app1.py

import streamlit as st
import pandas as pd
from sklearn.neighbors import NearestNeighbors
import plotly.express as px
import uuid
import streamlit.components.v1 as components
import warnings
warnings.filterwarnings("ignore", category=FutureWarning)
st.set_page_config(page_title="Music Recommendation", layout="wide")

@st.cache_data()
def load_data():
    df = pd.read_csv("data/processed_track_df.csv")
    df['genres'] = df.genres.apply(lambda x: [i[1:-1] for i in str(x)[1:-1].split(", ")])
    exploded_track_df = df.explode("genres")
    return exploded_track_df
    
genre_names = ['Dance Pop', 'Electronic', 'Electropop', 'Hip Hop', 'Jazz', 'K-pop', 'Latin', 'Pop', 'Pop Rap', 'R&B', 'Rock']
audio_feats = ["acousticness", "danceability", "energy", "instrumentalness", "valence", "tempo"]
exploded_track_df = load_data()
def n_neighbors_uri_audio(genre, start_year, end_year, test_feat):
    genre = genre.lower()
    genre_data = exploded_track_df[(exploded_track_df["genres"]==genre) & (exploded_track_df["release_year"]>=start_year) & (exploded_track_df["release_year"]<=end_year)]
    genre_data = genre_data.sort_values(by='popularity', ascending=False)[:500]
    neigh = NearestNeighbors()
    neigh.fit(genre_data[audio_feats].to_numpy())
    n_neighbors = neigh.kneighbors([test_feat], n_neighbors=len(genre_data), return_distance=False)[0]
        
    uris = genre_data.iloc[n_neighbors]["uri"].tolist()
    audios = genre_data.iloc[n_neighbors][audio_feats].to_numpy()
    return uris, audios


def login_page():
    st.title("User Login")
    username = st.text_input("Username", key="login_username")
    password = st.text_input("Password", type="password", key="login_password")

    if st.button("Login"):
      user_data = pd.read_csv("user_data.csv")
      if username in user_data["Username"].values and password in user_data["Password"].values:
          st.success("Login successful!")
          st.session_state["is_logged_in"] = True
          
      else:
          st.warning("Invalid username or password.")
            
    st.markdown("Don't have an account? [Create one](?register=true)")

def register_page():
    st.write("Enter your details below to create a new account.")
    first_name = st.text_input("First name", key="register_first_name")
    last_name = st.text_input("Last name", key="register_last_name")
    email = st.text_input("Email", key="register_email")
    password = st.text_input("Password", type="password", key="register_password")

    if st.button("Create Account", key="register_button"):
        if first_name and last_name and email and password:
            user_data = {
                "Username": [first_name],
                "Password": [password]
            }
            df = pd.DataFrame(user_data)
            df.to_csv("user_data.csv", index=False)
            st.success("Account created successfully! Please log in.")
            st.experimental_rerun()
        else:
             st.warning("Please enter all of the required details.")

def recommendation_page():
    title = "Music Recommendation System"
    st.title(title)
        
    st.write("Welcome! Here you can customize what you want to listen to based on genres. And listen to the songs recommended by our system!")
    st.markdown("##")
        
    with st.container():
        col1, col2,col3,col4 = st.columns((2,0.5,0.5,0.5))
        with col1:
            st.markdown("***Customize Features :***")
            start_year, end_year = st.slider(
                'Select the year range',
                1990, 2019, (2010, 2019)
            )
            acousticness = st.slider(
                'Acousticness',
                0.0, 1.0, 0.5
            )
            danceability = st.slider(
                'Danceability',
                0.0, 1.0, 0.5
            )
            energy = st.slider(
                'Energy',
                0.0, 1.0, 0.5
            )
            instrumentalness = st.slider(
                'Instrumentalness',
                0.0, 1.0, 0.0
            )
            valence = st.slider(
                'Valence',
                0.0, 1.0, 0.45
            )
            tempo = st.slider(
                'Tempo',
                0.0, 244.0, 118.0
            )
        with col3:
             st.sidebar.header("***Select genre:***")
             genre = st.sidebar.radio(
                 "",
                 genre_names, index=genre_names.index("K-pop"))
                    
    tracks_per_page = 8
    test_feat = [acousticness, danceability, energy, instrumentalness, valence, tempo]
    uris, audios = n_neighbors_uri_audio(genre, start_year, end_year, test_feat)

    tracks = []
    for uri in uris:
        track = """<iframe src="https://open.spotify.com/embed/track/{}" width="260" height="380" frameborder="0" allowtransparency="true" allow="encrypted-media"></iframe>""".format(uri)
        tracks.append(track)

    if 'previous_inputs' not in st.session_state:
        st.session_state['previous_inputs'] = [genre, start_year, end_year] + test_feat
    
    current_inputs = [genre, start_year, end_year] + test_feat
    if current_inputs != st.session_state['previous_inputs']:
        if 'start_track_i' in st.session_state:
            st.session_state['start_track_i'] = 0
        st.session_state['previous_inputs'] = current_inputs

    if 'start_track_i' not in st.session_state:
        st.session_state['start_track_i'] = 0
    
    with st.container():
        col1, col2, col3 = st.columns([2,1,2])
        if st.button("Recommend More Songs"):
            if st.session_state['start_track_i'] < len(tracks):
                st.session_state['start_track_i'] += tracks_per_page

        current_tracks = tracks[st.session_state['start_track_i']: st.session_state['start_track_i'] + tracks_per_page]
        current_audios = audios[st.session_state['start_track_i']: st.session_state['start_track_i'] + tracks_per_page]
        if st.session_state['start_track_i'] < len(tracks):
            for i, (track, audio) in enumerate(zip(current_tracks, current_audios)):
                if i%2==0:
                    with col1:
                        components.html(
                            track,
                            height=400,
                        )
                        with st.expander("See more details"):
                            df = pd.DataFrame(dict(
                            r=audio[:5],
                            theta=audio_feats[:5]))
                            fig = px.line_polar(df, r='r', theta='theta', line_close=True)
                            fig.update_layout(height=400, width=340)
                            fig.update_traces(fill='toself')  
                            st.plotly_chart(fig)
            
                else:
                    with col3:
                        components.html(
                            track,
                            height=400,
                        )
                        with st.expander("See more details"):
                            df = pd.DataFrame(dict(
                                r=audio[:5],
                                theta=audio_feats[:5]))
                            fig = px.line_polar(df, r='r', theta='theta', line_close=True)
                            fig.update_layout(height=400, width=340)
                            fig.update_traces(fill='toself')  
                            st.plotly_chart(fig)

        else:
            st.write("No songs left to recommend")
            
def main():
    st.session_state.setdefault("is_logged_in", False)

    if not st.session_state["is_logged_in"]:
        if "register" in st.experimental_get_query_params():
            st.session_state["register"] = True
            register_page()
            st.stop()
        else:
            if not st.session_state.get("is_csv_created", False):
                df = pd.DataFrame(columns=["Username", "Password"])
                df.to_csv("user_data.csv", index=False)
                st.session_state["is_csv_created"] = True

            login_page()
            if "register" in st.session_state and st.session_state["register"]:
                register_page()
                st.stop()

        if st.session_state["is_logged_in"]:
            recommendation_page()

    else:
        recommendation_page()


if __name__ == "__main__":
    main()