Add application file4
Browse files
app.py
CHANGED
@@ -2,30 +2,39 @@ import requests
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import time
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import threading
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import gradio as gr
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def get_public_ip():
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response = requests.get('https://api.ipify.org?format=json')
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return response.json()["ip"]
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def simulate_interaction():
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# *** Placeholder for simulating activity
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print("Simulating interaction...")
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def background_interaction():
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"""
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while True:
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simulate_interaction()
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time.sleep(60 * 5)
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# Gradio interface with
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iface = gr.Interface(
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)
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# Start background interaction thread
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interaction_thread = threading.Thread(target=background_interaction)
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interaction_thread.start()
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import time
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import threading
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import gradio as gr
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from transformers import pipeline
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# Load Whisper model (adjust size as needed)
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model = pipeline("automatic-speech-recognition", model="openai/whisper-base")
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def get_public_ip():
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response = requests.get('https://api.ipify.org?format=json')
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return response.json()["ip"]
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def simulate_interaction():
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# *** Placeholder for simulating activity ***
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print("Simulating interaction...")
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def transcribe_audio(audio):
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transcription = model(audio)["text"]
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return transcription
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def background_interaction():
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"""Placeholder for background interaction"""
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while True:
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simulate_interaction()
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time.sleep(60 * 5)
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# Gradio interface with IP display and speech-to-text
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iface = gr.Interface(
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[get_public_ip, transcribe_audio],
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[gr.inputs.Textbox(lines=1, placeholder="Public IP will appear here"), gr.inputs.Audio(source="microphone", type="filepath")],
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[gr.outputs.Textbox(), gr.outputs.Textbox()],
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title="Public IP Retriever & Whisper Transcription",
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description="Get your approximate public IP and transcribe audio using Whisper."
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)
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# Start background interaction thread (optional)
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interaction_thread = threading.Thread(target=background_interaction)
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interaction_thread.start()
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