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import sys | |
import requests | |
import re | |
import os | |
import base64 | |
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) |