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Update app.py
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app.py
CHANGED
@@ -1,3 +1,5 @@
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from PIL import Image
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from utils import *
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from app_utils import *
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@@ -23,18 +25,19 @@ def log_to_spotify():
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client_credentials_manager = SpotifyClientCredentials()
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sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager)
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user_id = None
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else:
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sp, user_id = new_get_client(session=st.session_state)
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if sp != None:
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legit_genres = sp.recommendation_genre_seeds()['genres']
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st.session_state['login'] = (sp, user_id, legit_genres)
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st.success('You are logged in.')
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else:
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legit_genres = None
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else:
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sp, user_id, legit_genres = st.session_state['login']
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st.success('You are logged in.')
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return sp, user_id, legit_genres
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@st.cache(suppress_st_warning=True)
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@@ -61,27 +64,28 @@ def get_filtered_user_playlists(user_links):
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if n_playlists <= 1:
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return all_uris
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else:
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if filter_playlist:
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return list(np.array(all_uris)[np.where(st.session_state['checkboxes_playlists'])])
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else:
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@@ -187,31 +191,41 @@ def select_songs(legit_genres):
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def customize_widgets(genres_labels):
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st.subheader("Step 3: Customize it!")
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st.markdown(
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with
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st.markdown("##### What's the mood?")
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valence = st.slider('Valence (0 negative, 100 positive)', min_value=0, max_value=100, value=
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energy = st.slider('Energy (0 low, 100 high)', min_value=0, max_value=100, value=
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danceability = st.slider('Danceability (0 low, 100 high)', min_value=0, max_value=100, value=
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target_mood = np.array([valence, energy, danceability]).reshape(1, 3)
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@st.cache
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def filter_songs_by_genre(checkboxes, genres_labels, genres):
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@@ -223,6 +237,7 @@ def filter_songs_by_genre(checkboxes, genres_labels, genres):
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genre_selected_indexes = np.array(sorted(set(genre_selected_indexes)))
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return genre_selected_indexes
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def find_best_songs_for_mood(all_tracks_audio_features, genre_selected_indexes, target_mood):
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candidate_moods = np.array([np.array(all_tracks_audio_features[feature])[genre_selected_indexes] for feature in ['valence', 'energy', 'danceability']]).T
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distances = np.sqrt(((candidate_moods - target_mood) ** 2).sum(axis=1))
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@@ -230,6 +245,72 @@ def find_best_songs_for_mood(all_tracks_audio_features, genre_selected_indexes,
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n_candidates = distances.shape[0]
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return min_dist_indexes, n_candidates
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def run_app():
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global sp
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@@ -243,13 +324,19 @@ def run_app():
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"* **You're in control**: you provide a source of candidate songs, select a list of genres and choose the mood for the playlist.")
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fake = centered_button(st.button, "Let's go", n_columns=7, disabled=True)
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sp, user_id, legit_genres = log_to_spotify()
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if 'login' in st.session_state or debug:
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all_tracks_uris, all_tracks_audio_features, genres, genres_labels = select_songs(legit_genres)
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if all_tracks_uris is not None:
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target_mood = customize_widgets(genres_labels)
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custom_button = centered_button(st.button, 'Run customization', n_columns=5)
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if custom_button or 'run_custom' in st.session_state.keys():
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st.session_state['run_custom'] = True
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@@ -265,27 +352,29 @@ def run_app():
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init_time = time.time()
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if genre_selected_indexes is not None:
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min_dist_indexes, n_candidates = find_best_songs_for_mood(all_tracks_audio_features, genre_selected_indexes, target_mood)
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print(f'7. filter by mood: {time.time() - init_time:.2f}')
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init_time = time.time()
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if n_candidates < 25:
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st.warning('Please add more music sources or select more genres.')
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else:
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playlist_length = st.number_input(f'Pick a playlist length, given {n_candidates} candidates.', min_value=5,
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value=min(10, n_candidates//
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playlist_name = st.text_input('Playlist name', value='Mood Playlist')
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if playlist_name == '':
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st.warning('Please enter a playlist name.')
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else:
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print(f'8. build playlist: {time.time() - init_time:.2f}')
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init_time = time.time()
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generation_button = centered_button(st.button, 'Generate playlist', n_columns=5)
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if generation_button:
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target_mood = np.array(target_mood).flatten() * 100
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description = f'Emotion Playlist for Valence: {int(target_mood[0])}, ' \
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f'Energy: {int(target_mood[1])}, ' \
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import requests
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import streamlit
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from PIL import Image
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from utils import *
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from app_utils import *
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client_credentials_manager = SpotifyClientCredentials()
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sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager)
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user_id = None
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auth_manager = None
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else:
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sp, user_id, auth_manager = new_get_client(session=st.session_state)
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if sp != None:
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legit_genres = sp.recommendation_genre_seeds()['genres']
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st.session_state['login'] = (sp, user_id, legit_genres, auth_manager)
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st.success('You are logged in.')
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else:
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legit_genres = None
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else:
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sp, user_id, legit_genres, auth_manager = st.session_state['login']
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st.success('You are logged in.')
