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import gradio as gr | |
from gradio_client import Client, handle_file | |
import os | |
client = Client(f"ahmedJaafari/{os.getenv('API_ENDPOINT')}", hf_token=os.getenv("API_KEY")) | |
def classify_audio(audio, choice): | |
# Simulating the classification result based on audio | |
result = client.predict( | |
audio=handle_file(audio), | |
choice=choice, | |
api_name="/predict" | |
) | |
transcript = result | |
return transcript | |
iface = gr.Interface( | |
fn=classify_audio, | |
inputs=[ | |
gr.Audio(type="filepath", label="Record Audio"), | |
gr.Radio(["Normal", "Advanced"], label="Select Model") | |
], | |
outputs=[ | |
gr.Textbox(label="Transcript") # Transcript of the audio | |
], | |
title="Vochai - Transcription", | |
description=( | |
"Developed by Vochai. For more information, visit [Voch.ai](https://voch.ai) or contact us at [email protected].\n\n" | |
"N.B. This Tool is for demonstration purposes only, the results may not be 100% accurate and the speed is slower than usual." | |
), | |
) | |
iface.launch() | |