Update app.py

app.py

@@ -1,55 +1,8 @@
 import gradio as gr
-from flask import Flask, request
 import os
-import time
-from collections import defaultdict
 
-# Environment variables for authentication and model
-token = os.environ["TOKEN"]
-model = os.environ["MODEL"]
-
-# Create Flask app
-app = Flask(__name__)
-
-# Rate-limiting configuration
-RATE_LIMIT_WINDOW = 60  # Time window in seconds
-RATE_LIMIT_REQUESTS = 5  # Max requests per user per window
-
-# Dictionary to store request logs
-request_log = defaultdict(list)
-
-# Function to apply rate limiting
-def rate_limiter():
-    user_ip = request.remote_addr  # Retrieve the user's IP address
-    current_time = time.time()
-
-    # Clean up old requests outside the rate limit window
-    request_log[user_ip] = [
-        timestamp for timestamp in request_log[user_ip]
-        if current_time - timestamp < RATE_LIMIT_WINDOW
-    ]
 
-    # Check if the user exceeded the allowed requests
-    if len(request_log[user_ip]) >= RATE_LIMIT_REQUESTS:
-        return "❌ Rate limit exceeded. Please wait and try again later."
-
-    # Log the current request timestamp
-    request_log[user_ip].append(current_time)
-    return None  # Indicate no rate limit violation
-
-# Load the Gradio model from Hugging Face Spaces
+token = os.environ["TOKEN"]
+model=os.environ["MODEL"]
 demo = gr.load(model, src="spaces", token=token)
-
-# Route to serve the Gradio interface with rate limiting
-@app.route("/", methods=["GET", "POST"])
-def gradio_interface():
-    # Apply rate limiting
-    rate_limit_message = rate_limiter()
-    if rate_limit_message:
-        return rate_limit_message  # Return rate limit error if exceeded
-
-    # Launch Gradio app
-    return demo.launch(prevent_thread_lock=True)
-
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860)  # Run the Flask app
+demo.launch(show_api=False, show_error=False, quiet=True, debug=False)