Update app.py

app.py

@@ -5,6 +5,10 @@ import torch
 from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
 from diffusers.utils import export_to_video
 from base64 import b64encode
+import torch
+
+device = "cpu"  # Force CPU usage
+
 
 # Load pipeline (outside the function for efficiency)
 pipe = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b", torch_dtype=torch.float16, variant="fp16")
@@ -15,7 +19,7 @@ pipe.enable_vae_slicing()
 def Generate_video(prompt, video_duration_seconds):
     num_frames = video_duration_seconds * 10
     video_frames = pipe(prompt=prompt, negative_prompt="low quality",
-                         num_inference_steps=25, num_frames=num_frames).frames
+                   num_inference_steps=25, num_frames=num_frames, device=device).frames
     video_path = export_to_video(video_frames)  # Assuming you have this function defined
     return video_path