Update app.py

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 import torch
-from diffusers import AutoPipelineForText2Image
+from diffusers import StableDiffusionXLPipeline, AutoPipelineForText2Image
 from io import BytesIO
 import asyncio
 from generate_propmts import generate_prompt
@@ -12,7 +12,7 @@ model = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo")
 async def generate_image(prompt):
     try:
         # Generate an image based on the prompt
-        output = await asyncio.to_thread(model, prompt=prompt, num_inference_steps=1, guidance_scale=0.0)
+        output = await asyncio.to_thread(model, prompt=prompt, num_inference_steps=50, guidance_scale=7.5)
         print(f"Model output: {output}")
 
         # Check if the model returned images
@@ -48,6 +48,8 @@ async def process_prompt(sentence_mapping, character_dict, selected_style):
     for i, (paragraph_number, _) in enumerate(prompts):
         if i < len(results):
             images[paragraph_number] = results[i]
+        else:
+            print(f"Error: No image generated for paragraph {paragraph_number}")
 
     return images
 
@@ -59,9 +61,9 @@ gradio_interface = gr.Interface(
         gr.JSON(label="Character Dict"),
         gr.Dropdown(["oil painting", "sketch", "watercolor"], label="Selected Style")
     ],
-    outputs="text",
-    concurrency_limit=20  # Set a high concurrency limit
+    outputs="json",
+    concurrency_count=20  # Set a high concurrency limit
 )
 
 if __name__ == "__main__":
-    gradio_interface.launch()  # No need for share=True for local testing
+    gradio_interface.launch()  # No need for share=True for local testing