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return sp, user_id, legit_genres, auth_manager
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@st.cache(suppress_st_warning=True)
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if n_playlists <= 1:
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return all_uris
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else:
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with st.expander("##### Select user playlists (default all)"):
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# let the user uncheck playlists
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st.markdown("Check boxes to select playlists from the selected users."
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"Note: to check all, first uncheck all (bug).")
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columns = st.columns(np.ones(5))
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with columns[1]:
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check_all_playlists = st.button('Check all')
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with columns[3]:
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uncheck_all_playlists = st.button('Uncheck all')
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if 'checkboxes' not in st.session_state.keys():
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st.session_state['checkboxes_playlists'] = [True] * n_playlists
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empty_checkboxes = wall_of_checkboxes(all_names, max_width=5)
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if check_all_playlists:
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st.session_state['checkboxes_playlists'] = [True] * n_playlists
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if uncheck_all_playlists:
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st.session_state['checkboxes_playlists'] = [False] * n_playlists
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for i_emc, emc in enumerate(empty_checkboxes):
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st.session_state['checkboxes_playlists'][i_emc] = emc.checkbox(all_names[i_emc], value=st.session_state['checkboxes_playlists'][i_emc])
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filter_playlist = centered_button(st.button, 'Update user playlists', n_columns=5)
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if filter_playlist:
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return list(np.array(all_uris)[np.where(st.session_state['checkboxes_playlists'])])
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else:
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def customize_widgets(genres_labels):
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st.subheader("Step 3: Customize it!")
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st.markdown('##### Which genres?')
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expanded = True if 'expanded_genres' in st.session_state else False
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with st.expander("Unroll to select (default all)", expanded=expanded):
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st.session_state['expanded_genres'] = True
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st.markdown("Check boxes to select genres, see how many tracks were selected below. Note: to check all, first uncheck all (bug).")
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columns = st.columns(np.ones(5))
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with columns[1]:
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check_all = st.button('Check all')
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with columns[3]:
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uncheck_all = st.button('Uncheck all')
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if 'checkboxes' not in st.session_state.keys():
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st.session_state['checkboxes'] = [True] * len(genres_labels)
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empty_checkboxes = wall_of_checkboxes(genres_labels, max_width=5)
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if check_all:
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st.session_state['checkboxes'] = [True] * len(genres_labels)
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if uncheck_all:
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st.session_state['checkboxes'] = [False] * len(genres_labels)
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for i_emc, emc in enumerate(empty_checkboxes):
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st.session_state['checkboxes'][i_emc] = emc.checkbox(genres_labels[i_emc], value=st.session_state['checkboxes'][i_emc])
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st.markdown("##### What's the mood?")
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valence = st.slider('Valence (0 negative, 100 positive)', min_value=0, max_value=100, value=60, step=1) / 100
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energy = st.slider('Energy (0 low, 100 high)', min_value=0, max_value=100, value=60, step=1) / 100
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danceability = st.slider('Danceability (0 low, 100 high)', min_value=0, max_value=100, value=60, step=1) / 100
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target_mood = np.array([valence, energy, danceability]).reshape(1, 3)
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streamlit.markdown('##### Shall we explore?')
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streamlit.write("Set the strength of music exploration:\n"
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"* 0%: all songs are selected from the music sources\n"
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"* 100%: all songs are new.")
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exploration = st.slider('Exploration (0%, 100%)', min_value=0, max_value=100, value=50, step=1) / 100
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return target_mood, exploration
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@st.cache
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def filter_songs_by_genre(checkboxes, genres_labels, genres):
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genre_selected_indexes = np.array(sorted(set(genre_selected_indexes)))
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return genre_selected_indexes
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@st.cache
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def find_best_songs_for_mood(all_tracks_audio_features, genre_selected_indexes, target_mood):
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candidate_moods = np.array([np.array(all_tracks_audio_features[feature])[genre_selected_indexes] for feature in ['valence', 'energy', 'danceability']]).T
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distances = np.sqrt(((candidate_moods - target_mood) ** 2).sum(axis=1))
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n_candidates = distances.shape[0]
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return min_dist_indexes, n_candidates
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@st.cache
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def run_exploration(selected_tracks_uris, playlist_length, exploration, all_tracks_uris, target_mood, reauthenticate):
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# sample exploration songs
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if exploration > 0:
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n_known = int(playlist_length * (1 - exploration))
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n_new = playlist_length - n_known
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print(f'Number of new songs: {n_new}, known songs: {n_known}')
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known_songs = selected_tracks_uris[:n_known]
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seed_songs = selected_tracks_uris[-n_new:]
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dict_args = dict() # enforce bounds on recommendations' moods
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for i_m, m in enumerate(['valence', 'energy', 'danceability']):
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dict_args[f'min_{m}'] = max(0, target_mood[i_m] - 0.1)
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dict_args[f'max_{m}'] = min(1, target_mood[i_m] + 0.1)
