Add application file4

app.py

@@ -2,30 +2,39 @@ import requests
 import time
 import threading
 import gradio as gr
+from transformers import pipeline
+
+# Load Whisper model (adjust size as needed)
+model = pipeline("automatic-speech-recognition", model="openai/whisper-base")
 
 def get_public_ip():
     response = requests.get('https://api.ipify.org?format=json')
     return response.json()["ip"]
 
 def simulate_interaction():
-    # *** Placeholder for simulating activity within a real application ***   
-    print("Simulating interaction...")  # Example action
+    # *** Placeholder for simulating activity ***   
+    print("Simulating interaction...") 
+
+def transcribe_audio(audio):
+    transcription = model(audio)["text"]
+    return transcription
 
 def background_interaction():
-    """Performs simulated interaction in a background thread"""
+    """Placeholder for background interaction"""
     while True:
         simulate_interaction()
-        time.sleep(60 * 5)  # Simulate interaction every 5 minutes
+        time.sleep(60 * 5)  
 
-# Gradio interface with public IP display
+# Gradio interface with IP display and speech-to-text
 iface = gr.Interface(
-    fn=get_public_ip, 
-    outputs="text", 
-    title="Public IP Retriever",
-    description="Displays the approximate public IP address."
+    [get_public_ip, transcribe_audio], 
+    [gr.inputs.Textbox(lines=1, placeholder="Public IP will appear here"), gr.inputs.Audio(source="microphone", type="filepath")], 
+    [gr.outputs.Textbox(), gr.outputs.Textbox()],
+    title="Public IP Retriever & Whisper Transcription",
+    description="Get your approximate public IP and transcribe audio using Whisper."
 )
 
-# Start background interaction thread
+# Start background interaction thread (optional)
 interaction_thread = threading.Thread(target=background_interaction)
 interaction_thread.start()