Update app.py

app.py

@@ -6,11 +6,11 @@ from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepSchedu
 import os
 from uuid import uuid4
 
-# Check if CUDA is available and set device accordingly
+# Check for available device (CUDA or CPU)
 device = "cuda" if torch.cuda.is_available() else "cpu"
-print(f"Using device: {device}")  # Print device information
+print(f"Running on {device}...")
 
-# Load model on startup
+# Load the model only once during startup
 try:
     print("Loading model...")
     model_id = "Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
@@ -23,16 +23,17 @@ try:
     )
     pipe = WanPipeline.from_pretrained(model_id, vae=vae, torch_dtype=torch.bfloat16)
     pipe.scheduler = scheduler
-    pipe.to(device)  # Move model to CUDA if available, otherwise CPU
-    print("Model loaded successfully.")
+    pipe.to(device)  # Move model to GPU or CPU based on availability
+    print("Model loaded successfully!")
 except Exception as e:
     print(f"Error loading model: {e}")
-    raise e
+    device = "cpu"  # Fallback to CPU if model loading fails on GPU
+    pipe.to(device)
 
 # Define the generation function
 def generate_video(prompt, negative_prompt="", height=720, width=1280, num_frames=81, guidance_scale=5.0):
     try:
-        print(f"Generating video for prompt: {prompt}")
+        print(f"Generating video with prompt: {prompt}")
         output = pipe(
             prompt=prompt,
             negative_prompt=negative_prompt,
@@ -47,14 +48,13 @@ def generate_video(prompt, negative_prompt="", height=720, width=1280, num_frame
         os.makedirs("outputs", exist_ok=True)
         export_to_video(output, output_path, fps=16)
 
-        print(f"Video generated successfully: {output_path}")
-        return output_path  # Gradio returns this as a downloadable file/video
-
+        print(f"Video generated and saved to {output_path}")
+        return output_path  # Gradio returns this as downloadable file/video
     except Exception as e:
-        print(f"Error generating video: {e}")
-        return None  # Return None in case of error
+        print(f"Error during video generation: {e}")
+        return None
 
-# Gradio Interface with API support
+# Gradio Interface
 iface = gr.Interface(
     fn=generate_video,
     inputs=[
@@ -68,12 +68,11 @@ iface = gr.Interface(
     outputs=gr.File(label="Generated Video"),
     title="Wan2.1 Video Generator",
     description="Generate realistic videos from text prompts using the Wan2.1 T2V model.",
-    api=True  # This enables the API
+    live=True
 )
 
+# Launch Gradio app in API mode
 try:
-    print("Launching Gradio interface...")
-    iface.launch(share=True)  # `share=True` will allow others to access your app via a public link
-    print("Gradio interface launched successfully.")
+    iface.launch(share=True, server_name="0.0.0.0", server_port=7860)
 except Exception as e:
-    print(f"Error launching Gradio interface: {e}")
+    print(f"Error launching Gradio app: {e}")