Optimize Gradio configuration for better performance and reliability

app.py

@@ -1,9 +1,6 @@
 import gradio as gr
 from transformers import T5Tokenizer, T5ForConditionalGeneration
-from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware
 
-# Initialize Gradio interface directly without FastAPI
 # Load the base T5 model and tokenizer
 model = T5ForConditionalGeneration.from_pretrained('t5-small')
 tokenizer = T5Tokenizer.from_pretrained('t5-small')
@@ -65,13 +62,11 @@ demo = gr.Interface(
 # Enable queue
 demo.queue()
 
-# Launch the app
+# Launch the app with optimized configuration for Hugging Face Spaces
 if __name__ == "__main__":
+    demo.queue(concurrency_count=1, max_size=20)  # Configure queue for better performance
     demo.launch(
-        share=True,
         server_name="0.0.0.0",
-        server_port=7860,
-        allowed_paths=[],
-        show_error=True,
-        cors_allowed_origins=["https://pdarleyjr.github.io"]
+        share=True,
+        show_error=True
     )