import requests import streamlit from PIL import Image from utils import * from app_utils import * import time from spotipy.oauth2 import SpotifyClientCredentials debug = False dir_path = os.path.dirname(os.path.realpath(__file__)) st.set_page_config( page_title="EmotionalPlaylist", page_icon="🎧", ) st.title('Emotional Playlists') def log_to_spotify(): st.subheader("Step 1: Connect to your Spotify app") st.markdown("Log into your Spotify account to let the app create the custom playlist.") if 'login' not in st.session_state or debug: if debug: client_credentials_manager = SpotifyClientCredentials() sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager) user_id = None auth_manager = None else: sp, user_id, auth_manager = new_get_client(session=st.session_state) if sp != None: legit_genres = sp.recommendation_genre_seeds()['genres'] st.session_state['login'] = (sp, user_id, legit_genres, auth_manager) st.success('You are logged in.') else: legit_genres = None else: sp, user_id, legit_genres, auth_manager = st.session_state['login'] st.success('You are logged in.') return sp, user_id, legit_genres, auth_manager @st.cache(suppress_st_warning=True) def get_user_playlists(users_links): global sp # Scanning users n_playlists = 0 all_uris, all_names = [], [] if users_links != "": try: print(users_links) user_ids = extract_uris_from_links(users_links, url_type='user') print(user_ids) all_uris, all_names = get_all_playlists_uris_from_users(sp, user_ids) n_playlists = len(all_uris) except: st.warning('Please enter a valid list of user names (one url per line)') return all_uris, all_names, n_playlists def get_filtered_user_playlists(user_links): global sp st.spinner(text="Scanning users..") all_uris, all_names, n_playlists = get_user_playlists(user_links) if n_playlists <= 1: return all_uris else: with st.expander("##### Select user playlists (default all)"): # let the user uncheck playlists st.markdown("Check boxes to select playlists from the selected users." "Note: to check all, first uncheck all (bug).") columns = st.columns(np.ones(5)) with columns[1]: check_all_playlists = st.button('Check all') with columns[3]: uncheck_all_playlists = st.button('Uncheck all') if 'checkboxes' not in st.session_state.keys(): st.session_state['checkboxes_playlists'] = [True] * n_playlists empty_checkboxes = wall_of_checkboxes(all_names, max_width=5) if check_all_playlists: st.session_state['checkboxes_playlists'] = [True] * n_playlists if uncheck_all_playlists: st.session_state['checkboxes_playlists'] = [False] * n_playlists for i_emc, emc in enumerate(empty_checkboxes): st.session_state['checkboxes_playlists'][i_emc] = emc.checkbox(all_names[i_emc], value=st.session_state['checkboxes_playlists'][i_emc]) filter_playlist = centered_button(st.button, 'Update user playlists', n_columns=5) if filter_playlist: return list(np.array(all_uris)[np.where(st.session_state['checkboxes_playlists'])]) else: return [] @st.cache(suppress_st_warning=True) def get_non_user_playlists(playlist_links): # Scanning playlists new_playlist_uris = [] if playlist_links != "": st.spinner(text="Scanning playlists..") try: new_playlist_uris = extract_uris_from_links(playlist_links, url_type='playlist') except: st.warning('Please enter a valid list of playlists (one url per line)') return new_playlist_uris @st.cache def extract_tracks(playlist_uris): global sp # extracting tracks data_tracks = get_all_tracks_from_playlists(sp, playlist_uris, verbose=True) return data_tracks @st.cache def extract_audio_features(data_tracks, legit_genres): # Extract audio features all_tracks_uris = np.array(list(data_tracks.keys())) all_audio_features = [data_tracks[uri]['track']['audio_features'] for uri in all_tracks_uris] valid_indexes = np.array([i for i in range(len(all_tracks_uris)) if all_audio_features[i] is not None]) all_tracks_uris = all_tracks_uris[valid_indexes] all_audio_features = np.array(all_audio_features)[valid_indexes] all_tracks_audio_features = dict(zip(relevant_audio_features, [[audio_f[k] for audio_f in all_audio_features] for k in relevant_audio_features])) all_tracks_genres = [] indexes_by_genre = dict() for index, uri in enumerate(all_tracks_uris): track = data_tracks[uri] track_genres = track['track']['genres'] all_tracks_genres.append([]) for glabel in track_genres: legit_genre = find_legit_genre(glabel, legit_genres) if