import os
import gradio as gr
from diffusers import StableVideoDiffusionPipeline
import torch

# Ensure dependencies are installed
os.system("pip install -r requirements.txt")

# Model Load (CPU Compatible)
model_id = "stabilityai/stable-video-diffusion-img2vid"
pipe = StableVideoDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)  # Float32 use karo
pipe.to("cpu")  # Ensure model runs on CPU

# Function to Generate Video
def generate_video(prompt):
    video = pipe(prompt, num_inference_steps=30).videos
    video_path = "generated_video.mp4"
    video[0].save(video_path)
    return video_path

# Gradio Interface
iface = gr.Interface(fn=generate_video, inputs="text", outputs="video")

# Launch Gradio Server on Hugging Face Space
iface.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)))