Update gradio_app.py

gradio_app.py

@@ -13,17 +13,21 @@ from huggingface_hub import snapshot_download
 weights_dir = './allegro_weights'
 os.makedirs(weights_dir, exist_ok=True)
 
-snapshot_download(
-    repo_id='rhymes-ai/Allegro',
-    allow_patterns=[
-        'scheduler/**',
-        'text_encoder/**',
-        'tokenizer/**',
-        'transformer/**',
-        'vae/**',
-    ],
-    local_dir=weights_dir,
-)
+is_shared_ui = True if "fffiloni/allegro-t2v" in os.environ['SPACE_ID'] else False
+is_gpu_associated = torch.cuda.is_available()
+
+if not is_shared_ui:
+    snapshot_download(
+        repo_id='rhymes-ai/Allegro',
+        allow_patterns=[
+            'scheduler/**',
+            'text_encoder/**',
+            'tokenizer/**',
+            'transformer/**',
+            'vae/**',
+        ],
+        local_dir=weights_dir,
+    )
 
 
 def single_inference(user_prompt, save_path, guidance_scale, num_sampling_steps, seed, enable_cpu_offload):
@@ -97,21 +101,113 @@ def run_inference(user_prompt, guidance_scale, num_sampling_steps, seed, enable_
     result_path = single_inference(user_prompt, save_path, guidance_scale, num_sampling_steps, seed, enable_cpu_offload)
     return result_path
 
+css="""
+#upl-dataset-group {background-color: none!important;}
+div#warning-ready {
+    background-color: #ecfdf5;
+    padding: 0 16px 16px;
+    margin: 20px 0;
+}
+div#warning-ready > .gr-prose > h2, div#warning-ready > .gr-prose > p {
+    color: #057857!important;
+}
+div#warning-duplicate {
+    background-color: #ebf5ff;
+    padding: 0 16px 16px;
+    margin: 20px 0;
+}
+div#warning-duplicate > .gr-prose > h2, div#warning-duplicate > .gr-prose > p {
+    color: #0f4592!important;
+}
+div#warning-duplicate strong {
+    color: #0f4592;
+}
+p.actions {
+    display: flex;
+    align-items: center;
+    margin: 20px 0;
+}
+div#warning-duplicate .actions a {
+    display: inline-block;
+    margin-right: 10px;
+}
+div#warning-setgpu {
+    background-color: #fff4eb;
+    padding: 0 16px 16px;
+    margin: 20px 0;
+}
+div#warning-setgpu > .gr-prose > h2, div#warning-setgpu > .gr-prose > p {
+    color: #92220f!important;
+}
+div#warning-setgpu a, div#warning-setgpu b {
+    color: #91230f;
+}
+div#warning-setgpu p.actions > a {
+    display: inline-block;
+    background: #1f1f23;
+    border-radius: 40px;
+    padding: 6px 24px;
+    color: antiquewhite;
+    text-decoration: none;
+    font-weight: 600;
+    font-size: 1.2em;
+}
+"""
 
