upload

app.py

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+import gradio as gr
+from datasets import load_dataset
+from PIL import Image  
+import re
+import os
+import requests
+
+model_id = "runwayml/stable-diffusion-v1-5"
+device = "cuda"
+
+word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
+word_list = word_list_dataset["train"]['text']
+
+is_gpu_busy = False
+def infer(prompt):
+    global is_gpu_busy
+    samples = 4
+    steps = 50
+    scale = 7.5
+    for filter in word_list:
+        if re.search(rf"\b{filter}\b", prompt):
+            raise gr.Error("Unsafe content found. Please try again with different prompts.")
+        
+    images = []
+    url = os.getenv('JAX_BACKEND_URL')
+    payload = {'prompt': prompt}
+    images_request = requests.post(url, json = payload)
+    for image in images_request.json()["images"]:
+        image_b64 = (f"data:image/jpeg;base64,{image}")
+        images.append(image_b64)
+    
+    return images
+    
+    
+css = """
+        .gradio-container {
+            font-family: 'IBM Plex Sans', sans-serif;
+        }
+        .gr-button {
+            color: white;
+            border-color: black;
+            background: black;
+        }
+        input[type='range'] {
+            accent-color: black;
+        }
+        .dark input[type='range'] {
+            accent-color: #dfdfdf;
+        }
+        .container {
+            max-width: 730px;
+            margin: auto;
+            padding-top: 1.5rem;
+        }
+        #gallery {
+            min-height: 22rem;
+            margin-bottom: 15px;
+            margin-left: auto;
+            margin-right: auto;
+            border-bottom-right-radius: .5rem !important;
+            border-bottom-left-radius: .5rem !important;
+        }
+        #gallery>div>.h-full {
+            min-height: 20rem;
+        }
+        .details:hover {
+            text-decoration: underline;
+        }
+        .gr-button {
+            white-space: nowrap;
+        }
+        .gr-button:focus {
+            border-color: rgb(147 197 253 / var(--tw-border-opacity));
+            outline: none;
+            box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
+            --tw-border-opacity: 1;
+            --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
+            --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
+            --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
+            --tw-ring-opacity: .5;
+        }
+        #advanced-btn {
+            font-size: .7rem !important;
+            line-height: 19px;
+            margin-top: 12px;
+            margin-bottom: 12px;
+            padding: 2px 8px;
+            border-radius: 14px !important;
+        }
+        #advanced-options {
+            display: none;
+            margin-bottom: 20px;
+        }
+        .footer {
+            margin-bottom: 45px;
+            margin-top: 35px;
+            text-align: center;
+            border-bottom: 1px solid #e5e5e5;
+        }
+        .footer>p {
+            font-size: .8rem;
+            display: inline-block;
+            padding: 0 10px;
+            transform: translateY(10px);
+            background: white;
+        }
+        .dark .footer {
+            border-color: #303030;
+        }
+        .dark .footer>p {
+            background: #0b0f19;
+        }
+        .acknowledgments h4{
+            margin: 1.25em 0 .25em 0;
+            font-weight: bold;
+            font-size: 115%;
+        }
+        #container-advanced-btns{
+            display: flex;
+            flex-wrap: wrap;
+            justify-content: space-between;
+            align-items: center;
+        }
+        .animate-spin {
+            animation: spin 1s linear infinite;
+        }
+        @keyframes spin {
+            from {
+                transform: rotate(0deg);
+            }
+            to {
+                transform: rotate(360deg);
+            }
+        }
+        #share-btn-container {
+            display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
+        }
+        #share-btn {
+            all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;
+        }
+        #share-btn * {
+            all: unset;
+        }
+        .gr-form{
+            flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;
+        }
+        #prompt-container{
+            gap: 0;
+        }
+        #share-btn-container div:nth-child(-n+2){
+        width: auto !important;
+        min-height: 0px !important;
+        } 
+"""
+
+block = gr.Blocks(css=css)
+
+examples = [
+    [
+        'The spirit of a tamagotchi wandering in the city of Paris',
+#        4,
+#        45,
+#        7.5,
+#        1024,
+    ],
+    [
+        'A delicious ceviche cheesecake slice',
+#        4,
+#        45,
+#        7,
+#        1024,
+    ],
+    [
+        'A pao de queijo foodcart in front of a japanese castle',
+#        4,
+#        45,
+#        7,
+#        1024,
+    ],
+    [
+        'alone in the amusement park by Edward Hopper',
+#        4,
+#        45,
+#        7,
+#        1024,
+    ],
+    [
+        "A large cabin on top of a sunny mountain in the style of Dreamworks, artstation",
+#        4,
+#        45,
+#        7,
+#        1024,
+    ],
+]
+
+
+with block:
+    gr.HTML(
+        """
+            <div style="text-align: center; max-width: 650px; margin: 0 auto; padding-top: 7px;">
+              <div
+                style="
+                  display: inline-flex;
+                  align-items: center;
+                  gap: 0.8rem;
+                  font-size: 1.75rem;
+                "
+              >
+                <h1 style="font-weight: 900; margin-bottom: 7px;">
+                  Image Generation
+                </h1>
+              </div>
+            </div>
+        """
+    )
+    with gr.Group():
+        with gr.Box():
+            with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
+                text = gr.Textbox(
+                    label="Enter your prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    elem_id="prompt-text-input",
+                ).style(
+                    border=(True, False, True, True),
+                    rounded=(True, False, False, True),
+                    container=False,
+                )
+                btn = gr.Button("Generate image").style(
+                    margin=False,
+                    rounded=(False, True, True, False),
+                    full_width=False,
+                )
+
+        gallery = gr.Gallery(
+            label="Generated images", show_label=False, elem_id="gallery"
+        ).style(grid=[2], height="auto")
+
+
+        with gr.Row(elem_id="advanced-options"):
+            gr.Markdown("Advanced settings are temporarily unavailable")
+            samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1)
+            steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1)
+            scale = gr.Slider(
+                label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
+            )
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=2147483647,
+                step=1,
+                randomize=True,
+            )
+
+        ex = gr.Examples(examples=examples, fn=infer, inputs=text, outputs=[gallery], cache_examples=True, postprocess=False)
+        ex.dataset.headers = [""]
+
+        text.submit(infer, inputs=text, outputs=[gallery], postprocess=False)
+        btn.click(infer, inputs=text, outputs=[gallery], postprocess=False)
+
+block.queue(concurrency_count=40, max_size=20).launch(max_threads=150)

requirements.txt

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+python-dotenv