Update app.py

app.py

@@ -1,3 +1,13 @@
+#!/usr/bin/env python
+#patch 2.0 ()
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# ...
 import os
 import random
 import uuid
@@ -9,36 +19,43 @@ import spaces
 import torch
 from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
 
+#Load the HTML content
+#html_file_url = "https://prithivmlmods-hamster-static.static.hf.space/index.html"
+#html_content = f'<iframe src="{html_file_url}" style="width:100%; height:180px; border:none;"></iframe>'
+#html_file_url = "https://prithivmlmods-static-loading-theme.static.hf.space/index.html"
+
+#html_file_url = "https://prithivhamster.vercel.app/"
+#html_content = f'<iframe src="{html_file_url}" style="width:100%; height:400px; border:none"></iframe>'
+
+DESCRIPTIONx = """## STABLE HAMSTER 🐹
+
+"""
+
 css = '''
-.gradio-container{max-width: 888px !important}
+.gradio-container{max-width: 560px !important}
 h1{text-align:center}
 footer {
     visibility: hidden
 }
-.submit-btn {
-    background-color: #6263c7 !important;
-    color: white !important;
-}
-.submit-btn:hover {
-    background-color: #6063ff !important;
-}
 '''
 
 examples = [
-
-    "A tiny astronaut hatching from an egg on the moon, 4k, planet theme",
-    "An anime-style illustration of a delicious, golden-brown wiener schnitzel on a plate, served with fresh lemon slices, parsley --style raw5",
     "3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)",
     "Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K",
-    "Food photography of a milk shake with flying strawberrys against a pink background, professionally studio shot with cinematic lighting. The image is in the style of a professional studio shot --ar 85:128 --v 6.0 --style raw"
+    "Vector illustration of a horse, vector graphic design with flat colors on an brown background in the style of vector art, using simple shapes and graphics with simple details, professionally designed as a tshirt logo ready for print on a white background. --ar 89:82 --v 6.0 --style raw",
+    "Man in brown leather jacket posing for camera, in the style of sleek and stylized, clockpunk, subtle shades, exacting precision, ferrania p30  --ar 67:101 --v 5",
+    "Commercial photography, giant burger, white lighting, studio light, 8k octane rendering, high resolution photography, insanely detailed, fine details, on white isolated plain, 8k, commercial photography, stock photo, professional color grading, --v 4 --ar 9:16 "
+    
 ]
 
-MODEL_ID = os.getenv("MODEL_VAL_PATH") 
+
+MODEL_ID = os.getenv("MODEL_VAL_PATH") #Use SDXL Model as "MODEL_REPO" --------->>> ”VALUE”. 
 MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "4096"))
 USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
 ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
-BATCH_SIZE = int(os.getenv("BATCH_SIZE", "1")) 
+BATCH_SIZE = int(os.getenv("BATCH_SIZE", "1"))  # Allow generating multiple images at once
 
+#Load model outside of function
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 pipe = StableDiffusionXLPipeline.from_pretrained(
     MODEL_ID,
@@ -48,9 +65,11 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
 ).to(device)
 pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
 
+# <compile speedup >
 if USE_TORCH_COMPILE:
     pipe.compile()
 
+# Offloading capacity (RAM)
 if ENABLE_CPU_OFFLOAD:
     pipe.enable_model_cpu_offload()
 
@@ -84,6 +103,7 @@ def generate(
     seed = int(randomize_seed_fn(seed, randomize_seed))
     generator = torch.Generator(device=device).manual_seed(seed)
 
+    #Options 
     options = {
         "prompt": [prompt] * num_images,
         "negative_prompt": [negative_prompt] * num_images if use_negative_prompt else None,
@@ -98,6 +118,7 @@ def generate(
     if use_resolution_binning:
         options["use_resolution_binning"] = True
 
+    #Images potential batches
     images = []
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
@@ -110,8 +131,9 @@ def generate(
     return image_paths, seed
 
 with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
-    with gr.Row():
-        with gr.Column(scale=1):
+    gr.Markdown(DESCRIPTIONx)  
+    with gr.Group():
+        with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
                 show_label=False,
@@ -119,13 +141,9 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
                 placeholder="Enter your prompt",
                 container=False,
             )
-            run_button = gr.Button(
-                "Generate as ( 1024 x 1024 )🤗", 
-                scale=0, 
-                elem_classes="submit-btn"
-            )
-    
-    with gr.Accordion("Advanced options", open=True):
+            run_button = gr.Button("Run", scale=0)
+        result = gr.Gallery(label="Result", columns=1, show_label=False) 
+    with gr.Accordion("Advanced options", open=False, visible=False):
         num_images = gr.Slider(
             label="Number of Images",
             minimum=1,
@@ -172,7 +190,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
                 minimum=0.1,
                 maximum=6,
                 step=0.1,
-                value=2.0,
+                value=3.0,
             )
             num_inference_steps = gr.Slider(
                 label="Number of inference steps",
@@ -182,20 +200,19 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
                 value=23,
             )
 
-        with gr.Column(scale=2):
-            result = gr.Gallery(label="Result", columns=1, show_label=False)
-            
     gr.Examples(
         examples=examples,
         inputs=prompt,
         cache_examples=False
     )
+
     use_negative_prompt.change(
         fn=lambda x: gr.update(visible=x),
         inputs=use_negative_prompt,
         outputs=negative_prompt,
         api_name=False,
     )
+
     gr.on(
         triggers=[
             prompt.submit,
@@ -218,6 +235,6 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
         outputs=[result, seed],
         api_name="run",
     )   
-    
+
 if __name__ == "__main__":
     demo.queue(max_size=40).launch()