correct parquet read

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import numpy as np
 import pandas as pd
+import pyarrow
 from sklearn.metrics.pairwise import cosine_similarity
 
 import os
@@ -26,7 +27,7 @@ print("Contents of the Directory:")
 for item in contents:
     print(item)
 
-df = pd.read_csv('v2ga_w_embeddings.parquet')
+df = pd.read_parquet('v2ga_w_embeddings.parquet')
 
 def get_most_similar_songs(artist, title, df):
     def find_most_similar(embedding_column):

requirements.txt

@@ -1,4 +1,5 @@
 gradio
 pandas
 scikit-learn
-requests
+requests
+pyarrow