legit_genre in indexes_by_genre.keys(): indexes_by_genre[legit_genre].append(index) else: indexes_by_genre[legit_genre] = [index] all_tracks_genres[-1].append(legit_genre) all_tracks_genres[-1] = sorted(set(all_tracks_genres[-1])) genres_labels = sorted(indexes_by_genre.keys()) all_tracks_genres = np.array(all_tracks_genres) return all_tracks_uris, all_tracks_audio_features, all_tracks_genres, indexes_by_genre, genres_labels # st.session_state['music_extracted'] = dict(all_tracks_uris=all_tracks_uris, # all_tracks_audio_features=all_tracks_audio_features, # genres=genres, # genres_labels=genres_labels) def select_songs(legit_genres): global sp st.subheader("Step 2: Select candidate songs") st.markdown("This can be done in two ways: \n" "1. Get songs from a list of users (and their playlists)\n" "2. Get songs from a list of playlists.\n" "For this you'll need to collect user and/or playlist urls by clicking on \"Share\" and \"Copy link\" in the Spotify app.") users_playlists = "Add a list of user urls, one per line (optional)" users_links = st.text_area(users_playlists, value="") label_playlists = "Add a list of playlists urls, one per line (optional)" playlist_links = st.text_area(label_playlists, value="https://open.spotify.com/playlist/1H7a4q8JZArMQiidRy6qon\nhttps://open.spotify.com/playlist/6wbaZqht4w6CMv3od5taax?si=5c6ebe13fdd049b6") extract_button = centered_button(st.button, 'Extract music', n_columns=5) all_tracks_uris, all_tracks_audio_features, all_tracks_genres, indexes_by_genre, genres_labels = [None] * 5 updated_sources = False if extract_button or debug or 'extract_button' in st.session_state.keys(): if extract_button: updated_sources = True st.session_state['extract_button'] = True # check the user input music sourc if playlist_links == "" and users_links == "": st.warning('Please enter at least one source of music.') else: st.spinner(text="Scanning music sources..") playlist_uris = [] init_time = time.time() init_time_tot = init_time user_playlists = get_filtered_user_playlists(users_links) playlist_uris += user_playlists print(f'1. user playlist: {time.time() - init_time:.2f}') init_time = time.time() new_playlist_uris = get_non_user_playlists(playlist_links) playlist_uris += new_playlist_uris n_users = len(users_links.split('\n')) st.success(f'{len(playlist_uris)} new playlists added from {n_users} users.') print(f'2. non user playlist: {time.time() - init_time:.2f}') init_time = time.time() if str(playlist_uris) in st.session_state.keys(): data_tracks = st.session_state[str(playlist_uris)] else: data_tracks = extract_tracks(playlist_uris) st.session_state[str(playlist_uris)] = data_tracks print(f'3. track extraction: {time.time() - init_time:.2f}') init_time = time.time() if len(data_tracks.keys()) < 10: st.warning('Please select more music sources.') else: all_tracks_uris, all_tracks_audio_features, all_tracks_genres, indexes_by_genre, genres_labels = extract_audio_features(data_tracks, legit_genres) print(f'4. audio feature extraction: {time.time() - init_time:.2f}') print(f'\t total extraction: {time.time() - init_time_tot:.2f}') st.success(f'{len(data_tracks.keys())} tracks found!') return all_tracks_uris, all_tracks_audio_features, all_tracks_genres, indexes_by_genre, genres_labels, updated_sources def customize_widgets(genres_labels, updated_sources): st.subheader("Step 3: Customize it!") st.markdown('##### Which genres?') expanded = True if 'expanded_genres' in st.session_state else False with st.expander("Unroll to select (default all)", expanded=expanded): st.session_state['expanded_genres'] = True st.markdown("Check boxes to select genres. Note: to check all, first uncheck all (bug).") columns = st.columns(np.ones(5)) with columns[1]: check_all = st.button('Check all') with columns[3]: uncheck_all = st.button('Uncheck all') if 'checkboxes' not in st.session_state.keys() or updated_sources: st.session_state['checkboxes'] = [True] * len(genres_labels) updated_sources = False empty_checkboxes = wall_of_checkboxes(genres_labels, max_width=5) if check_all: st.session_state['checkboxes'] = [True] * len(genres_labels) if uncheck_all: st.session_state['checkboxes'] = [False] * len(genres_labels) for i_emc, emc in enumerate(empty_checkboxes): st.session_state['checkboxes'][i_emc] = emc.checkbox(genres_labels[i_emc], value=st.session_state['checkboxes'][i_emc]) st.markdown("##### What's