import streamlit as st
from downloader import download_video
from extractor import extract_audio
from detector import detect_accent
import asyncio

# Setup async event loop
try:
    asyncio.get_running_loop()
except RuntimeError:
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)

st.set_page_config(page_title="Accentometer", page_icon="🎙️")

# Sidebar navigation
st.sidebar.title("🎙️ Accentometer")
page = st.sidebar.radio("", ["Home", "Info"])

# ---------------------------
# Page 1: Home
# ---------------------------
if page == "Home":
    st.title("🎙️ Accentometer")

    # ✅ Example video links
    st.markdown("### Try with these example MP4 links:")

    st.text("Australian: https://docs.google.com/uc?export=download&id=12dKoO-jgWgjor_aQpovbtwOulMQBEEps")
    st.text("British:    https://docs.google.com/uc?export=download&id=10aiY_0dnsWXqhxeNL54n5LYe6l4XquR8")
    st.text("American:   https://docs.google.com/uc?export=download&id=1k1wfSxmQ-ZbYCKNZrb0aF8xfM6JWEfKQ")

    st.markdown(
        """
        📌 **Instructions**: Copy one of the above MP4 URLs and paste it into the field below, then click **Analyze** to detect the accent, and get a transcript.
        """
    )

    st.markdown(""" --- """)
    st.write("Paste a direct public MP4 video URL to **classify the English accent, get transcript**.")

    video_url = st.text_input("Direct Video URL (MP4 only):")

    if st.button("Analyze"):
        if not video_url:
            st.error("Please provide a valid MP4 video URL.")
        else:
            try:
                with st.spinner("Downloading video..."):
                    video_file_path = download_video(video_url)

                with st.spinner("Extracting audio..."):
                    audio_file = extract_audio(video_file_path)

                with st.spinner("Transcribing & detecting accent..."):
                    accent, confidence, transcript = detect_accent(audio_file)

                st.success(f"Accent: **{accent}**")
                st.metric(label="Confidence", value=f"{confidence}%")
                st.text_area("Transcript", transcript, height=150, disabled=True)

            except Exception as e:
                st.error(f"Error: {str(e)}")


# ---------------------------
# Page 2: Info
# ---------------------------
elif page == "Info":

    st.title("ℹ️ About Accentometer")

    st.markdown("""
    ### 🧠 What is Accentometer?

    **Accentometer** is a simple **demo** application for English accent classification.  
    It doesn't use any advanced machine learning or deep learning models beyond basic heuristics.

    ---

    ### ⚙️ How It Works

    1. **Video Downloader**  
    Accepts only **direct MP4 links**.  
    (Loom URLs aren’t supported in this free demo version — integration would require a paid Loom API or other backend setup.)

    2. **Audio Extraction**  
    Uses the `moviepy` library to extract the audio from the video.

    3. **Speech-to-Text**  
    Applies the `openai/whisper-base` model from Hugging Face to transcribe the audio into text.

    4. **Accent Detection**  
    Runs simple **hand-crafted heuristic rules** over the transcribed text to classify the accent into:
    - 🇺🇸 American
    - 🇬🇧 British
    - 🇦🇺 Australian
    - 🇮🇳 Indian
    - ❓ Unknown

    ---

    ### 🚀 Possible Improvements

    If you're interested in expanding this demo into a more robust application:

    - **Support More Input Options**: Upload local MP4 files, YouTube links, Loom links (via API), Additional video formats, etc.
    - **Improve Accent Detection**: Train a custom model using a labeled accent dataset, or integrate a model like `accent-id-commonaccent_xlsr-en-english`, or other approaches.

    ---
    """)