Revert

app.py

@@ -1,12 +1,10 @@
 import os
+import spaces
 import torch
 from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
 import gradio as gr
 import random
 import tqdm
-from pyngrok import ngrok
-
-NGROK_API_KEY = os.getenv("NGROK_API_KEY")
 
 # Enable TQDM progress tracking
 tqdm.monitor_interval = 0
@@ -21,6 +19,7 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
 pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
 
 # Function to generate an image
+@spaces.GPU()  # Adjust the duration as needed
 def generate_image(prompt, negative_prompt, use_defaults, resolution, guidance_scale, num_inference_steps, seed, randomize_seed, progress=gr.Progress()):
     pipe.to('cuda')  # Move the model to GPU when the function is called
     
@@ -104,8 +103,4 @@ with gr.Blocks(title="UrangDiffusion 1.0 Demo", theme="NoCrypt/[email protected]") as d
         ]
     )
 
-# Set up ngrok
-public_url = ngrok.connect(api_key=NGROK_API_KEY)
-print(f"Public URL: {public_url}")
-
-demo.queue(max_size=20).launch(server_name="0.0.0.0", server_port=7860)
+demo.queue(max_size=20).launch(share=False)