    background-color: #444;
-    color: #f0f0f0;
-    border: 1px solid #555;
+.gradio-slider label, .gradio-checkbox label, .gradio-radio label {
+    color: #3E4C59;
 }
-
-.gradio-accordion {
-    background-color: #444;
-    color: #f0f0f0;
-    border: 1px solid #555;
+.gradio-examples {
+    display: flex;
+    flex-wrap: wrap;
+    justify-content: space-between;
+}
+.gradio-examples > div {
+    flex: 1;
+    margin: 5px;
+    padding: 10px;
+    background-color: #f9f9f9;
+    border: 1px solid #ddd;
+    border-radius: 5px;
+    cursor: pointer;
+}
+.gradio-examples > div:hover {
+    background-color: #f1f1f1;
 }
 '''
 
@@ -286,10 +265,10 @@ with gr.Blocks(css=css, theme="default") as demo:
                 placeholder="Enter your prompt",
                 container=True
             )
-            run_button = gr.Button("Run", css=".gradio-button")
-        result = gr.Gallery(label="Result", columns=2, preview=True, css=".gradio-gallery { width: 100%; }")
-    with gr.Accordion("Advanced options", open=False, css=".gradio-accordion"):
-        use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True, css=".gradio-checkbox")
+            run_button = gr.Button("Run")
+        result = gr.Gallery(label="Result", columns=2, preview=True)
+    with gr.Accordion("Advanced options", open=False):
+        use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
         negative_prompt = gr.Textbox(
             label="Negative prompt",
             max_lines=1,
@@ -303,8 +282,7 @@ with gr.Blocks(css=css, theme="default") as demo:
                 minimum=10,
                 maximum=60,
                 step=1,
-                value=30,
-                css=".gradio-slider"
+                value=30
             )
         with gr.Row():
             num_images_per_prompt = gr.Slider(
@@ -312,8 +290,7 @@ with gr.Blocks(css=css, theme="default") as demo:
                 minimum=1,
                 maximum=5,
                 step=1,
-                value=2,
-                css=".gradio-slider"
+                value=2
             )
         seed = gr.Slider(
             label="Seed",
@@ -321,26 +298,23 @@ with gr.Blocks(css=css, theme="default") as demo:
             maximum=MAX_SEED,
             step=1,
             value=0,
-            visible=True,
-            css=".gradio-slider"
+            visible=True
         )
-        randomize_seed = gr.Checkbox(label="Randomize seed", value=True, css=".gradio-checkbox")
+        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
         with gr.Row(visible=True):
             width = gr.Slider(
                 label="Width",
                 minimum=512,
                 maximum=2048,
                 step=8,
-                value=1024,
-                css=".gradio-slider"
+                value=1024
             )
             height = gr.Slider(
                 label="Height",
                 minimum=512,
                 maximum=2048,
                 step=8,
-                value=1024,
-                css=".gradio-slider"
+                value=1024
             )
         with gr.Row():
             guidance_scale = gr.Slider(
@@ -348,8 +322,7 @@ with gr.Blocks(css=css, theme="default") as demo:
                 minimum=0.1,
                 maximum=20.0,
                 step=0.1,
-                value=6,
-                css=".gradio-slider"
+                value=6
             )
     with gr.Row(visible=True):
         style_selection = gr.Radio(
@@ -358,16 +331,14 @@ with gr.Blocks(css=css, theme="default") as demo:
             interactive=True,
             choices=STYLE_NAMES,
             value=DEFAULT_STYLE_NAME,
-            label="Image Style",
-            css=".gradio-radio"
+            label="Image Style"
         )
     gr.Examples(
         examples=examples,
         inputs=prompt,
         outputs=[result, seed],
         fn=generate,
-        cache_examples=CACHE_EXAMPLES,
-        css=".gradio-examples"
+        cache_examples=CACHE_EXAMPLES
     )
 
     use_negative_prompt.change(
@@ -399,6 +370,6 @@ with gr.Blocks(css=css, theme="default") as demo:
         api_name="run",
     )
     gr.Markdown(DESCRIPTION)
+
 if __name__ == "__main__":
     demo.queue(max_size=20).launch()
-