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import logging

import gradio as gr
from transformers import pipeline

logging.basicConfig(
    format="%(asctime)s [%(levelname)s] [NLU] [Trainer] %(message)s",
    datefmt="%Y-%m-%dT%H:%M:%SZ",
)
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)

pipe = pipeline(model="bhuang/wav2vec2-xls-r-1b-cv9-fr")


def transcribe(audio, state=""):
    text = pipe(audio, chunk_length_s=5, stride_length_s=1)["text"]
    state += text + " "
    logger.info(f"Transcription for {audio}: {state}")
    return state, state


# streaming mode
iface = gr.Interface(
    fn=transcribe,
    inputs=[gr.Audio(source="microphone", type="filepath", streaming=True, label="Record something..."), "state"],
    outputs=["textbox", "state"],
    title="Realtime Speech-to-Text in French",
    description="Realtime demo for French automatic speech recognition.",
    allow_flagging="never",
    live=True,
)

iface.launch()