Resolving more issues

app.py

@@ -50,7 +50,7 @@ if st.button("GO!"):
 	prompt = process_text(topic)
 	model = get_model()
 	prompt_embedded = model.encode(prompt)
-	df_embed = pd.read_pickle('../data/embeddings_pkl.pkl').drop_duplicates(subset=['titles'])
+	df_embed = pd.read_pickle('data/embeddings_pkl.pkl').drop_duplicates(subset=['titles'])
 	df_embed["similarity_scores"] = df_embed["abstracts_embeddings"].apply(lambda x: get_cosine_similarity(x, prompt_embedded))
 	top_n = df_embed.nlargest(number, 'similarity_scores').head(5)["titles"].to_list()
 	st.text(" ")