the mood?") valence = st.slider('Valence (0 negative, 100 positive)', min_value=0, max_value=100, value=60, step=1) / 100 energy = st.slider('Energy (0 low, 100 high)', min_value=0, max_value=100, value=60, step=1) / 100 danceability = st.slider('Danceability (0 low, 100 high)', min_value=0, max_value=100, value=60, step=1) / 100 target_mood = np.array([valence, energy, danceability]).reshape(1, 3) streamlit.markdown('##### Shall we explore?') streamlit.write("Set the strength of music exploration:\n" "* 0%: all songs are selected from the music sources\n" "* 100%: all songs are new.") exploration = st.slider('Exploration (0%, 100%)', min_value=0, max_value=100, value=50, step=1) / 100 return target_mood, exploration @st.cache def filter_songs_by_genre(checkboxes, genres_labels, indexes_by_genre): # filter songs by genres selected_labels = [genres_labels[i] for i in range(len(genres_labels)) if checkboxes[i]] genre_selected_indexes = [] for label in selected_labels: genre_selected_indexes += indexes_by_genre[label] genre_selected_indexes = np.array(sorted(set(genre_selected_indexes))) return genre_selected_indexes @st.cache def find_best_songs_for_mood(all_tracks_audio_features, genre_selected_indexes, target_mood): candidate_moods = np.array([np.array(all_tracks_audio_features[feature])[genre_selected_indexes] for feature in ['valence', 'energy', 'danceability']]).T distances = np.sqrt(((candidate_moods - target_mood) ** 2).sum(axis=1)) min_dist_indexes = np.argsort(distances) n_candidates = distances.shape[0] return min_dist_indexes, n_candidates @st.cache def run_exploration(selected_tracks_uris, selected_tracks_genres, playlist_length, exploration, all_tracks_uris, target_mood, selected_genres): # sample exploration songs if exploration > 0: n_known = int(playlist_length * (1 - exploration)) n_new = playlist_length - n_known print(f'Number of new songs: {n_new}, known songs: {n_known}') known_songs = selected_tracks_uris[:n_known] seed_songs = selected_tracks_uris[-n_new:] seed_genres = selected_tracks_genres[-n_new:] dict_args = dict() # enforce bounds on recommendations' moods for i_m, m in enumerate(['valence', 'energy', 'danceability']): dict_args[f'min_{m}'] = max(0, target_mood[i_m] - 0.1) dict_args[f'max_{m}'] = min(1, target_mood[i_m] + 0.1) dict_args_loose = dict() # enforce bounds on recommendations' moods for i_m, m in enumerate(['valence', 'energy', 'danceability']): dict_args_loose[f'min_{m}'] = max(0, target_mood[i_m] - 0.2) dict_args_loose[f'max_{m}'] = min(1, target_mood[i_m] + 0.2) dict_args_looser = dict() # enforce bounds on recommendations' moods for i_m, m in enumerate(['valence', 'energy', 'danceability']): dict_args_loose[f'min_{m}'] = max(0, target_mood[i_m] - 0.3) dict_args_loose[f'max_{m}'] = min(1, target_mood[i_m] + 0.3) new_songs = [] counter_seed = 0 print(selected_genres) while len(new_songs) < n_new: try: print(seed_songs[counter_seed]) print(dict_args) np.random.shuffle(selected_genres) reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], seed_genres=selected_genres, market="from_token", country='from_token', **dict_args)['tracks'] if len(reco) == 0: print('Using loose bounds') np.random.shuffle(selected_genres) reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], seed_genres=selected_genres, market="from_token", country='from_token', **dict_args_loose)['tracks'] if len(reco) == 0: print('Using looser bounds') np.random.shuffle(selected_genres) reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], seed_genres=selected_genres, market="from_token", country='from_token', **dict_args_looser)['tracks'] if len(reco) == 0: print('Removing bounds') reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], market="from_token")['tracks'] assert len(reco) > 0 for r in reco: if r['uri'] not in all_tracks_uris and r['uri'] not in new_songs: new_songs.append(r['uri']) break except: pass print(counter_seed, len(new_songs)) counter_seed = (counter_seed + 1) % len(seed_songs) assert len(new_songs) == n_new assert len(known_songs) == n_known selected_tracks_uris = np.array(list(known_songs) + new_songs) np.random.shuffle(selected_tracks_uris) return selected_tracks_uris @st.cache def sample_playlist(n_candidates, playlist_length, genre_selected_indexes, min_dist_indexes, all_tracks_uris, all_tracks_genres): # give