| 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() |