app.py

from diffusers import DiffusionPipeline
import gradio as gr
import torch

pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", torch_dtype=torch.float16)
pipe.to("cuda")

def generate(prompt):
    video_frames = pipe(prompt, num_inference_steps=25).frames
    return video_frames[0]  # return first frame or full video logic

gr.Interface(fn=generate, inputs="text", outputs="image").launch()