import os
os.environ["STREAMLIT_HOME"] = "/tmp"
os.environ["MPLCONFIGDIR"] = "/tmp"
os.environ["STREAMLIT_BROWSER_GATHER_USAGE_STATS"] = "false"
os.environ["STREAMLIT_WATCHER_TYPE"] = "none"
os.environ["XDG_CACHE_HOME"] = "/tmp"

import asyncio
try:
    asyncio.get_running_loop()
except RuntimeError:
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)

import streamlit as st
import whisper
import uuid

st.title("🧪 Whisper Tiny ASR (No Diarization)")
st.write("Upload an audio file (wav/mp3/m4a) and get a quick transcription using Whisper Tiny.")

uploaded = st.file_uploader("Choose an audio file", type=["wav", "mp3", "m4a", "flac"])

if uploaded:
    audio_id = uuid.uuid4().hex
    audio_path = f"/tmp/audio_{audio_id}.wav"
    with open(audio_path, "wb") as f:
        f.write(uploaded.read())
    st.success(f"✅ File saved to {audio_path}")

    if st.button("Transcribe"):
        with st.spinner("Loading Whisper (tiny)..."):
            model = whisper.load_model("tiny").to("cpu")

        with st.spinner("Transcribing..."):
            result = model.transcribe(audio_path, language="id")
            st.header("📝 Transcription Result")
            st.markdown(result["text"])