app.py

import gradio as gr
import subprocess
import os

# Path to save the generated video
output_dir = './results'

# Ensure the output directory exists
os.makedirs(output_dir, exist_ok=True)

# Define the function to generate the video
def generate_video(prompt, video_size, video_length, infer_steps, seed, save_path):
    # Command to run the HunyuanVideo script
    command = [
        "python3", "sample_video.py",
        "--prompt", prompt,
        "--video-size", video_size,
        "--video-length", str(video_length),
        "--infer-steps", str(infer_steps),
        "--seed", str(seed),
        "--save-path", save_path
    ]
    
    # Run the video generation process
    try:
        subprocess.run(command, check=True)
        # Return the path to the generated video file
        generated_video_path = os.path.join(save_path, "generated_video.mp4")
        return generated_video_path
    except subprocess.CalledProcessError as e:
        return f"Error generating video: {e}"

# Create the Gradio interface
def create_interface():
    # Define input components
    prompt_input = gr.Textbox(label="Prompt", placeholder="Enter the prompt for the video.")
    video_size_input = gr.Textbox(label="Video Size", value="720 1280")
    video_length_input = gr.Slider(label="Video Length", minimum=1, maximum=200, value=129)
    infer_steps_input = gr.Slider(label="Inference Steps", minimum=1, maximum=100, value=30)
    seed_input = gr.Slider(label="Seed", minimum=0, maximum=1000, value=0)
    save_path_input = gr.Textbox(label="Save Path", value=output_dir)

    # Define output component
    output_video = gr.Video(label="Generated Video")

    # Create Gradio interface
    interface = gr.Interface(
        fn=generate_video,
        inputs=[prompt_input, video_size_input, video_length_input, infer_steps_input, seed_input, save_path_input],
        outputs=[output_video],
        live=True
    )
    
    # Launch the interface
    interface.launch()

if __name__ == "__main__":
    create_interface()