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import gradio as gr
from transformers import pipeline
import requests
import json
def greet(file):
API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo"
headers = {"Authorization": "Bearer hf_api_key"}
def query(file):
with open(file, "rb") as f:
data = f.read()
response = requests.post(API_URL, headers=headers, data=data)
return response.json()
my_text = query(file)
#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() |