import gradio as gr
from gradio_client import Client, handle_file

def generate_video(input_image, prompt, negative_prompt, diffusion_step, height, width, scfg_scale, use_dctinit, dct_coefficients, noise_level, motion_bucket_id, seed):
    client = Client("maxin-cn/Cinemo")
    
    try:
        result = client.predict(
            input_image=handle_file(input_image),
            prompt=prompt,
            negative_prompt=negative_prompt,
            diffusion_step=diffusion_step,
            height=height,
            width=width,
            scfg_scale=scfg_scale,
            use_dctinit=use_dctinit,
            dct_coefficients=dct_coefficients,
            noise_level=noise_level,
            motion_bucket_id=motion_bucket_id,
            seed=seed,
            api_name="/gen_video"
        )

        print("API Response:", result)
        return result
    except Exception as e:
        return f"Error: {str(e)}"

# Define the Gradio interface
with gr.Blocks() as demo:
    with gr.Row():
        input_image = gr.Image(label="Input Image", type="filepath")
        with gr.Column():
            prompt = gr.Textbox(label="Prompt", placeholder="Enter prompt here...")
            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter negative prompt here...")

    diffusion_step = gr.Slider(minimum=1, maximum=100, value=50, label="Diffusion Steps")
    height = gr.Slider(minimum=128, maximum=1024, value=320, label="Height")
    width = gr.Slider(minimum=128, maximum=1024, value=512, label="Width")
    scfg_scale = gr.Slider(minimum=1.0, maximum=20.0, value=7.5, label="CFG Scale")
    use_dctinit = gr.Checkbox(value=True, label="Enable DCTInit")
    dct_coefficients = gr.Slider(minimum=0.0, maximum=1.0, value=0.23, label="DCT Coefficients")
    noise_level = gr.Slider(minimum=0, maximum=1000, value=985, label="Noise Level")
    motion_bucket_id = gr.Slider(minimum=1, maximum=100, value=10, label="Motion Intensity")
    seed = gr.Slider(minimum=1, maximum=10000, value=100, label="Seed")

    generate_btn = gr.Button("Generate Video")

    output_video = gr.Video(label="Generated Video")

    generate_btn.click(generate_video, inputs=[input_image, prompt, negative_prompt, diffusion_step, height, width, scfg_scale, use_dctinit, dct_coefficients, noise_level, motion_bucket_id, seed], outputs=output_video)

# Launch the app with verbose error reporting
demo.launch(show_error=True)