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dict_args_loose = dict() # enforce bounds on recommendations' moods
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for i_m, m in enumerate(['valence', 'energy', 'danceability']):
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dict_args_loose[f'min_{m}'] = max(0, target_mood[i_m] - 0.2)
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dict_args_loose[f'max_{m}'] = min(1, target_mood[i_m] + 0.2)
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dict_args_looser = dict() # enforce bounds on recommendations' moods
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for i_m, m in enumerate(['valence', 'energy', 'danceability']):
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dict_args_loose[f'min_{m}'] = max(0, target_mood[i_m] - 0.3)
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dict_args_loose[f'max_{m}'] = min(1, target_mood[i_m] + 0.3)
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new_songs = []
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counter_seed = 0
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counter_failure = 0
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while len(new_songs) < n_new:
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try:
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print(seed_songs[counter_seed])
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print(dict_args)
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reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], market="from_token", **dict_args)['tracks']
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if len(reco) == 0:
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print('Using loose bounds')
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reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], market="from_token", **dict_args_loose)['tracks']
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if len(reco) == 0:
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print('Using looser bounds')
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reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], market="from_token", **dict_args_looser)['tracks']
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if len(reco) == 0:
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print('Removing bounds')
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reco = sp.recommendations(seed_tracks=[seed_songs[counter_seed]], market="from_token")['tracks']
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assert len(reco) > 0
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for r in reco:
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if r['uri'] not in all_tracks_uris:
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new_songs.append(r['uri'])
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break
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except:
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pass
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print(counter_seed, len(new_songs))
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counter_seed = (counter_seed + 1) % len(seed_songs)
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assert len(new_songs) == n_new
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assert len(known_songs) == n_known
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selected_tracks_uris = np.array(list(known_songs) + new_songs)
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np.random.shuffle(selected_tracks_uris)
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return selected_tracks_uris
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@st.cache
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def sample_playlist(n_candidates, playlist_length, genre_selected_indexes, min_dist_indexes, all_tracks_uris):
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# give more freedom to randomize the playlist
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if n_candidates > 5 * playlist_length:
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selected_tracks_indexes = genre_selected_indexes[min_dist_indexes[:int(playlist_length * 2)]]
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else:
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selected_tracks_indexes = genre_selected_indexes[min_dist_indexes[:playlist_length]]
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selected_tracks_uris = all_tracks_uris[selected_tracks_indexes]
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np.random.shuffle(selected_tracks_uris)
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selected_tracks_uris = selected_tracks_uris[:playlist_length]
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return selected_tracks_uris
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def run_app():
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global sp
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"* **You're in control**: you provide a source of candidate songs, select a list of genres and choose the mood for the playlist.")
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fake = centered_button(st.button, "Let's go", n_columns=7, disabled=True)
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sp, user_id, legit_genres, auth_manager = log_to_spotify()
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def reauthenticate():
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global sp
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auth_manager.get_access_token(st.experimental_get_query_params()['code'])
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sp = spotipy.Spotify(auth_manager=auth_manager)
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return sp
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if 'login' in st.session_state or debug:
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all_tracks_uris, all_tracks_audio_features, genres, genres_labels = select_songs(legit_genres)
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if all_tracks_uris is not None:
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target_mood, exploration = customize_widgets(genres_labels)
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custom_button = centered_button(st.button, 'Run customization', n_columns=5)
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if custom_button or 'run_custom' in st.session_state.keys():
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st.session_state['run_custom'] = True
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init_time = time.time()
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if genre_selected_indexes is not None:
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min_dist_indexes, n_candidates = find_best_songs_for_mood(all_tracks_audio_features, genre_selected_indexes, target_mood)
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print(f'7. filter by mood: {time.time() - init_time:.2f}')
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init_time = time.time()
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if n_candidates < 25:
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st.warning('Please add more music sources or select more genres.')
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else:
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361 |
playlist_length = st.number_input(f'Pick a playlist length, given {n_candidates} candidates.', min_value=5,
|
362 |
+
value=min(10, n_candidates//3), max_value=n_candidates//3)
|
363 |
|
364 |
+
selected_tracks_uris = sample_playlist(n_candidates, playlist_length, genre_selected_indexes, min_dist_indexes, all_tracks_uris)
|
365 |
+
print(f'8. Sample songs: {time.time() - init_time:.2f}')
|
366 |
+
init_time = time.time()
|
367 |
|
368 |
playlist_name = st.text_input('Playlist name', value='Mood Playlist')
|
369 |
if playlist_name == '':
|
370 |
st.warning('Please enter a playlist name.')
|
371 |
else:
|
|
|
|
|
372 |
generation_button = centered_button(st.button, 'Generate playlist', n_columns=5)
|
373 |
if generation_button:
|
374 |
+
selected_tracks_uris = run_exploration(selected_tracks_uris, playlist_length, exploration, all_tracks_uris, target_mood.flatten(), reauthenticate)
|
375 |
+
print(f'9. run exploration: {time.time() - init_time:.2f}')
|
376 |
+
init_time = time.time()
|
377 |
+
|
378 |
target_mood = np.array(target_mood).flatten() * 100
|
379 |
description = f'Emotion Playlist for Valence: {int(target_mood[0])}, ' \
|
380 |
f'Energy: {int(target_mood[1])}, ' \
|