Update app.py

app.py

@@ -1,30 +1,26 @@
 import gradio as gr
 import torch
-from diffusers import DiffusionPipeline, AutoPipelineForText2Image
+from diffusers import AutoPipelineForText2Image
 import base64
 from io import BytesIO
 
+# Load the model once outside of the function
+model = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo")
 
-
-def text_to_image_model():
-    # AutoPipelineForText2Image.from_pretrained("stabilityai/sd-turbo")
-    # AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo")
-     return AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo")
-
-# Generate image from prompt using AmusedPipeline
 def generate_image(prompt):
     try:
-        pipe = text_to_image_model()
-        image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+        image = model(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
         return image, None
     except Exception as e:
         return None, str(e)
 
 def inference(prompt):
-    print(f"Received prompt: {prompt}")  # Debugging statement
+    print(f"Received prompt: {prompt}")
+    # Debugging statement
     image, error = generate_image(prompt)
     if error:
-        print(f"Error generating image: {error}")  # Debugging statement
+        print(f"Error generating image: {error}")
+        # Debugging statement
         return "Error: " + error
     
     buffered = BytesIO()
@@ -39,4 +35,4 @@ gradio_interface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    gradio_interface.launch()
+    gradio_interface.launch()