more freedom to randomize the playlist if n_candidates > 5 * playlist_length: selected_tracks_indexes = genre_selected_indexes[min_dist_indexes[:int(playlist_length * 2)]] else: selected_tracks_indexes = genre_selected_indexes[min_dist_indexes[:playlist_length]] shuffled_indexes = np.arange(len(selected_tracks_indexes)) np.random.shuffle(shuffled_indexes) selected_tracks_uris = all_tracks_uris[selected_tracks_indexes][shuffled_indexes] selected_tracks_genres = all_tracks_genres[selected_tracks_indexes][shuffled_indexes] selected_tracks_uris = selected_tracks_uris[:playlist_length] selected_tracks_genres = selected_tracks_genres[:playlist_length] return selected_tracks_uris, selected_tracks_genres def run_app(): global sp setup_credentials() image = Image.open(dir_path + '/image.png') st.image(image) st.markdown("This app let's you quickly build playlists in a customized way: ") st.markdown("* **It's easy**: you won't have to add songs one by one,\n" "* **You're in control**: you provide the source of songs, select genres and pick the mood,\n" "* **You're free to explore**: set the exploration strength from no new songs to all new songs.") sp, user_id, legit_genres, auth_manager = log_to_spotify() if 'login' in st.session_state or debug: all_tracks_uris, all_tracks_audio_features, all_tracks_genres, indexes_by_genre, genres_labels, updated_sources = select_songs(legit_genres) if all_tracks_uris is not None: target_mood, exploration = customize_widgets(genres_labels, updated_sources) custom_button = centered_button(st.button, 'Run customization', n_columns=5) if custom_button or 'run_custom' in st.session_state.keys() or debug: st.session_state['run_custom'] = True checkboxes = st.session_state['checkboxes'].copy() selected_genres = [genres_labels[i] for i in range(len(genres_labels)) if checkboxes[i] and genres_labels[i] != 'unknown'] init_time = time.time() genre_selected_indexes = filter_songs_by_genre(checkboxes, genres_labels, indexes_by_genre) if len(genre_selected_indexes) < 10: genre_selected_indexes = None st.warning('Please select more genres or add more music sources.') else: st.success(f'{len(genre_selected_indexes)} candidate tracks selected.') print(f'6. filter by genre: {time.time() - init_time:.2f}') init_time = time.time() if genre_selected_indexes is not None: min_dist_indexes, n_candidates = find_best_songs_for_mood(all_tracks_audio_features, genre_selected_indexes, target_mood) print(f'7. filter by mood: {time.time() - init_time:.2f}') init_time = time.time() if n_candidates < 25: st.warning('Please add more music sources or select more genres.') else: playlist_length = st.number_input(f'Pick a playlist length, given {n_candidates} candidates.', min_value=5, value=min(10, n_candidates//3), max_value=n_candidates//3) selected_tracks_uris, selected_tracks_genres = sample_playlist(n_candidates, playlist_length, genre_selected_indexes, min_dist_indexes, all_tracks_uris, all_tracks_genres) print(f'8. Sample songs: {time.time() - init_time:.2f}') init_time = time.time() playlist_name = st.text_input('Playlist name', value='Mood Playlist') if playlist_name == '': st.warning('Please enter a playlist name.') else: generation_button = centered_button(st.button, 'Generate playlist', n_columns=5) if generation_button: selected_tracks_uris = run_exploration(selected_tracks_uris, selected_tracks_genres, playlist_length, exploration, all_tracks_uris, target_mood.flatten(), selected_genres) print(f'9. run exploration: {time.time() - init_time:.2f}') init_time = time.time() target_mood = np.array(target_mood).flatten() * 100 description = f'Emotion Playlist for Valence: {int(target_mood[0])}, ' \ f'Energy: {int(target_mood[1])}, ' \ f'Danceability: {int(target_mood[2])}). ' \ f'Playlist generated by the EmotionPlaylist app: https://huggingface.co/spaces/ccolas/EmotionPlaylist.' playlist_info = sp.user_playlist_create(user_id, playlist_name, public=True, collaborative=False, description=description) playlist_uri = playlist_info['uri'].split(':')[-1] sp.playlist_add_items(playlist_uri, selected_tracks_uris) st.write( f"""
""", unsafe_allow_html=True) st.success(f'The playlist has been generated, find it [here](https://open.spotify.com/playlist/{playlist_uri}).') stop = 1 if __name__ == '__main__': run_app()