Enhanced Gradio UI

demos/cli.py

@@ -25,12 +25,20 @@
 cpu_offload = False
 
 
-def configure_model(model_dir_path_, lora_path_, cpu_offload_):
+def configure_model(model_dir_path_, lora_path_, cpu_offload_, gpu=None):
     global model_dir_path, lora_path, cpu_offload
     model_dir_path = model_dir_path_
     lora_path = lora_path_
     cpu_offload = cpu_offload_
 
+    # Set the GPU device if specified
+    if gpu:
+        os.environ["CUDA_VISIBLE_DEVICES"] = gpu
+        print(f"Using GPU: {gpu}")
+    else:
+        print("Using default GPU configuration.")
+
+
 
 def load_model():
     global num_gpus, pipeline, model_dir_path, lora_path

demos/comfyui_nodes.py

@@ -0,0 +1 @@
+

demos/gradio_ui.py

@@ -1,32 +1,45 @@
 #! /usr/bin/env python
 
-
 import sys
-
 import click
 import gradio as gr
 
 sys.path.append("..")
 from cli import configure_model, generate_video
 
-with gr.Blocks() as demo:
-    gr.Markdown("Video Generator")
+# Enhanced Gradio App
+with gr.Blocks(css=".gradio-container {font-family: 'Arial', sans-serif; background-color: #f9f9f9;}") as demo:
+    gr.Markdown(
+        """
+        <h1 style="text-align: center; color: #4CAF50;">🎥 Mochi Video Generator</h1>
+        <p style="text-align: center;">Generate stunning videos with ease!</p>
+        """,
+        elem_id="header",
+    )
     with gr.Row():
         prompt = gr.Textbox(
             label="Prompt",
             value="A hand with delicate fingers picks up a bright yellow lemon from a wooden bowl filled with lemons and sprigs of mint against a peach-colored background. The hand gently tosses the lemon up and catches it, showcasing its smooth texture. A beige string bag sits beside the bowl, adding a rustic touch to the scene. Additional lemons, one halved, are scattered around the base of the bowl. The even lighting enhances the vibrant colors and creates a fresh, inviting atmosphere.",
+            lines=3,
+            placeholder="Enter your prompt here...",
         )
-        negative_prompt = gr.Textbox(label="Negative Prompt", value="")
+        negative_prompt = gr.Textbox(
+            label="Negative Prompt",
+            value="",
+            lines=2,
+            placeholder="Enter negative prompt here...",
+        )
+    with gr.Row():
         seed = gr.Number(label="Seed", value=1710977262, precision=0)
+        cfg_scale = gr.Number(label="CFG Scale", value=4.5)
     with gr.Row():
         width = gr.Number(label="Width", value=848, precision=0)
         height = gr.Number(label="Height", value=480, precision=0)
-        num_frames = gr.Number(label="Number of Frames", value=163, precision=0)
     with gr.Row():
-        cfg_scale = gr.Number(label="CFG Scale", value=4.5)
+        num_frames = gr.Number(label="Number of Frames", value=163, precision=0)
         num_inference_steps = gr.Number(label="Number of Inference Steps", value=200, precision=0)
-    btn = gr.Button("Generate Video")
-    output = gr.Video()
+    btn = gr.Button("🎬 Generate Video", elem_id="generate-btn")
+    output = gr.Video(label="Generated Video")
 
     btn.click(
         generate_video,
@@ -43,13 +56,20 @@
         outputs=output,
     )
 
-
+# Command-line interface with GPU, host, and port options
 @click.command()
 @click.option("--model_dir", required=True, help="Path to the model directory.")
-@click.option("--cpu_offload", is_flag=True, help="Whether to offload model to CPU")
-def launch(model_dir, cpu_offload):
-    configure_model(model_dir, cpu_offload)
-    demo.launch()
+@click.option("--lora_path", required=False, help="Path to the lora file.")
+@click.option("--cpu_offload", is_flag=True, help="Whether to offload model to CPU.")
+@click.option("--gpu", default=None, help="Specify the GPU to use (e.g., 'cuda:0').")
+@click.option("--host", default="127.0.0.1", help="Host address for the Gradio app.")
+@click.option("--port", default=7860, help="Port number for the Gradio app.")
+def launch(model_dir, lora_path, cpu_offload, gpu, host, port):
+    # Configure the model
+    configure_model(model_dir, lora_path, cpu_offload, gpu=gpu)
+
+    # Launch the Gradio app
+    demo.launch(server_name=host, server_port=port)
 
 
 if __name__ == "__main__":