app.py

import gradio as gr
from transformers import pipeline
import requests
import json

def greet(sentences1):

    API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo"
    headers = {"Authorization": "Bearer hf_api_key"}

    def query(filename):
        with open(filename, "rb") as f:
            data = f.read()
        response = requests.post(API_URL, headers=headers, data=data)
        return response.json()

    my_text = query("rawveg7.mp3")

    sentences = my_text["text"].split(".")

    return my_text

    #translation = pipeline("translation", model="Helsinki-NLP/opus-mt-en-hu")
    
    #text_translated=[]
    #for text in sentences:
    #    text_translated.append(translation(text))

    #combined_text = ' '.join([item['translation_text'] for sublist in text_translated for item in sublist])

    #return text_translated

demo = gr.Interface(fn=greet, inputs="file", outputs="text")
demo.launch()