app.py

import gradio as gr
from transformers import pipeline

MODEL_NAME = "openai/whisper-large-v3"
BATCH_SIZE = 8

asr = pipeline(
    task="automatic-speech-recognition",
    model=MODEL_NAME,
)

def transcribe(filepath):
    if filepath is None:
        gr.Warning("No audio found, please retry.")
        return ""
    output = asr(
      filepath,
      max_new_tokens=256,
      chunk_length_s=30,
      batch_size=8,
    )
    return output["text"]

mic_transcribe = gr.Interface(
    fn=transcribe,
    inputs=gr.Audio(sources="microphone",
                    type="filepath"),
    outputs=gr.Textbox(label="Transcription",
                       lines=3),
    allow_flagging="never")

demo = gr.Blocks()

with demo:
    gr.TabbedInterface(
        [mic_transcribe],
        ["Transcribe Microphone"],
    )

demo.launch()