#!/usr/bin/env python
# -*- coding: utf-8 -*-

from tempfile import NamedTemporaryFile

import streamlit as st

from conette import CoNeTTEModel, conette


@st.cache_resource
def load_conette(*args, **kwargs) -> CoNeTTEModel:
    return conette(*args, **kwargs)


def main() -> None:
    st.header("CoNeTTE model test")
    model = load_conette(model_kwds=dict(device="cpu"))

    task = st.selectbox("Task embedding input", model.tasks, 0)
    beam_size: int = st.select_slider(  # type: ignore
        "Beam size",
        list(range(1, 20)),
        model.config.beam_size,
    )
    min_pred_size: int = st.select_slider(  # type: ignore
        "Minimal number of words",
        list(range(1, 31)),
        model.config.min_pred_size,
    )
    max_pred_size: int = st.select_slider(  # type: ignore
        "Maximal number of words",
        list(range(1, 31)),
        model.config.max_pred_size,
    )

    audios = st.file_uploader(
        "Upload an audio file",
        type=["wav", "flac", "mp3", "ogg", "avi"],
        accept_multiple_files=True,
    )

    if audios is not None and len(audios) > 0:
        for audio in audios:
            with NamedTemporaryFile() as temp:
                temp.write(audio.getvalue())
                fpath = temp.name
                outputs = model(
                    fpath,
                    task=task,
                    beam_size=beam_size,
                    min_pred_size=min_pred_size,
                    max_pred_size=max_pred_size,
                )
                cand = outputs["cands"][0]

                st.write(f"Output for {audio.name}:")
                st.write(" - ", cand)


if __name__ == "__main__":
    main()