import gradio as gr
import subprocess
import os
import spaces
import torch

extensions_dir = "./torch_extension/"
os.environ["TORCH_EXTENSIONS_DIR"] = extensions_dir

from networks.generator import Generator

device = torch.device("cuda")
gen = Generator(size=512, motion_dim=40, scale=2).to(device)
tmp_ckpt_path = "/home/user/.cache/torch/hub/checkpoints/lia-x.pt"
if os.path.exists(tmp_ckpt_path):
	gen.load_state_dict(torch.load(tmp_ckpt_path, weights_only=True))
else:
	gen.load_state_dict(torch.hub.load_state_dict_from_url(f"https://huggingface.co/YaohuiW/LIA-X/resolve/main/lia-x.pt"))
gen.eval()

chunk_size=8

def load_file(path):

	with open(path, 'r', encoding='utf-8') as f:
		content  = f.read()

	return content

custom_css = """
<style>
  body {
	font-family: Georgia, serif; /* Change to your desired font */
  }
  h1 {
	color: black; /* Change title color */
  }
</style>
"""


# def load_tabs():
# 	from gradio_tabs.animation import animation
# 	from gradio_tabs.vid_edit import vid_edit
    
# 	animation()
# 	vid_edit()


with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
	# ... (input/output setup remains unchanged)

	gr.HTML(load_file("assets/title.md"))
	with gr.Row():
		with gr.Accordion(open=False, label="Instruction"):
			gr.Markdown(load_file("assets/instruction.md"))
	
	with gr.Row():
		with gr.Tabs():
			from gradio_tabs.animation import animation
			from gradio_tabs.vid_edit import vid_edit
			animation(gen, chunk_size, device)
			vid_edit(gen, chunk_size, device)

    
demo.launch(
    server_name='0.0.0.0',
    share=True,
    allowed_paths=["./data/source","./data/driving"]
)