Update app.py

app.py

@@ -20,17 +20,6 @@ from fastapi import FastAPI
 
 app = FastAPI()
 
-# CSS to style the app
-css = """
-#generate {
-    width: 75%;
-}
-#image_output {
-height: 100% !important;
-}
-.gradio-container {background-color: MediumAquaMarine}
-footer{display:none !important}
-"""
 
 def query(prompt, negative_prompt, task, steps, sampler, cfg_scale, seed, width, height):
     result = {"prompt": prompt,"negative_prompt": negative_prompt,"task": task,"steps": steps,"sampler": sampler,"cfg_scale": cfg_scale,"seed": seed, "width": width, "height": height}
@@ -190,55 +179,54 @@ def mirror(image_output, scale_by, method, gfpgan, codeformer):
     img = Image.open(BytesIO(response2.content))
     return img
 
-examples = [
-    "a beautiful woman with blonde hair and blue eyes",
-    "a beautiful woman with brown hair and grey eyes",
-    "a beautiful woman with black hair and brown eyes",
-]    
-
-
+# CSS to style the app
+css = """
+.gradio-container {background-color: MediumAquaMarine}
+#app-container {
+    max-width: 930px;
+    margin-left: auto;
+    margin-right: auto;
+}
+footer {
+    visibility: hidden;
+}
+"""
 
 with gr.Blocks(css=css, theme=theme) as app:
     with gr.Tab("Basic Settings"):
-        with gr.Column(elem_id="col-container"):
-            with gr.Row():
-                prompt = gr.Textbox(placeholder="Enter the image description...", show_label=True, label='Image Prompt ✍️', lines=3, show_copy_button = True)
-            
-            with gr.Row():
-                gr.Examples(
-                examples = examples,    
-                inputs = [prompt], 
-            )
-            with gr.Row():
-                task = gr.Radio(interactive=True, value="Stable Diffusion XL 1.0", show_label=True, label="Model of neural network 🧠 ", choices=['Stable Diffusion XL 1.0', 'Crystal Clear XL', 
-                                                                                                                  'Juggernaut XL', 'DreamShaper XL',
-                                                                                                                  'SDXL Niji', 'Cinemax SDXL', 'NightVision XL'])
-        with gr.Tab("Extended settings"):
-            with gr.Row():
-                negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=True, label='Negative Prompt:', lines=3, value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry")
-            with gr.Row():
-                sampler = gr.Dropdown(value="DPM++ 2M Karras", show_label=True, label="Sampling Method:", choices=[
-                    "DPM++ 2M Karras", "DPM++ 2S a Karras", "DPM2 a Karras", "DPM2 Karras", "DPM++ SDE Karras", "DEIS", "LMS", "DPM Adaptive", "DPM++ 2M", "DPM2 Ancestral", "DPM++ S", "DPM++ SDE", "DDPM", "DPM Fast", "dpmpp_2s_ancestral", "Euler", "Euler CFG PP", "Euler a", "Euler Ancestral", "Euler+beta", "Heun", "Heun PP2", "DDIM", "LMS Karras", "PLMS", "UniPC", "UniPC BH2"])
-            with gr.Row():
-                steps = gr.Slider(show_label=True, label="Sampling Steps:", minimum=1, maximum=50, value=35, step=1)
-            with gr.Row():
-                cfg_scale = gr.Slider(show_label=True, label="CFG Scale:", minimum=1, maximum=20, value=7, step=1)
-            with gr.Row():
-                seed = gr.Number(show_label=True, label="Seed:", minimum=-1, maximum=1000000, value=-1, step=1)
-            with gr.Row():
-                width = gr.Slider(label="Width", minimum=512, maximum=2048, step=8, value=896, interactive=True,)
-            with gr.Row():
-                height = gr.Slider(label="Height", minimum=512, maximum=2048, step=8, value=1152,interactive=True,)
+        with gr.Row():
+            prompt = gr.Textbox(placeholder="Enter the image description...", show_label=True, label='Image Prompt ✍️', lines=3, show_copy_button = True)
+        with gr.Row():
+            task = gr.Radio(interactive=True, value="Stable Diffusion XL 1.0", show_label=True, label="Model of neural network 🧠 ", choices=['Stable Diffusion XL 1.0', 'Crystal Clear XL', 
+                                                                                                              'Juggernaut XL', 'DreamShaper XL',
+                                                                                                              'SDXL Niji', 'Cinemax SDXL', 'NightVision XL'])
+    with gr.Tab("Extended settings"):
+        with gr.Row():
+            negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=True, label='Negative Prompt:', lines=3, value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry")
+        
+        with gr.Row():
+            sampler = gr.Dropdown(value="DPM++ 2M Karras", show_label=True, label="Sampling Method:", choices=[
+                "DPM++ 2M Karras", "DPM++ 2S a Karras", "DPM2 a Karras", "DPM2 Karras", "DPM++ SDE Karras", "DEIS", "LMS", "DPM Adaptive", "DPM++ 2M", "DPM2 Ancestral", "DPM++ S", "DPM++ SDE", "DDPM", "DPM Fast", "dpmpp_2s_ancestral", "Euler", "Euler CFG PP", "Euler a", "Euler Ancestral", "Euler+beta", "Heun", "Heun PP2", "DDIM", "LMS Karras", "PLMS", "UniPC", "UniPC BH2"])
+        with gr.Row():
+            steps = gr.Slider(show_label=True, label="Sampling Steps:", minimum=1, maximum=50, value=35, step=1)
+        with gr.Row():
+            cfg_scale = gr.Slider(show_label=True, label="CFG Scale:", minimum=1, maximum=20, value=7, step=1)
+        with gr.Row():
+            seed = gr.Number(show_label=True, label="Seed:", minimum=-1, maximum=1000000, value=-1, step=1)
+        with gr.Row():
+            width = gr.Slider(label="Width", minimum=512, maximum=2048, step=8, value=896, interactive=True,)
+        with gr.Row():
+            height = gr.Slider(label="Height", minimum=512, maximum=2048, step=8, value=1152,interactive=True,)
+    
+    with gr.Column():
+        text_button = gr.Button("Generate image", variant="primary", interactive=True, elem_id="generate")
+    with gr.Column():
+        image_output = gr.Image(show_download_button=True, interactive=False, label='Generated Image 🌄', show_share_button=False, format="png", type="filepath", elem_id="gallery")
+        
+        text_button.click(query, inputs=[prompt, negative_prompt, task, steps, sampler, cfg_scale, seed, width, height], outputs=image_output, concurrency_limit=48)
+        clear_prompt =gr.Button("Clear 🗑️",variant="primary", elem_id="clear_button")
+        clear_prompt.click(lambda: (None, None), None, [prompt, image_output], queue=False, show_api=False)
         
-        with gr.Column():
-            text_button = gr.Button("Generate image", variant="primary", interactive=True, elem_id="generate")
-        with gr.Column():
-            image_output = gr.Image(show_download_button=True, interactive=False, label='Generated Image 🌄', show_share_button=False, format="png", type="filepath", elem_id="gallery")
-            
-            text_button.click(query, inputs=[prompt, negative_prompt, task, steps, sampler, cfg_scale, seed, width, height], outputs=image_output, concurrency_limit=48)
-            clear_prompt =gr.Button("Clear 🗑️",variant="primary", elem_id="clear_button")
-            clear_prompt.click(lambda: (None, None), None, [prompt, image_output], queue=False, show_api=False)
-            
 
 app.queue(default_concurrency_limit=200, max_size=200)  # <-- Sets up a queue with default parameters
 if __name__ == "__main__":