app.py

import streamlit as st
import librosa
import numpy as np
import matplotlib.pyplot as plt
from pydub import AudioSegment
from io import BytesIO
from utils import apply_equalizer, apply_pitch_shift, extract_lyrics

st.set_page_config(page_title="AI Singing Voice Player", layout="wide")

st.title("🎤 AI Singing Voice Player with Equalizer, Visualizer & Karaoke")

audio_file = "audio/output.wav"
y, sr = librosa.load(audio_file)

# Equalizer Controls
st.sidebar.header("🎚️ Equalizer & Pitch")
bass_gain = st.sidebar.slider("Bass Gain (dB)", -10, 10, 0)
mid_gain = st.sidebar.slider("Mid Gain (dB)", -10, 10, 0)
treble_gain = st.sidebar.slider("Treble Gain (dB)", -10, 10, 0)
pitch_shift_val = st.sidebar.slider("Pitch Shift (semitones)", -12, 12, 0)

# Apply Equalizer and Pitch Shift
y_eq = apply_equalizer(y, bass_gain, mid_gain, treble_gain, sr)
y_final = apply_pitch_shift(y_eq, sr, pitch_shift_val)

# Convert to playable audio
audio_bytes = BytesIO()
AudioSegment(
    y_final.tobytes(), frame_rate=sr, sample_width=2, channels=1
).export(audio_bytes, format="wav")

# Audio Player
st.audio(audio_bytes, format='audio/wav')

# Optional Real-time Visualizer
if st.checkbox("🎶 Show Real-Time Spectrum Visualizer"):
    HtmlFile = open("static/visualizer.html", 'r', encoding='utf-8')
    source_code = HtmlFile.read()
    st.components.v1.html(source_code, height=350)

# Optional Karaoke Lyrics Sync
if st.checkbox("🎤 Show Karaoke Lyrics (Optional Upload)"):
    lyrics_file = st.file_uploader("Upload Lyrics (.lrc or .txt)", type=["lrc", "txt"])
    if lyrics_file:
        lyrics_text = extract_lyrics(lyrics_file)
        st.markdown("### 📜 Lyrics:")
        st.markdown(lyrics_text, unsafe_allow_html=True)

# Waveform Visualization
st.subheader("Waveform Visualization")
fig, ax = plt.subplots(figsize=(10, 3))
librosa.display.waveshow(y_final, sr=sr, ax=ax)
st.pyplot(fig)