Update app.py

app.py

@@ -5,7 +5,9 @@ import os
 import random
 import gradio as gr
 import numpy as np
-import PIL.Image
+from PIL import Image
+import base64
+import io
 import torch
 from diffusers import LCMScheduler, AutoPipelineForText2Image
 
@@ -52,7 +54,7 @@ def generate(prompt: str,
     if not use_negative_prompt:
         negative_prompt = None  # type: ignore
 
-    return pipe(prompt=prompt,
+    image = pipe(prompt=prompt,
                 negative_prompt=negative_prompt,
                 width=width,
                 height=height,
@@ -60,6 +62,14 @@ def generate(prompt: str,
                 num_inference_steps=num_inference_steps,
                 generator=generator,
                 output_type='pil').images[0]
+    
+    # Convert PIL image to a byte stream
+    buffered = io.BytesIO()
+    image.save(buffered, format="PNG")
+    
+    # Encode to base64
+    img_str = base64.b64encode(buffered.getvalue()).decode()
+    return img_str
 
 with gr.Blocks() as demo:
     gr.HTML("""
@@ -81,7 +91,7 @@ with gr.Blocks() as demo:
         placeholder='Enter your prompt',
         container=False,
     )
-    result = gr.Image(label='Result', show_label=False)
+    result = gr.Image(label='Result', show_label=False, type="base64")
 
     use_negative_prompt = gr.Checkbox(label='Use negative prompt', value=False)
     negative_prompt = gr.Text(
@@ -156,4 +166,4 @@ with gr.Blocks() as demo:
         api_name='run',
     )
 
-demo.queue(max_size=16).launch()
+demo.queue(max_size=32).launch()