Update app.py

app.py

@@ -2,32 +2,45 @@ import gradio as gr
 import torch
 from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
 from diffusers.utils import export_to_video
+import logging
 
-# Initialize the diffusion pipeline
-pipe = DiffusionPipeline.from_pretrained(
-    "heboya8/text2video-test-2",    
-    torch_dtype=torch.float16,
-    # variant="fp16",
-    trust_remote_code=True,
-)
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+try:
+    # Initialize the diffusion pipeline
+    logger.info("Loading diffusion pipeline...")
+    pipe = DiffusionPipeline.from_pretrained(
+        "heboya8/text2video-test-2",
+        torch_dtype=torch.float16,
+        trust_remote_code=True,
+    )
 
-# Optimize for GPU memory
-pipe.enable_model_cpu_offload()
-pipe.enable_vae_slicing()
+    # Optimize for GPU memory
+    logger.info("Enabling CPU offload and VAE slicing...")
+    pipe.enable_model_cpu_offload()
+    pipe.enable_vae_slicing()
+except Exception as e:
+    logger.error(f"Failed to initialize pipeline: {str(e)}")
+    raise
 
 def generate_video(prompt):
     try:
+        logger.info(f"Generating video for prompt: {prompt}")
         # Generate video frames
         video_frames = pipe(
             prompt,
-            num_inference_steps=1,
-            num_frames=1
+            num_inference_steps=50,  # Increased for better quality
+            num_frames=16,          # Increased for longer video
         ).frames
-        
+
         # Export frames to video file
         video_path = export_to_video(video_frames, output_video_path="output_video.mp4")
+        logger.info(f"Video generated at: {video_path}")
         return video_path
     except Exception as e:
+        logger.error(f"Error generating video: {str(e)}")
         return f"Error generating video: {str(e)}"
 
 # Create Gradio interface
@@ -43,4 +56,6 @@ interface = gr.Interface(
 )
 
 # Launch the app
-interface.launch()
+if __name__ == "__main__":
+    logger.info("Launching Gradio interface...")
+    interface.launch(server_name="0.0.0.0", server_port=7860)