Update app.py

app.py

@@ -1,47 +1,25 @@
 import gradio as gr
-import threading
-import requests
-import time
+import websockets
+import asyncio
+
+async def send_to_websocket(message):
+    uri = "ws://localhost:8765"  # Replace with your WebSocket server URI
+    async with websockets.connect(uri) as websocket:
+        await websocket.send(message)
+        response = await websocket.recv()
+        return response
+
+def predict(input_text):
+    # You can replace this with your actual machine learning model prediction logic
+    # For now, we'll just send the input to the WebSocket server and echo the response
+    response = asyncio.run(send_to_websocket(input_text))
+    return response
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(),
+    outputs="text",
+    live=True,
+)
 
-def send_dummy_request(space_url):
-    try:
-        response = requests.get(space_url)
-        # Print the response status code (optional)
-        print(f"Response Status Code Of Wait: {response.status_code}")
-    except Exception as e:
-        print(f"Error: {e}")
-
-def send_dummy_request_self(space_url_self):
-    try:
-        response = requests.get(space_url_self)
-        # Print the response status code (optional)
-        print(f"Response Status Code Of Self: {response.status_code}")
-    except Exception as e:
-        print(f"Error: {e}")
-
-def background_request(space_url,space_url_self, interval_seconds):
-    try:
-        while True:
-            send_dummy_request(space_url)
-            send_dummy_request_self(space_url_self)
-            time.sleep(interval_seconds)
-    except KeyboardInterrupt:
-        print("Background script terminated by user.")
-
-# Replace 'YOUR_SPACE_URL' with the actual URL of your deployed Hugging Face Space
-space_url = 'https://huggingface.co/spaces/clone3/Wait'
-space_url_self = 'https://huggingface.co/spaces/clone3/Sender'
-
-# Set the interval for sending requests (in seconds)
-interval_seconds = 1800  # 30 minutes
-
-# Start the background thread
-background_thread = threading.Thread(target=background_request, args=(space_url,space_url_self, interval_seconds))
-background_thread.start()
-
-# Gradio interface
-def echo_text(text):
-    return f"You said: {text}"
-
-iface = gr.Interface(fn=echo_text, inputs="text", outputs="text")
 iface.launch()