File size: 22,137 Bytes
bc64e5a
 
cb32cb9
 
 
80d5795
3dd7abd
80d5795
1767f84
ca32a6a
36321f6
3dd7abd
cb32cb9
dde73a1
cb32cb9
 
dde73a1
cb32cb9
 
80d5795
cb32cb9
 
3dd7abd
 
 
 
 
bc64e5a
3dd7abd
bc64e5a
cb32cb9
 
bc64e5a
fad5ae9
 
 
3dd7abd
bc64e5a
fad5ae9
bc64e5a
cb32cb9
 
300f883
80d5795
 
 
 
 
 
 
300f883
 
 
 
80d5795
 
 
 
 
 
 
 
 
 
 
 
bc64e5a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80d5795
 
 
 
 
300f883
80d5795
 
 
 
 
 
 
 
 
 
cb32cb9
80d5795
 
 
 
 
 
 
 
 
 
 
 
300f883
 
 
80d5795
dbea0da
 
80d5795
 
 
dbea0da
 
 
 
 
1767f84
dbea0da
 
 
 
 
 
80d5795
 
 
 
 
 
 
 
 
 
 
dde73a1
80d5795
300f883
80d5795
 
dbea0da
80d5795
 
dbea0da
d7dfcdc
80d5795
dbea0da
 
80d5795
0b9ab43
80d5795
 
 
cb32cb9
80d5795
 
 
 
 
 
 
 
 
300f883
 
80d5795
 
 
 
 
 
 
 
 
300f883
 
 
dbea0da
300f883
 
 
dbea0da
cb32cb9
dbea0da
80d5795
bc64e5a
 
 
 
 
dde73a1
bc64e5a
 
 
 
 
 
dbea0da
bc64e5a
dbea0da
bc64e5a
 
 
 
 
 
 
 
80d5795
 
bc64e5a
 
 
80d5795
bc64e5a
 
 
 
 
 
 
80d5795
 
dbea0da
80d5795
 
 
 
dbea0da
80d5795
 
cb32cb9
bc64e5a
80d5795
 
 
 
 
 
cb32cb9
bc64e5a
cda8a3a
bc64e5a
 
 
 
 
 
 
dbea0da
bc64e5a
 
 
 
 
 
 
 
 
 
 
 
 
 
cda8a3a
bc64e5a
 
 
 
cda8a3a
 
dbea0da
bc64e5a
 
cda8a3a
 
dbea0da
bc64e5a
 
cda8a3a
 
dbea0da
bc64e5a
 
 
 
 
563e52e
bc64e5a
 
cda8a3a
bc64e5a
 
 
 
 
 
 
 
 
 
 
 
dbea0da
bc64e5a
 
 
 
 
 
dbea0da
 
 
 
bc64e5a
dbea0da
 
cb32cb9
80d5795
3dd7abd
 
80d5795
cb32cb9
80d5795
 
 
 
dde73a1
 
bc64e5a
 
80d5795
 
dbea0da
3dd7abd
80d5795
dbea0da
80d5795
dbea0da
80d5795
 
cda8a3a
80d5795
dbea0da
80d5795
 
 
cb32cb9
80d5795
 
 
 
 
 
 
bc64e5a
80d5795
 
cb32cb9
80d5795
bc64e5a
80d5795
dbea0da
 
bc64e5a
 
80d5795
 
 
 
 
 
 
dbea0da
cda8a3a
bc64e5a
 
 
300f883
 
 
 
80d5795
 
 
 
 
 
 
 
 
 
 
 
 
 
cb32cb9
 
 
 
 
80d5795
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
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"""
                                    <html>
                                    <body>
                                    <center>
                                    <iframe style = "border-radius:12px" src="https://open.spotify.com/embed/playlist/{playlist_uri}" allowtransparency="true"
                                     allow="encrypted-media" width="80%" height="580" frameborder="0"></iframe></center></body></html>
                                    """, 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()