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import gradio as gr | |
from gradio_client import Client, handle_file | |
def text_to_image(client, prompt, image, duration): | |
result = client.predict( | |
prompt=prompt, | |
input_image_filepath=handle_file(image), | |
duration_ui=duration, | |
api_name="/generate_video" | |
) | |
return result | |
def set_client_for_session(request: gr.Request): | |
x_ip_token = request.headers['x-ip-token'] | |
# The "gradio/text-to-image" space is a ZeroGPU space | |
return Client("KingNish/ltx-video-distilled", headers={"X-IP-Token": x_ip_token}) | |
with gr.Blocks() as demo: | |
client = gr.State() | |
image = gr.Image(type="filepath") | |
prompt = gr.Textbox(max_lines=1) | |
duration = gr.Slider(minimum=1, maximum=8, step=1, interactive=True) | |
submit_button = gr.Button("Submit") | |
output = gr.Video() | |
submit_button.click(text_to_image, [client, prompt, image, duration], [output]) | |
demo.load(set_client_for_session, None, client) | |
demo.launch() |