update

app.py

@@ -2,7 +2,26 @@ import gradio as gr
 import numpy as np
 import pandas as pd
 from sklearn.metrics.pairwise import cosine_similarity
-from datasets import load_dataset
 
-dataset = load_dataset("sheacon/song_lyrics")
+import os
+import requests
 
+url = 'https://huggingface.co/datasets/sheacon/song_lyrics/resolve/main/v2ga_w_embeddings.parquet'
+response = requests.get(url, stream=True)
+
+filename = os.path.join(os.getcwd(), url.split('/')[-1])
+with open(filename, 'wb') as file:
+    for chunk in response.iter_content(chunk_size=8192):
+        if chunk:
+            file.write(chunk)
+
+print(f"File '{filename}' has been downloaded to the present working directory.")
+
+
+pwd = os.getcwd()
+print("Present Working Directory:", pwd)
+
+contents = os.listdir(pwd)
+print("Contents of the Directory:")
+for item in contents:
+    print(item)

requirements.txt

@@ -1,4 +1,4 @@
 gradio
 pandas
 scikit-learn
-datasets
+requests