Update app.py

app.py

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+import torch
+import gradio as gr
+from diffusers import DiffusionPipeline
+
+# Load the pipeline from Hugging Face's model hub
+pipe = DiffusionPipeline.from_pretrained("THUDM/CogVideoX-2b")
+
+# Optional: Move the model to GPU for faster processing if available
+if torch.cuda.is_available():
+    pipe.to("cuda")
+
+# Define the function that generates the video from the user prompt
+def generate_video(prompt):
+    # Generate the video
+    video = pipe(prompt).videos[0]
+    # Save the video to a file (Gradio needs a file path to display video)
+    video_path = "generated_video.mp4"
+    video.save(video_path)
+    return video_path
+
+# Create a Gradio interface with text input for the prompt and video output
+interface = gr.Interface(
+    fn=generate_video,           # The function to generate the video
+    inputs="text",               # Text input for the prompt
+    outputs="video",             # Video output
+    title="Video Generator",     # Title of the Gradio app
+    description="Enter a prompt to generate a video using the diffusion model"
+)
+
+# Launch the Gradio app
+interface.launch()