 # Create Gradio interface
-iface = gr.Interface(
+with gr.Blocks(css=css) as demo:
+    with gr.Column():
+        gr.Markdown("# Allegro Video Generation")
+        gr.Markdown("Generate a video based on a text prompt using the Allegro pipeline.")
+        with gr.Row():
+            with gr.Column():
+                user_prompt=gr.Textbox(label="User Prompt")
+                with gr.Row():
+                    guidance_scale=gr.Slider(minimum=0, maximum=20, step=0.1, label="Guidance Scale", value=7.5)
+                    num_sampling_steps=gr.Slider(minimum=10, maximum=100, step=1, label="Number of Sampling Steps", value=20)
+                with gr.Row():
+                    seed=gr.Slider(minimum=0, maximum=10000, step=1, label="Random Seed", value=42)
+                    enable_cpu_offload=gr.Checkbox(label="Enable CPU Offload", value=False, scale=1)
+                if is_shared_ui:
+                    top_description = gr.HTML(f'''
+                        <div class="gr-prose">
+                            <h2><svg xmlns="http://www.w3.org/2000/svg" width="18px" height="18px" style="margin-right: 0px;display: inline-block;"fill="none"><path fill="#fff" d="M7 13.2a6.3 6.3 0 0 0 4.4-10.7A6.3 6.3 0 0 0 .6 6.9 6.3 6.3 0 0 0 7 13.2Z"/><path fill="#fff" fill-rule="evenodd" d="M7 0a6.9 6.9 0 0 1 4.8 11.8A6.9 6.9 0 0 1 0 7 6.9 6.9 0 0 1 7 0Zm0 0v.7V0ZM0 7h.6H0Zm7 6.8v-.6.6ZM13.7 7h-.6.6ZM9.1 1.7c-.7-.3-1.4-.4-2.2-.4a5.6 5.6 0 0 0-4 1.6 5.6 5.6 0 0 0-1.6 4 5.6 5.6 0 0 0 1.6 4 5.6 5.6 0 0 0 4 1.7 5.6 5.6 0 0 0 4-1.7 5.6 5.6 0 0 0 1.7-4 5.6 5.6 0 0 0-1.7-4c-.5-.5-1.1-.9-1.8-1.2Z" clip-rule="evenodd"/><path fill="#000" fill-rule="evenodd" d="M7 2.9a.8.8 0 1 1 0 1.5A.8.8 0 0 1 7 3ZM5.8 5.7c0-.4.3-.6.6-.6h.7c.3 0 .6.2.6.6v3.7h.5a.6.6 0 0 1 0 1.3H6a.6.6 0 0 1 0-1.3h.4v-3a.6.6 0 0 1-.6-.7Z" clip-rule="evenodd"/></svg>
+                            Attention: this Space need to be duplicated to work</h2>
+                            <p class="main-message">
+                                To make it work, <strong>duplicate the Space</strong> and run it on your own profile using a <strong>private</strong> GPU.<br />
+                                You'll be able to offload the model into CPU for less GPU memory cost (about 9.3G, compared to 27.5G if CPU offload is not enabled), but the inference time will increase significantly.
+                            </p>
+                            <p class="actions">
+                                <a href="https://huggingface.co/spaces/{os.environ['SPACE_ID']}?duplicate=true">
+                                    <img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-lg-dark.svg" alt="Duplicate this Space" />
+                                </a>
+                            </p>
+                        </div>
+                    ''', elem_id="warning-duplicate")
+                else:
+                    if(is_gpu_associated):
+                        submit_btn = gr.Button("Generate Video", visible=False)
+                    else:
+                        top_description = gr.HTML(f'''
+                                <div class="gr-prose">
+                                <h2><svg xmlns="http://www.w3.org/2000/svg" width="18px" height="18px" style="margin-right: 0px;display: inline-block;"fill="none"><path fill="#fff" d="M7 13.2a6.3 6.3 0 0 0 4.4-10.7A6.3 6.3 0 0 0 .6 6.9 6.3 6.3 0 0 0 7 13.2Z"/><path fill="#fff" fill-rule="evenodd" d="M7 0a6.9 6.9 0 0 1 4.8 11.8A6.9 6.9 0 0 1 0 7 6.9 6.9 0 0 1 7 0Zm0 0v.7V0ZM0 7h.6H0Zm7 6.8v-.6.6ZM13.7 7h-.6.6ZM9.1 1.7c-.7-.3-1.4-.4-2.2-.4a5.6 5.6 0 0 0-4 1.6 5.6 5.6 0 0 0-1.6 4 5.6 5.6 0 0 0 1.6 4 5.6 5.6 0 0 0 4 1.7 5.6 5.6 0 0 0 4-1.7 5.6 5.6 0 0 0 1.7-4 5.6 5.6 0 0 0-1.7-4c-.5-.5-1.1-.9-1.8-1.2Z" clip-rule="evenodd"/><path fill="#000" fill-rule="evenodd" d="M7 2.9a.8.8 0 1 1 0 1.5A.8.8 0 0 1 7 3ZM5.8 5.7c0-.4.3-.6.6-.6h.7c.3 0 .6.2.6.6v3.7h.5a.6.6 0 0 1 0 1.3H6a.6.6 0 0 1 0-1.3h.4v-3a.6.6 0 0 1-.6-.7Z" clip-rule="evenodd"/></svg>
+                                You have successfully duplicated the Allegro Video Generation Space 🎉</h2>
+                                <p>There's only one step left before you can generate a video: <a href="https://huggingface.co/spaces/{os.environ['SPACE_ID']}/settings" style="text-decoration: underline" target="_blank">attribute a GPU</b> to it (via the Settings tab)</a>.
+                                You will be billed by the minute from when you activate the GPU until when it is turned off.</p> 
+                                <p class="actions">
+                                    <a href="https://huggingface.co/spaces/{os.environ['SPACE_ID']}/settings">🔥 &nbsp; Set recommended GPU</a>
+                                </p>
+                                </div>
+                        ''', elem_id="warning-setgpu")
+                    
+            with gr.Column():
+                video_output=gr.Video(label="Generated Video")
+
+submit_btn.click(
     fn=run_inference,
-    inputs=[
-        gr.Textbox(label="User Prompt"),
-        gr.Slider(minimum=0, maximum=20, step=0.1, label="Guidance Scale", value=7.5),
-        gr.Slider(minimum=10, maximum=200, step=1, label="Number of Sampling Steps", value=100),
-        gr.Slider(minimum=0, maximum=10000, step=1, label="Random Seed", value=42),
-        gr.Checkbox(label="Enable CPU Offload", value=False),
-    ],
-    outputs=gr.Video(label="Generated Video"),
-    title="Allegro Video Generation",
-    description="Generate a video based on a text prompt using the Allegro pipeline."
+    inputs=[user_prompt, guidance_scale, num_sampling_steps, seed, enable_cpu_offload],
+    outputs=video_output
 )
 
 # Launch the interface
-iface.launch()
+demo.launch(show_error=True, show_api=False)