app.py

from transformers import pipeline
import gradio as gr

pipe = pipeline(model="Yuyang2022/yue")  # change to "your-username/the-name-you-picked"

def transcribe(audio):
    text = pipe(audio)["text"]
    return text

def transcribe_video(link):
    video=link
    data=pytube.YouTube(video)
    audio=data.streams.get_audio_only()
    audio.download()

    pattern=r".mp4$"
    content=os.listdir()
    for i in content:
        if re.search(pattern,i) is not None:
            video=i
    
    text = pipe(video)["text"]
    return text

iface1 = gr.Interface(
    fn=transcribe, 
    inputs=gr.Audio(source="microphone", type="filepath"), 
    outputs="text",
    title="Whisper Base",
    description="Realtime demo for  speech recognition using a fine-tuned Whisper-base model.",
)

iface2 = gr.Interface(
    fn=transcribe_video, 
    inputs=gr.Textbox(label="Youtube Link",placeholder="Youtube Link"), 
    outputs=["text"],
    title="Whisper Base",
    description="Asynchronous demo for youtube speech recognition using a fine-tuned Whisper-base model.",
)



iface1.launch()