app.py

import sys
import requests
import re
import os
import base64
import gradio as gr
api_token1="Bearer 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"
headers1= {"Authorization":api_token1}

API_URL = "https://api-inference.huggingface.co/models/jonatasgrosman/wav2vec2-large-xlsr-53-arabic"

def query(filename):
    with open(filename, "rb") as f:
        data = f.read()

    # Convert bytes to base64-encoded string
    encoded_data = base64.b64encode(data).decode()
    options = {"wait_for_model": True}  # Set wait_for_model parameter to True
    payload = {"inputs": encoded_data, "options": options}
    response = requests.post(API_URL, headers=headers1, json=payload)

    return response.json()

def process_audio(filename):
    response = query(filename)
    o1 = response['text']
    return o1
# Define the Gradio interface
demo = gr.Interface(
    fn=process_audio,
    inputs=gr.inputs.Audio(source="upload", type="filepath"),
    outputs="text"
)

# Launch the Gradio interface
demo.launch(share=True)