Update app.py

app.py

@@ -3,7 +3,9 @@ import torch
 from diffusers import I2VGenXLPipeline
 from diffusers.utils import export_to_gif, load_image
 import tempfile
+import spaces
 
+@spaces.GPU
 def initialize_pipeline(device):
     # Initialize the pipeline with CUDA support
     pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float16, variant="fp16")
@@ -12,7 +14,6 @@ def initialize_pipeline(device):
 
 def generate_gif(prompt, image, negative_prompt, num_inference_steps, guidance_scale, seed):
     # Check if CUDA is available and set the device
-    device = "cuda" if torch.cuda.is_available() else "cpu"
 
     # Initialize the pipeline within the function
     pipeline = initialize_pipeline(device)
@@ -65,7 +66,7 @@ with gr.Blocks() as demo:
 
             text_generate_button.click(
                 fn=generate_gif,
-                inputs=[text_prompt, None, text_negative_prompt, text_num_inference_steps, text_guidance_scale, text_seed],
+                inputs=[text_prompt, gr.Image(type="filepath", label="Input Image (optional)", visible=False), text_negative_prompt, text_num_inference_steps, text_guidance_scale, text_seed],
                 outputs=text_output_video
             )