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app.py

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+# importing libraries
+import gradio as gr
+import pickle
+import pandas as pd
+from huggingface_hub import hf_hub_download
+import json
+import requests
+
+pd.options.mode.chained_assignment = None  # Turn off SettingWithCopyWarning
+
+
+songs_df = pd.read_csv(
+  hf_hub_download('damilojohn/Personal_Playlist_Generator',
+                  repo_type='dataset',
+                  filename='spotify_transformed.csv'))
+mappings = pd.read_csv(
+  hf_hub_download('damilojohn/Personal_Playlist_Generator',
+                  repo_type='dataset',
+                  filename='song_mappings.csv'))
+verses_df = pd.read_csv(
+  hf_hub_download('damilojohn/Personal_Playlist_Generator',
+                  repo_type='dataset',
+                  filename='verses.csv'))
+song_embeddings = pickle.load(
+  open(hf_hub_download('damilojohn/Personal_Playlist_Generator',
+                       repo_type='dataset',
+                       filename='embeddings.pkl'), 'rb'))
+
+verses_df.rename(columns={'0': 'verse'}, inplace=True)
+mappings.rename(columns={'Unnamed: 0': 'verse', '0': 'song_name'},
+                inplace=True)
+
+
+def generate_playlist(prompt):
+    payload = {'prompt': prompt}
+    response = requests.request('POST',
+                                url='https://xi5j0hwh1a.execute-api.eu-west-2.amazonaws.com/test/huh',
+                                data=json.dumps(payload)).json()
+    hits = response['hits']
+    hits = pd.DataFrame.from_dict(hits[0])
+    verses_match = verses_df.iloc[hits['corpus_id']]
+    songs_match = mappings[mappings['verse'].isin(
+        verses_match['verse'].values)]
+    songs_match = songs_df[songs_df['song_name'].isin(
+        songs_match['song_name'].values)]
+    songs_match = songs_match.sort_values('song_name')
+    songs_match = songs_match.drop_duplicates(subset='song_name')
+    songs_name = list(songs_match['song_name'][:9])
+    cover_art = list(songs_match['image'][:9])
+    images = [gr.Image.update(value=art, visible=True) for art in cover_art]
+    return (gr.Radio.update(label='songs', interactive=True,
+                            choices=songs_name),
+            *images)
+
+
+def set_example_prompt(examples):
+    return gr.TextArea.update(value=examples[0])
+
+
+def create_frontend():
+    demo = gr.Blocks()
+    with demo:
+        gr.Markdown(
+            '''
+            # A Text based playlist Generator for Afrobeats
+
+            '''
+        )
+        with gr.Row():
+            with gr.Column():
+                gr.Markdown(
+                    '''
+                    Enter words describing your playlist
+                    '''
+                )
+                song_prompt = gr.TextArea(
+                    value='',
+                    placeholder=" Enter a sentence that describes how you're feeling or what you want your playlist to be about "
+                )
+                example_prompts = gr.Dataset(
+                    components=[song_prompt],
+                    samples=[
+                        ['heartbreak'],
+                        ['love at the beach'],
+                        ['uncertainty and bleak hopes']
+                    ]
+                )
+            with gr.Column():
+                fetch_songs = gr.Button(
+                    value='Enter to see playlist',).style(full_width=True)
+
+            with gr.Column():
+                song_options = gr.Radio(label='songs', interactive=True,
+                                        choices=None, type='value',
+                                        visible=True)
+            with gr.Column():
+                with gr.Row():
+                    tile1 = gr.Image(value="/content/songs_cover.jpg",
+                                     show_label=False, visible=True)
+                    tile2 = gr.Image(value="/content/songs_cover.jpg",
+                                     show_label=False, visible=True)
+                    tile3 = gr.Image(value="/content/songs_cover.jpg",
+                                     show_label=False, visible=True)
+                with gr.Row():
+                    tile4 = gr.Image(value="/content/songs_cover.jpg",
+                                     show_label=False, visible=True)
+                    tile5 = gr.Image(value="/content/songs_cover.jpg",
+                                     show_label=False, visible=True)
+                    tile6 = gr.Image(value="/content/songs_cover.jpg",
+                                     show_label=False, visible=True)
+                with gr.Row():
+                    tile7 = gr.Image(value="/content/songs_cover.jpg",
+                                     show_label=False, visible=True)
+                    tile8 = gr.Image(value='/content/songs_cover.jpg',
+                                     show_label=False, visible=True)
+
+            tiles = [tile1, tile2, tile3, tile4, tile5, tile6, tile7, tile8]
+
+            fetch_songs.click(
+                fn=generate_playlist,
+                inputs=[song_prompt],
+                outputs=[song_options, *tiles]
+            )
+            example_prompts.click(
+                fn=set_example_prompt,
+                inputs=[example_prompts],
+                outputs=example_prompts.components
+            )
+
+    demo.launch(debug=True)
+
+
+def main():
+    create_frontend()
+
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+sentence-transformers
+spotify
+requests_html
+boto3
+datasets
+# torch --extra-index-url https://download.pytorch.org/whl/cpu
+torch
+loguru
+huggingface-hub
+wandb