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import gradio as gr | |
import openai | |
import shutil | |
import tempfile | |
import os | |
vocabolario_LOUD = os.environ.get("VOCABOLARIO_LOUD") | |
open_ai_key = os.environ.get("OPEN_AI_KEY") | |
openai.api_key = open_ai_key | |
def transcribe(audio): | |
# the audio file has no extension. We mae a .wav copy: | |
with tempfile.NamedTemporaryFile(suffix=".wav", delete=True) as temp_audio_file: | |
shutil.copy(audio, temp_audio_file.name) | |
audio_filepath = temp_audio_file.name | |
audio_file= open(audio_filepath, "rb") | |
transcript = openai.Audio.transcribe("whisper-1", audio_file, prompt=vocabolario_LOUD, language="it") | |
return transcript["text"] | |
app = gr.Interface(fn=transcribe, inputs=gr.Microphone(type="filepath"), outputs="text", title="Demo di trascrizione con vocabolario LOUD",description="Demo implementante l'API di Whisper personalizzato con vocabolario LOUD", theme="dark-peach") | |
app.launch() | |